In the second part of this contribution, the reasoning is extended to a number of traditional arguments in favour of randomization. This discussion is rather non-technical, and sometimes touches on the rather fundamental Frequentist/Bayesian debate. However, the result of this analysis turns out to be quite similar: While the contribution of randomization remains doubtful, comparability contributes much to a compelling conclusion. Summing up, classical experimentation based on sound background theory and the systematic construction of exchangeable groups seems to be advisable.According to R.A. Fisher, randomization “relieves the experimenter from the anxiety of considering innumerable causes by which the data may be disturbed.” Since, in particular, it is said to control for known and unknown nuisance factors that may considerably challenge the validity of a result, it has become very popular. This contribution challenges the received view. First, looking for quantitative support, we study a number of straightforward, mathematically simple models. They all demonstrate that the optimism surrounding randomization is questionable: In small to medium-sized samples, random allocation of units to treatments typically  Fisher . Arguablmethod of difference. Straightforward algebra gives,Given some constant i = 10 and k = 3, which specifies the requirement that most samples be located within a rather tight acceptable range. In this case, one has to consider the functions n/10 and n are shown in the following figure :i) decreases the number of subjects necessary:k:Thus, depending on p is rather low.  Otherwise there is hardly any guarantee that the two groups will be comparable. Rather, they will differ considerably due to random fluctuations.This shows that randomization works, if the number of subjects ranges in the hundreds or if the probability D is well known  that two groups, constructed by randomization, will be comparable. If i = 5, i.e., if one fifth of the range of ∣D∣ is judged to be comparable, we obtain:Therefore, it is also possible to compute the probability m independent binary factors, each of them occurring with probability p, the probability that the groups will be balanced with respect to all nuisance variables is qm. Numerically, the above results yield:The situation becomes worse if one takes more than one nuisance factor into account. Given m independent binary factors, each occurring with probability pj ), the probabilities closest to 1/2 will dominate 1 − q1⋯qm, which is the probability that the two groups are not comparable due to an imbalance in at least one variable. In a typical study with 2n = 100 persons, for example, it does not matter if there are one, two, five or even ten factors, if each of them occurs with probability of 1/100. However, if some of the factors are rather common (e.g. 1/5 < pj < 4/5), this changes considerably. In a smaller study with fewer than 2n = 50 participants, a few such factors suffice to increase the probability that the groups constructed by randomization won’t be comparable to 50%. With only a few units per group, one can be reasonably sure that some undetected, but rather common, nuisance factor(s) will make the groups non-comparable. Altogether our conclusion based on an explicit quantitative analysis coincides with the qualitative argument given by  covariates, then the balance might well have been better [for those covariates], but there would be no basis for expecting other unmeasured variables to be similarly balanced hints at further undetectable imbalances in unobserved variables.This is a straightforward and popular argument in favour of randomization. Since randomization treats known and unknown factors alike, it is quite an asset that one may thus infer from the observed to the unobserved without further assumptions. However, this argument backfires immediately since, for exactly the same reason, an imbalance in an observed variable cannot be judged as harmless. Quite the contrary: With random assignment there is some basis for expecting other unmeasured variables to be similarly unbalanced. An observed imbalance Moreover, treating known and unknown factors equivalently is cold comfort compared to the considerable amount of imbalance evoked by randomization. Fisher’s favourite method always comes with the cost that it introduces additional variability, whereas a systematic schema at least balances known factors. In subject areas haunted by heterogeneity it seems intuitively right to deliberately work in favour of comparability, and rather odd to introduce further variability.X, an unobserved factor Y, and their dependence structure in more detail. Without loss of generality let all functions d be positive in the following. Having constructed two groups of equal size via randomization, suppose X. Using a systematic scheme instead, i.e., distributing the units among T and C in a more balanced way, this may be reduced to dS(X).In order to sharpen these qualitative arguments, let us look at an observed factor dR(Y), the balance between the groups with respect to another variable. Now there are three types of dependence structures:The crucial question is how such a manipulation affects dS(Y) < dR(Y). In other words, the effort of balancing X pays off, since the increased comparability in this variable carries over to Y. For example, given today’s occupational structures with women earning considerably less than men, balancing for gender should also even out differences in income.A benign dependence structure may be characterized by X has no effect on Y, dS(Y) ≈ dR(Y), no harm is done. For example, balancing for gender should not affect the distribution of blood type in the observed groups, since blood type is independent of gender.If balancing in X has the opposite effect on Y, one may face troubles. As an example, let there be four pairs  = ;  = ;  = ; and  = . Putting units 1 and 4 in one group, and units 2 and 3 in another, yields a perfect balance in the first variable, but the worst imbalance possible in the second.Only in the pathological case when increasing the balance in d(⋅) < c where the constant (threshold) c defines comparability. Then, in the randomized case, the groups are comparable if both dR(X) and dR(Y) are smaller than c. By construction, dS(X) ≤ dR(X) < c, i.e., the systematically composed groups are also comparable with respect to X. Given a malign dependence structure, dS(Y) increases and may exceed dR(Y). Yet dS(Y) < c may still hold, since, in this case, the “safety margin” c − dR(Y) may prevent the systematically constructed groups from becoming non-comparable with respect to property Y. In large samples, c − dR(⋅) is considerable for both variables. Therefore, in most cases, consciously constructed samples will (still) be comparable. Moreover, the whole argument easily extends to more than two factors.However, suppose In a nutshell, endeavouring to balance relevant variables pays off. A conscious balancing schema equates known factors better than chance and may have some positive effect on related, but unknown, variables. If the balancing schema has no effect on an unknown factor, the latter is treated as if randomization were interfering—i.e. in a completely nonsystematic, ‘neutral’ way. Only if there is a malign dependence structure, when systematically balancing some variable yields (considerable) “collateral damage”, might randomization be preferable.n is  large. Yet if n is large, so are the “safety margins” in the variables, and even an unfortunate dependence structure won’t do any harm. If n is smaller, the above models show that systematic efforts, rather than randomization, may yield comparability. Given a small number of units, both approaches only have a chance of succeeding if there are hardly any unknown nuisance factors, or if there is a benign dependence structure, i.e., if a balance in some variable (no matter how achieved) has a positive effect on others. In particular, if the number of relevant nuisance factors and interactions is small, it pays to isolate and control for a handful of obviously influential variables, which is a crucial ingredient of experimentation in the classical natural sciences. Our overall conclusion may thus be summarized in the following table  number of nuisance factors can be captured by a single probability statement. How is this remarkable goal achieved?In a statistical experiment one controls the random mechanism, thus the experimenter knows the sample space and the distribution in question. This constructed and therefore “valid” framework keeps nuisance variables at bay, and sound reasoning within the paradigm leads to correct results. Someone following this “Frequentist” train of thought could therefore state—and several referees of this contribution have indeed done so—that the above models underline the rather well-known fact that randomization can have difficulties in constructing similar groups , in particular if Any analytical procedure, e.g., a statistical test, is an algorithm, transferring some numerical input into a certain output which, in the simplest case, is just a number. Given the same data, it yields exactly the same result. The procedure does not go any further: In general, there are no semantics or convincing story associated with a bare numerical result that could increase the latter’s impact. In other words, a strong interpretation needs to be based on the framework in which the calculations are embedded.T and C should be due to the experimental intervention.Now, since randomization treats all variables (known and unknown) alike, the analytical procedure is able to “catch” them all and their effects show up in the output. For example, a confidence interval, so the story goes, gives a quantitative estimate of all of the variables’ impact. One can thus numerically assess how strong this influence is, and one has, in a sense, achieved explicit quantitative control. In particular, if the total influence of all nuisance factors (including random fluctuations due to randomization) is numerically small, one may conclude with some confidence that a substantial difference between Following this line of argument, owing to randomization, a statistical experiment gives a valid result in the sense that it allows for far-reaching, in particular causal, conclusions. Thus, from a Frequentist point of view, one should distinguish between two very different kinds of input: (randomized) experimental data on the one hand and (non-randomized) non-experimental data on the other. Moreover, since randomization seems to be crucial—at least sufficient—for a causal conclusion, some are convinced that it is also necessary. For example, the frequently heard remark that “only randomization can break a causal link” −10 = 0.001, showing that what we observe is not likely due to chance alone, or that it is very likely the new drug is better than the old one … Such simplicity is difficult to beat. Given that a physical randomization was actually used, very little extra assumption is needed to produce a valid conclusion.A new eye drug was tested against an old one on 10 subjects. The drugs were randomly assigned to both eyes of each person. In all cases the new drug performed better than the old drug. The P-value from the observed data is 2This train of thought is supplemented by the observation that random assignment is easy to implement, and that hardly any (questionable) assumptions are needed in order to get a strong conclusion. For example, Pawitan  says:A Finally, one finds a rather broad range of verbal arguments why randomization should be employed, e.g. “valid” conclusions, either based on the randomization distribution  or some Traditionally, criticism of the Frequentist line of argument in general, and randomization in particular, has come from the Bayesian school of statistics. While Frequentist statistics is much concerned with the way data is collected, focusing on the design of experiments, the corresponding sample space and sampling distribution, Bayesian statistics is rather concerned with the data actually obtained. Its focus is on learning from the(se) data—in particular with the help of Bayes’ theorem—and the parameter space.In a sense, both viewpoints are perfectly natural and do not contradict one other. However, the example of randomization shows that this cannot be the final word: For the pre-data view, randomization is essential; it constitutes the difference between a real statistical experiment and any kind of quasi-experiment. For the post-data view, however, randomization does not add much to the information at hand, and is ancillary or just a nuisance.p ≫ n).The crucial and rather fundamental issue therefore becomes how far-reaching the conclusions of each of these styles of inference are. To cut a long story short, despite a “valid” framework and mathematically sound conclusions a Frequentist train of thought may easily miss its target or might even go astray.  After The idea that the influence of many nuisance factors—even unknown ones—may be caught by a simple experimental device and some probability theory is a bold claim. Therefore it should come as no surprise that some Frequentist statisticians, many scientists and most Bayesians have questioned it. For example, towards the end of his article, Basu  writes qvery tight hypothesis this calculation is obviously logically sound” . I). I7]). n is not too small” is a verbal statement, implicitly appealing to the central limit theorem. Owing to the latter theorem, groups created by random assignment tend to become similar. The informal assurance, affirming that this happens fast, ranks among the most prominent conventions of traditional statistics. However, explicit numerical models underline that our intuition needs to be corrected. Rather straightforward calculations suffice to show that fluctuations cannot be dismissed easily, even if n is large.Our analysis above fits in nicely: The standard phrase “if narrative prior to the data that makes such a tremendous difference in the end. Since heuristic arguments have a certain power of persuasion which is certainly weaker than a crisp formal derivation or a strict mathematical proof, it seems to be no coincidence that opinion on this matter has remained divided. Followers of Fisher believed in his intuition and trusted randomization; critics did not. And since, sociologically speaking, the Frequentist school dominated the field for decades, so did randomization.Worse still, the crucial part of the Frequentist’s main argument in favour of randomization is informal in a rather principled way: In an experimental, as well as in a similar non-experimental situation, the core formal machinery, i.e. the data at hand, the explicit analytical procedure , and the final numerical result may be identical. In other words, it is just the clear statistical definitions”; yet, on the other hand, he has to concede at once that “there is a long tradition of informal—but systematic and successful—causal inference in the medical sciences” , everybody—Fisher included—seems to be prepared to dismiss this realization: “It should in fairness be mentioned that, when randomization leads to a bad-looking experiment or sample, Fisher said that the experimenter should, with discretion and judgement, put the sample aside and draw another” .The latter concession isn’t just a minor inconvenience, but runs contrary to the very principle of the Frequentist viewpoint: First, an informal correction is wide open to subjective judgement. (Already) “bad-looking” to person A may be (still) “fine-looking” to person B. Second, what’s the randomization distribution actually being used when dismissing some samples? A vague selection procedure will inevitably lead to a badly defined distribution. Third, why reject certain samples at all? If the crucial feature of randomization is to provide a “valid” distribution , one should not give away this advantage unhesitatingly. At the very least, it is inconsistent to praise the argument of the known framework in theoretical work, and to turn a blind eye to it in practice.X, this distribution should be normal—at least approximately, if n is not too small. Therefore, in a statistical experiment, it seems to be justified to compare As a matter of fact, in applications, the exact permutation distribution created by some particular randomization process plays a rather subordinate role. Much more frequently, randomization is used as a rationale for common statistical procedures. Here is one of them: Randomization guarantees independence and if many small uncorrelated  factors contribute to the distribution of some observable variable  earlier  and workRegression adjustments are often made to experimental data. Since randomization does not justify the models, almost anything can happen … The simulations, like the analytic results, indicate a wide range of possible behavior. For instance, adjustment may help or hurt.How should experimental data be analyzed? If the known distribution were of paramount importance, there should be a unanimous vote, at least by Frequentist statisticians. However, only a minority, perfectly in line with the received position, advise leaving the data as it is. Freedman  argues tYet a majority have a different opinion e.g. , 3, 45)., 45.3, 4Apart from the rather explicit rhetoric of a “valid framework”, there is also always the implicit logic of the experiment. Thus, although the received theory emphasizes that “actual balance has nothing to do with validity of statistical inference; it is an issue of efficiency only” ; comparaT and C. At least, in almost every article a list of covariates—with their groupwise means and standard errors—can be found.Many, if not most, of those supporting randomization rush to mention that it promotes similar groups. Nowadays, only a small minority bases its inferences on the known permutation distribution created by the process of randomization; but an overwhelming majority checks for comparability. Reviewers of experimental studies routinely request that authors provide randomization checks, that is, statistical tests designed to substantiate the equivalence of A narrow, restricted framework is only able to support weak conclusions; there is no such thing as a “free lunch.” Therefore, upon reaching a strong conclusion, there must be implicit, hidden assumptions  Though, at times, we fail, e.g. “it does not seem possible to base a meaningful experiment on a small heterogenous group” , there c around” , p. 70  was the most influential statistician. However, while his early work on mathematical statistics is highly respected in all quarters, hardly anybody relies on his later ideas, in particular fiducial inference . RandomiSince the most important application of random assignment can be found in clinical trials, it is straightforward to ask how strong the evidence produced by a randomized controlled trial is. Vis-à-vis the rather anecdotal and qualitative research that preceded today’s RCTs, the latter surely constituted real progress. Strict design and standardized analysis has raised the bar and has fostered consensus among researchers. However, many classical experiments in the natural sciences are deterministic and have an even better reputation. If in doubt, physicists do not randomize, but replicate. Fisher , p. 58, http://validation.scienceexchange.com. One may also consult www.nature.com/nature/focus/reproducibility on this matter.)Alas, a large number of important biomedical findings (RCTs included) failed this examination and turned out to be non-replicable –57, so tApart from the control of imbalance in prognostic factors, randomized studies have several qualities that … follow from the fact that [they] belong to a larger class of high-quality studies, namely, prospective parallel comparisons with a written protocol specifying important aspects of patient enrollment, treatment, observation, analysis, and other procedures.The logic of Section 1 offers a straightforward explanation for this unfortunate state of affairs. Given  equal initial conditions, the same boundary conditions thereafter, and a well-defined experimental intervention, an effect once observed must re-occur. That’s how classical experiments work, which reliably and thus repeatedly hit their target. During the experiment, a controlled environment keeps disturbing factors at bay. Thus, if an effect cannot be replicated, the constructional flaw should be sought at the very beginning of the endeavour. At this point, it is conspicuous that today’s studies do not focus explicitly on the crucial idea of comparability. With other issues—possibly rather irrelevant or even misleading—being at least as important, initial imbalances are the rule and not the exception. At the very least, with randomization, the starting point of researcher 2, trying to repeat the result of researcher 1, will always differ from the latter’s point of origin. Therefore, if an effect cannot be replicated, this may well be due to the additional variability introduced by the “R” in RCT, yielding unequal initial conditions, and “drowning” the interesting phenomenon in a sea of random fluctuation. In a similar but more positive vein, Abel and Koch  underlinT and C), exerting a tremendous influence on the final result of an RCT is in line with this more recent portrait of chance.Chance has a Janus face. The idea that many (the more the better), small and rather uncorrelated random influences sum up to a “mild” distribution originated in the 19th century, culminating in the famous central limit theorem on which much of classical statistics is built. However, this was not the end of the story. Studying complex systems, physicists soon encountered “wild” distributions, in particular power laws Randomization has tremendous prestige in orthodox statistics, downgrading all designs without a random element to quasi-experiments. One even distinguishes between truly random allocation and “haphazard assignment, that is, a procedure that is not formally random but has no obvious bias” With the core technique (or rather dogma) of randomization, Fisher’s conception of experiments could even develop into a “cult of the single study” r  is less complex than a sequence like s =  in a mathematically strict way. random number generator”, i.e., a deterministic algorithm designed to produce chaotic output, or of a “truly random” mechanism. In a more positive vein, computer scientist J. Rissannen  showed hfound in , p. 48; s as a particular assignment of units to groups , the above fundamental distinction between “‘haphazard” and “random” assignment processes seems to be exaggerated, some might even question whether it is relevant at all. However, it is difficult to deny that the (non-)regularity of the concrete mapping matters. Just compare r to s: Since r invites a straightforward alternative explanation, most people would prefer s. In today’s terminology, Fisher could have been looking for maximally complex sequences, i.e., allocations without any regularity. In his time, a simple stochastic process typically yielding an “irregular” sequence was a straightforward and convenient solution to this problem.Interpreting Random assignment makes groups comparable.Yes, but only if n is large. Otherwise, randomization rather provokes imbalances (Section 3).A random process treats known and unknown factors alike, and thus controls unknown nuisance factors.Conversely, imbalances in observed variables hint at imbalances in unobserved variables. Moreover, a more detailed study of dependence structures reveals that consciously working in favour of similar groups typically pays off (Section 4).The act of randomization generates the sample space and hence provides the basis for valid conclusions.The formal Frequentist framework thus defined is narrow, yielding weak conclusions that have to be supplemented with a lot of informal reasoning (Section 5).Random allocation allows for causal inference since it keeps nuisance factors at bay.No; comparability and strict experimental control are crucial for internally valid, replicable studies (Section 6).In sum, Fisher’s idea of randomization is still alive. However, on the whole it looks more like a backward-looking tool than like the indispensable key to the future of statistics. Though there are many claims in its favour, they can all be seriously questioned:not “relieve the experimenter from the anxiety of considering and estimating the magnitude of the innumerable causes by which the data may be disturbed.” Quantitative arguments and formalized theories demonstrate that it is no philosopher’s stone, almost effortlessly lifting experimental procedures in the medical and social sciences to the level of classical experiments in the natural sciences. Rather, random assignment may lull researchers into a false sense of security.In a nutshell, contrary to what Fisher  thought,It is true that chance, in the guise of randomization, by and large supports comparability. However, since the former is blind with respect to the concrete factors and relevant interactions that may be present, it needs a large number of experimental units to do so. The intuition behind this result is easy to grasp: Without knowledge of the subject matter, randomization has to protect against every conceivable nuisance factor. Such unsystematic protection is provided by number and builds up slowly. Thus, a huge number of randomly allocated subjects is needed to shield against a moderate number of potential confounders. And, of course, no finite procedure such as the flip of a coin is able to control for an infinite number of nuisance variables.Therefore, it seems much more advisable to use background knowledge in order to minimize the difference between groups with respect to known factors or specific threats to experimental validity. As of today, minimization seems to operationalize this idea best. At the end of such a conscious construction process, randomization finds its proper place. Only if no reliable context information exists is unrestricted randomization the method of choice. It must be clear, however, that it is a weak guard against confounding, yet the only one available in such inconvenient situations.… it is the existence of sound background theory which is crucial for the success of science. It is the framework against which observations are made, it allows strict definition of the items involved, it is the source of information about possible relevant variables and allows for the identification of homogeneous reference classes that ensure regularity and, hence, reliable causal inference.Summing up, the above analysis strongly recommends traditional experimentation, thoroughly selecting, balancing and controlling factors and subjects with respect to known relevant variables, thereby using broader context information—i.e., substantial scientific knowledge. I agree with Penston , pp. 76–Cumulative science is the result of a successful series of such experiments, each of them focusing on the crucial ingredients, like precise research questions, convincing operationalizations, explicit control, quantitative measures of effect, and—last but not least—comparability.


The eosinophil was first named by the brilliant German scientist Paul Ehrlich in 1879, while he was experimenting with aniline dyes to stain blood cells and tissues. He also discovered neutrophils, basophils, and mast cells. The highly basic proteins in cytosolic granules of a small subpopulation of cells in human blood stained vivid pink with the acid dye eosin (from the Greek “eos” meaning dawn), hence “eosinophils.” He subsequently observed high numbers of these cells in the sputum of asthmatic patients and recognized the close relationship between eosinophilia and the severity of asthma. Pertinent to our story was his proposition that a “material which attracts eosinophils” exists. Further, he postulated that eosinophils and neutrophils possess different “chemotactic irritability” and that eosinophils only migrate to sites where a “specific stimulating substance” is present . We then began experiments with 111In-neutrophil trafficking in vivo, and the purification and identification of C5a brought us into contact with an expert protein sequencing group in London. In a paper published in 1986, we noted that there was a small amount of permeability-increasing activity, other than C5a, in 2 h zymosan-induced peritoneal exudates. Some time later, we assayed 6 h exudates in the skin in the presence of a C5a neutralizing antibody and identified two potent activities. Purification using HPLC, followed by microsequencing, revealed that these were the rabbit equivalents of IL-8 (CXCL8) and MGSA (CXCL1); results published in 1990 and 1991. Thus, at this stage, our journey had taken us from an interest in the barrier function of the venular endothelium, to the complement system and neutrophils, and then on to chemokines.This could have been the inspiration behind the Eotaxin project but, in truth, its origins were more prosaic. To provide a brief background, my Ph.D. project on mechanisms of inflammation involved the measurement of microvascular plasma protein leakage in rabbit and guinea pig skin using 111In-eosinophil accumulation in guinea pig skin in vivo. I later recruited David Griffiths-Johnson who had specialized in lung lavage of allergen-challenged sensitized guinea pigs. The plan to combine the two techniques as an in vivo generating and in vivo bioassay system to identify endogenous eosinophil chemoattractants was submitted to the asthma charity as a project grant, but sadly this was rejected with not unreasonable reservations about feasibility. Despite this, we continued using funds raised for another project. After several “false dawns,” the pursuit proved successful and in 1992 we were regularly detecting activity in lung lavage fluid, indicated by a strong 111In-eosinophil signal in bioassay skin samples. Unfortunately, at this point, we had lost our biochemist, Peter Jose, who had developed the methodology for the purification of rabbit IL-8 and MGSA. Peter had abandoned the hunt for the elusive eosinophil chemoattractant and moved out of science to a rural retreat in Marmande in France. I flew to France clutching the new data and met Peter who seemed more interested in the ripening of his strawberry crop, but was persuaded to return to London to take on the challenge. The lavage fluid was put through a series of HPLC purification stages and within a relatively short time Peter had purified the protein for microsequencing. Within 2 weeks, the sequencing group had an N-terminal sequence of a novel CC chemokine. Soon, they had sequenced peptide proteolytic fragments of the protein and had assembled the full 73-aa sequence. We called this protein “Eotaxin” (condensed from “eosinophil chemotaxin”). We submitted a manuscript to Nature and were pleased with the positive reports that came back from two of the referees, which betrayed a North American flavor (“flavor”). The third, more critical, referee appeared to be from the “United” Kingdom and stated that the molecule had not been cloned and that chemotaxis had not been demonstrated in vitro. These statements were true, but seemed to miss the point. There was considerable interest in academia and industry in the eosinophil as a therapeutic target in asthma. Activated eosinophils release their highly basic, tissue-damaging proteins, and a range of mediators that can exacerbate lung inflammation. Despite the interest, cloning had not revealed the Eotaxin sequence. We had tried eosinophil chemotaxis in vitro as an assay, but the cells were confused by a whole gamut of non-specific stimulants in lavage fluid. In contrast, the in vivo skin assay excelled in picking up the chemoattractant “needle” in a “haystack” of irrelevant molecules. After two more unsuccessful attempts at submission to Nature with more data, the paper was redrafted and appeared, considerably delayed, in the Journal of Experimental Medicine in March 1994 . To redress the balance, I introduced Lucia Faccioli, a visitor from Brazil, to eosinophil expert Redwan Moqbel in the Institute and we developed a method to measure in vitro from tissues of allergen-sensitized guinea pigs in the early 1900s) would have appreciated our approach. I took this as a compliment but, on reflection, this more resembled understandable sarcasm at our “retro” methodology. However, one advantage with our approach was that we could immediately set our molecule in a disease context and give it a rational name. With the encouragement of Craig Gerard, Tim invited me to join the scientific advisory board of LeukoSite Inc., the company that he had recently founded with Eugene Butcher. The Eotaxin patents were licensed to the Company and a successful relationship ensued. Based on the protein sequence  and locally produced Eotaxins are thought to mediate angiogenesis in this condition [see Ref.  and discovered a subpopulation of donors whose cells responded to CCR3 and CCR1 agonists. This led to the first publication on a CCR3 antagonist , one thaThus, from humble origins, the work on Eotaxin-1 has raised tantalizing opportunities for therapy ranging across several diseases. These possibilities have not yet translated into effective therapy, but we are not alone in this in the chemokine field .The author is a named “inventor” on a patent of the Eotaxin-1 molecule.


This study provides information about owners’ experiences with their dogs’ excitable behavior. We found that certain daily scenarios tended to prompt excitable behavior. The majority of owners in this self-selected sample were very frustrated with their excitable dog. Many dogs in the sample had other behavior problems.Past research has found that excitable dog behavior is prevalent among sheltered and owned dogs and many times is a reason for canine relinquishment. In spite of its prevalence in the canine population, excitable behavior is relatively unstudied in the scientific literature. The intent of this research was to understand the experience of owners of excitable dogs through the analysis of self-administered online questionnaires completed by owners as part of another study. We found that certain daily scenarios tended to prompt excitable behavior, with excitability most common when the owner or other people came to the dog’s home. All owners experienced some level of frustration with their dog’s excitable behavior, with the majority being very frustrated. Many dogs in the sample had other behavior problems, with disobedient, destructive, chasing and barking behaviors being the most commonly reported. Other characteristics of excitable dogs also are discussed. Although the ability to generalize from these results is likely limited, due to targeted recruitment and selection of owners of more excitable dogs, this research provides valuable insights into the owner’s experience of excitable behavior. We hope this study prompts more research into canine excitable behavior which would expand our understanding of this behavior and help behaviorists, veterinarians, and shelters develop tools for managing it, as well as provide better education to owners of excitable dogs. Excitable dog behavior such as jumping on people is a very common behavior, especially for young dogs ,2,3. A ret al.  is affectionately known as a “body slammer”. He is high-energy, rough, and fast”. Jumping up, mouthing/nipping and different vocalizations during play were also reported. Only a few dogs were reported to be scared or aggressive, and, consequently, could not play with other dogs. About 10% (17) of owners reported that their dogs loved to play, but not with every dog. Familiarity with the other dog and its behavior as well as its size were factors. According to one owner, “[It] depends on the dog, with some he will rough house… with others he will not play at all. He seems to be nervous around larger dogs”.H(2) = 20.14, p < 0.001). Owners of less excitable dogs felt less frustrated . Post-hoc tests of the pairwise differences amongst the groups, using the Bonferroni approach to control for Type I error, revealed all three groups  were statistically different from each other.All owners rated their dogs as a 3 or higher on the question about the severity of their dog’s excitability : 14 (8.0%) rated their dog a 3, 92 (52.6%) rated their dog a 4, and 69 (39.4%) rated their dog a 5. In addition, the majority were frustrated with their dog’s excitable behavior : 19 (10.9%) rated their frustration a 2, 56 (32.0%) rated a 3, 61 (34.9%) rated a 4, and 39 (22.3%) rated a 5. There was a statistically significant difference between the excitability ratings and owners’ ratings of frustration , and also reported their dogs were less excitable .Almost all owners  found the excitable behavior difficult to manage. Owners who said that the behavior was not difficult to manage were less frustrated with their dogs (etc.).” Barking behavior was another theme that emerged, with the dogs barking at people , other dogs , or the front door or window. The nature of the barking behavior varied; according to owners, some dogs barked due to overexcitement, and in some cases barking turned into more severe behavior. “When she gets overstimulated, she barks at me”, one owner reported, “and grabs and shakes my shoelace or pants leg or leg (sometimes breaking the skin). Overstimulation can come from a sneeze from me on a hike, or whenever we turn back on a walk/hike, if I stumble or fall, or reasons I can’t explain…She can be so frustrating”. Some barking behavior had a protective nature. “When he sees someone outside our house, he charges at the window and barks extremely loud,” one owner noted. Some barking behavior was exhibited primarily outside when the dog was walked on a leash. “When walking him, he barks at strangers uncontrollably and will not stop until they pass by…even if he knows the person, he acts like he is going to attack them. He will be aggressive if someone jumps nearby or [if] kids are playing roughly he will become aggressive.” Although it was very hard to interpret the owners’ responses if the dog was described as aggressive or as overstimulated and excessively excitable without any specific behaviors included in the description, some owners  described their dogs as being sometimes aggressive to people or mentioned the dog’s biting history: “He can be aggressive if he feels uncomfortable or overwhelmed”, “His major issue is his reaction when he sees another animal that he cannot get …He turns his frustrations on anyone and anything that is near him, biting and barking uncontrollably”. Aggression directed toward other dogs  was slightly more common than aggression toward people. Anxiety, digging, and escaping behaviors were rarely mentioned.Eleven people (6%) skipped the open-ended question about other behavior problems entirely. For the rest, although they were asked about other behavior problems, many of them felt the need to reiterate and provide a further explanation of their dog’s excitable behavior. About 22.9% (40/175) of owners were concerned about their dog’s excitable behavior when meeting people. Concerns varied from the dog’s jumping or putting its mouth around an arm to nipping and grabbing clothes. The majority  of these respondents described their dog as jumping excessively on visitors or new people. According to one owner, “He lunges, licks, [and] gives them no personal space.” Another owner described even more severe behavior, “He barks and can jump up in the air to reach people, children’s faces... He bites their clothes or hands or arms.” Disobedient and destructive behaviors were also commonly reported by owners, ranging from pulling on the leash  to climbing furniture  and destroying household items . Some owners specified that their dog does not listen or respond to commands , with examples such as, “My dog jumps on [the] kitchen counter with all four feet to steal cat food… almost never listens, destroys toys…jumps over [the] gate, steals from [the] trash”. Another significant theme that emerged from owner responses was chase behavior . The dogs were chasing children, small animals , and moving objects . One owner reported, “If off leash he has a habit of suddenly deciding to chase cars (he used to chase anything that moved faster than a walk when we first got him—joggers, bikes, In this study, the survey responses of owners of excitable dogs were analyzed in order to explore and understand their experiences with their dogs. The findings demonstrate that excitable behavior is indeed complex, with a range of severity and frequencies, prompted by many daily scenarios. However, excitability was most commonly reported, with greater frequency and more severity, when the owner or other people came to the dog’s home or played with the dog. Playtime in particular triggered more severe behavior which included hard mouthing of body parts. This may be due to the stimulation that usually comes with “play” such as loud voices, fast movements, and toys. Surprisingly, food preparation by the owner did not prompt excitable behaviors, with less than a third of owners reporting jumping some of the time or more frequently. This may be due to effective owner modification or management of the behavior, where owners could have trained their dogs to sit and wait for the food. Owners could have also prepared the food in a different room without the dog seeing it.etc. could provide more information about the etiology of excitable behavior.All owners experienced some level of frustration with their dog’s excitable behavior, with the majority being very or extremely frustrated. In addition, the more excitable the dog was, the more frustrated the owner was, although it is possible more frustrated owners perceived their dog’s behavior as more excitable. Not surprisingly, attention-seeking activity or general excitability of the dog could have become an irritant to the owner . AlthougIn general, disobedient, destructive, chasing and barking behavior problems were the most commonly reported behaviors by owners of excitable dogs when asked about other behavior problems. Since these behaviors were frequently reported by our sample of owners, it would be important to include them in future research about excitability. Pulling on the leash also was frequently reported in our study. In previous research, this behavior was grouped together with jumping up in a data reduction technique , again sThe majority of dogs in the sample were reported to feel comfortable in a new environment and around new people. However, the fact that 41% of dogs in this sample had previously stayed in the boarding kennel, the site of the broader study, could have made them more comfortable than the average dog in new environments. Although 43% of owners reported their dog having a certain level of aggression toward other dogs, only a few of them described their dog as aggressive or fearful when their dog was playing with conspecifics. Previous research has reported that a dog’s reaction to other canines may vary based on the other canine’s behavior, sex and appearance . We alsoThere were weak but significant relationships between some demographics of the dog and excitability. Although the negative relationship between age of the dog and excitability was expected, and the negative relationship between weight and excitability might make sense anecdotally, the weak relationship suggests these findings are unstable, at least in this study. Future research should consider these characteristics closely to determine if they are related to the development or expression of excitability, to what degree, and how they might moderate an owner’s perception of the behavior.In conclusion, the large number of people who responded to this survey in a very short time with minimal advertising suggests that there is a need to bring more attention to excitable dog behavior. This study provides—for the first time—information about owners’ experiences with dogs’ excitable behavior, based on owners’ perception and understanding of it. Characteristics of excitable behavior, as well as what may routinely prompt it, were also presented. Future research should explore what owner-related factors contribute to excitable behavior. Since this study’s results were subjected to a self-selection bias, a nationally representative sample of owners could extend the research about excitable dogs. Moreover, such a sample would provide comparisons between excitable and non-excitable dogs, as defined by their owners. The last will help to clarify the definition of excitable behavior. In addition, in-depth qualitative interviews would provide a deeper understanding of not only excitable dogs’ behavior but also insight into owners’ experiences with and feelings about it. In-depth research into excitable behavior etiology as well as ethology would extend our understanding of this behavior. The research into excitable behavior could help behaviorists, veterinarians, and shelters to develop better tools for managing it, as well as provide better education to owners of excitable dogs, resulting in satisfying bonds between owners and dogs and successful long-term retention in the home.


Search of metagenomics sequence databases for homologs of virophage capsid proteins resulted in the discovery of a new family of virophages in the sheep rumen metagenome. The genomes of the rumen virophages (RVP) encode a typical virophage major capsid protein, ATPase and protease combined with a Polinton-type, protein primed family B DNA polymerase. The RVP genomes appear to be linear molecules, with terminal inverted repeats. Thus, the RVP seem to represent virophage-Polinton hybrids that are likely capable of formation of infectious virions. Virion proteins of mimiviruses were detected in the same metagenomes as the RVP suggesting that the virophages of the new family parasitize on giant viruses that infect protist inhabitants of the rumen.This article was reviewed by Mart Krupovic and Kenneth Stedman; for complete reviews, see the The online version of this article (doi:10.1186/s13062-015-0054-9) contains supplementary material, which is available to authorized users. With the rapid increase of the quantity and quality of available metagenomics sequences, metagenomes have become a rich source for the discovery of novel viruses -3. A proCafeteria roenbergensis [We were interested in mining metagenomes to explore the diversity of virophages, an unusual group of viruses that parasitize on giant viruses of the family Mimiviridae. The known virophages possess double-stranded, typically circular DNA genomes of about 20 kilobase pairs (kbp) and icosahedral virions comprised of highly derived double jelly-roll capsid proteins ,10. So fergensis . Sputnikergensis  that subergensis ,18. So fergensis .The genomes of Mavirus  and the We sought to harness the potential of metagenomics for the discovery of substantially novel virophages, distinct from the Sputnik, Mavirus and OLV families. All sequenced virophage genomes encompass a conserved gene module that encodes proteins involved in virion morphognesis, namely major and minor capsid proteins, packaging ATPase and capsid maturation protease, but otherwise, possess highly variably gene repertoires . Among tWe used four MCP sequences from diverse virophages to search the metagenomic nucleotide databases that are available via GenBank and detected multiple hits . The respective metagenomic sequences were translated and used as queries for BLASTP to search the non-redundant protein sequence database, in order to further ascertain their provenance. As a result of this search, 35 Open Reading Frames (ORFs) and ORF fragments from 6 metagenomics databases, namely, Activated sludge metagenome (AS), Bioreactor metagenome (BR), Freshwater sediment metagenome (FWS), Gut metagenome (Gut), Marine metagenome (Mar), and Wastewater metagenome (WW), were identified as likely virophage MCPs  genomes encoded proteins without significant similarities in the current databases, with the sole exception of a putative polynucleotide kinase encoded in one of the contigs  allowed us to assemble 3 long virophage genomes ; typically, the two capsid proteins are encoded in adjacent genes ,22. A foThe presence of the idiosyncratic structural variant of the MCP that is unique to virophages implies that the RVPs are parasites of giant viruses in the family Mimiviridae. To ascertain the presence of mimivirus sequences in the analyzed metagenomes, we searched the metagenomic libraries, in which the virophage MCPs were identified, using as queries representative sequences of mimivirus MCPs. Sequences of apparent mimivirus origin were identified in all metagenomes except for WW but were particularly numerous in the gut metagenome , a distant relative of the mimiviruses [The genomes of the RVPs appear to have evolved via recombination between a virophage and a Polinton. A similar evolutionary scenario seems to have produced the Mavirus which inherited from the Polinton ancestor not only the PolB but also the integrase . Howeveriviruses . HoweverThe identification of a new family of putative virophages with unusual features of genomic composition and architecture emphasizes the potential of metagenomes for discovery of novel classes of mobile elements. The RVPs appear to be virophage-Polinton chimeras and in this respect resemble the chimeric ssDNA viruses that have been recently discovered, also by metagenome mining ,5,7,26. Four virophage major capsid proteins, Mavirus GI:326439166; Sputnik virophage GI:193245560, Organic Lake virophage GI:322510455, and Yellowstone Lake virophage 7 GI:701905716, were used as queries for translating blast searches (Tblastn ) againstSimilarly, four mimiviridae major capsid proteins, Acanthamoeba polyphaga mimivirus GI:311977828, Cafeteria roenbergensis virus BV-PW1 GI:310831332, Acanthamoeba polyphaga mimivirus GI:311977809, and Organic Lake phycodnavirus 1 GI:322510624, were used as queries for Tblastn searches against the AS, BR, FWS, Gut, and WW metagenomes.Protein sequences were aligned using MUSCLE , and gapInverted repeats were identified using Censor software .Mart Krupovic, Institut PasteurIn this Discovery Note, Yutin et al. describe a new group of putative virophages, which they discovered in the sheep rumen metagenome. These new elements differ considerably from the previously described virophages and appear to contain a chimeric genome. The virion morphogenesis module is similar to that shared by all virophages, whereas the family B DNA polymerase is more closely related to the corresponding proteins of large, virus-like DNA transposons of the Polinton/Maverick superfamily. The authors succeeded to assemble several nearly complete genomes of these novel virophages. The virophage-containing metagenome was positive for the presence of mimiviruses, as judged by the occurrence of reads coding for the mimivirus major capsid protein. This result is consistent with the conclusion that the newly identified virophages parasitize on the giant viruses. The manuscript is very clearly and logically written.Using the major capsid protein sequences presented in Additional file The morphogenetic module of virophages and polintons includes a minor capsid protein. Do the rumen virophages encode a homolog of this protein? This has to be stated in the text.This is an important point that is explicitly addressed in the revised manuscript. It seems that the RVP genuinely lack the minor capsid protein.Authors’ response: Minor comments:The second half of the third sentence might be an overstatement.Yes, the second reviewer also made a similar comment. We modified the sentence to indicate that the chimeric viruses “might” be major components of viromes.Authors’ response: “of two distinct family” change to “families”.correctedAuthors’ response: “adopts a derived jelly-roll fold” change to ?adopts a derived double jelly-roll fold”.Authors’ response: modified as suggested.In the last paragraph of the Findings (before conclusions), it might be worth mentioning that although Mavirus genome has been reported as a circular molecule, it contains abutted 50 bp inverted repeats (separated by 15 bp) (ref 12 in the current reference list), which could correspond to terminal inverted repeats found in polintons, PGV and RVPs.Authors’ response: Considering the Biology Direct format, we believe that it is sufficient to include this detail here. We appreciate the reviewer pointing it out.Labels of some of the ORFs in Additional file Authors’ response: Corrected.Kenneth Stedman, Portland State UniversityYutin et al., in their “Discovery Note” have performed highly sensitive searches of available metagenomic sequence datasets for sequences similar to major capsid protein genes (MCP) of known virophages. Then they used these sequences as anchors to acquire associated sequence data from the metagenomic datasets. Thereby the authors discover a new group of sequences, whose putative MCPs are similar to virophage MCPs but consist of a phylogenetically well-supported separate clade. Interestingly, some of these MCPs are associated with putative protein-primed DNA polymerase genes that are similar to some Polinton DNA polymerase genes. The authors propose a new family of virophages based on this analysis.It is unfortunate that this manuscript is constrained by the discovery note format, as I find the Additional figures to be integral to interpretation of the results presented in the manuscript. Specifically, I find the phylogenetic trees for the putative viral ATPase and Protease genes to be at least as convincing as the phylogenetic tree presented in Figure We appreciate these thoughts but maintain that the Discovery Note format is most appropriate for these findings. The principal reason is that we do not have confirmed, complete genome sequences of the RVP and did not have an opportunity to perform any confirmatory sequencing as pointed out by the reviewer below. Therefore the short communication format appears to be the correct choice. We do agree that the trees for ATPases and proteases are as convincing as the pPolB tree and might be even easier to interpret. We have chosen the polymerase for the main body of the article because overall, this gene is more common among diverse genetic elements than either of the other two. To the best of our understanding, the additional files are integral parts of the published paper and they are accessible from the article by one click. Thus, we hope and trust that there is no problem for readers in assessing the entirety of evidence presented here.Authors’ response: Figure We are not quite sure about the source of the confusion. Potentially, the problem might lie in the fact that different groups of eukaryotic viruses and other selfish elements emerge from within the polinton diversity. i.e. apparently evolved from different groups of polintons. We emphasize this trend in two places in the revised manuscript. Beyond these clarifications that, as we hope, suffice to avoid any confusion, there does not seem to be room in this brief manuscript to introduce the polintons in greater detail.Authors’ response: I, and I think most Biology Direct readers, would like more detail on some of the methods, and some clarification of some of the statements in the manuscript. These are detailed below:First, even though our lab was the first to recognize them, I am not sure if the chimeric ssDNA and + strand RNA viruses are “major components of viromes”. I would like to think that they are. However, since most of the viromes cited, and certainly ours, were amplified using Phi29DNA polymerase, which preferentially amplifies small ssDNA virus genomes, one cannot be sure of quantification. Perhaps this is discussed in Krupovic et al., Genome Biology and Evolution, 2015, but I was unable to access this manuscript.this is by no account a key point in the article. We might have over-reached in the original version. The statement was softened in the revision following this comment and a similar comment of reviewer 1.Authors’ response: In the second sentence of the second paragraph of “Findings”, I suggest adding “known” after “The” and before “virophages” and changing “kilobases” to “kilobasepairs”?.Authors’ response: modified as suggested.Third paragraph of Findings: Consider including a reference to Maverick transposons at the first mention of Polintons to clarify this for researchers who have not been able to keep up with the recent literature by the authors (and others) on Polintons.doneAuthors’ response: Fifth paragraph of “Findings”: The definition of “hits” needs to be made here or the exact parameters used for the searches and criteria for selection given. I did a tBLASTn search with the first MCP sequence listed (Mavirus MCP) using the metagenome taxonomic id and found “hits” with high e-values and low scores. I would also list the ids of the metagenomes found here, rather than abbreviations. I disagree that this analysis “confirmed” as likely, I would say “identified”.We indicate in the revision that at the first stage, we used the BLAST default, i.e. E-value < 10 . “Confirmed” changed to “identified” as suggested. However, we think that here taxonomic id would unnecessarily clutter the text, abbreviations should suffice. The e-values, scores and best hit IDs, as well as the IDs of metagenomics sequences, are in the Additional file1.Authors’ response: Sixth paragraph of “Findings”: The affinity of the Sputnik-like virophage MCPs to the sheep rumen putative virophage MCPs seems very tenuous from Figure the interpretation of ELW is basically correct. However, the trees were redone with a different method, and based on the results included in the revised version, we do not claim an affinity with the Sputnik family anymore. We analyzed all sheep rumen metagenome contigs deposited in GenBank at the time of this manuscript submission , and the contigs detailed in Additional file3are the only one encoding virophage-related proteins. Thus, RVP are not particularly common in the sheep rumen.Authors’ response: Seventh paragraph: The assemblies of the metagenomic contigs shown in Additional file The assemblies reported here were obtained using BLASTN searches as implemented in Censor. A detailed figure legend is included in the revised Additional file3. each contig encoding an MCP homolog was used as a query in a Censor search against the full set of all sheep rumen metagenome contigs . Using Censor, we have not found significant overlaps of the termini of the assembled virophages with any other contigs.Authors’ response: Eighth paragraph: I disagree that the RVP group of putative virophages is “clearly related” to the Sputnik-like virophages . The RVP are a distinct, new family of virophages. The text was modified accordingly.Authors’ response: Ninth paragraph: The possible relationship between the RVPs and mimivirus-like sequences in the metavirome is clearly speculative, but some mention should be made here whether these viruses are likely to be endogenous or of something consumed by the sheep. The statement “particularly numerous” is imprecise, some quantification, at least relative to the other metagenomes, should be given here.Given that virophages so far have been shown to parasitize only giant viruses of the family Mimiviridae, we consider the relationship between the RVP and the mimiviruses that appear to be present in the same habitat, judged from metagenome analysis, to be highly plausible although, certainly, still a conjecture. The possibility that the mimiviruses come from food and do not reproduce in the rumen is difficult to fathom given the diet of sheep that is hardly rich in amoeba. “Particularly numerous” relates to the ratio of extended-Mimiviridae-like MCPs in rumen metagenome compared to other metagenomes analyzed for this matter, as shown in Additional file1. We do not think the numbers need to be included in the article. A particularly interested reader can calculate using Additional file1.Authors’ response: Tenth paragraph: The analysis of TIRs should also include analysis of internal IRs, if any, in the sequences. If original metagenomic sequence reads are available, this could address whether the identified IRs are actually terminal. I would describe the PGV putative virophage in more detail, does it just have TIRs but none of the other genes? At the end of the paragraph, I believe the authors mean “in trans” instead of “in-trance”.There were no internal IRs. A clarification on PGV virophage-encoded proteins added. The typo corrected.Authors’ response: Conclusions: I completely agree with the incredible potential of metagenomes as sources of new virus genomes. It should be mentioned that, in the case of the chimeric ssDNA viruses, many of these have been reconfirmed by amplification and resequencing from original samples, which I do not believe has been done for these RVPs.There was indeed no amplification and resequencing involved here. However, we do not believe this disclaimer belongs in the Conclusions. Suffice it to be here for the interested reader to see.Authors’ response: Methods: For the nr database searches, were all of the putative MCP hits searched individually or as a consensus sequence or HMM? Please specify. How were the branch support values calculated?Individual sequences were used as queries for database searches. Neither Tblastn nor Blastp work with profiles, so this is clear as written. The sentence regarding branch support was changed.Authors’ response: “Author contributions” and “Acknowledgements” appear to be duplicated in the manuscript.Corrected.Authors’ response: Figure legends: I suggest removing “Evolutionary provenance of the rumen virophages” from both figure titles.done, with an additional modification.Authors’ response: I also suggest splitting the legend instead of putting all in Figure doneAuthors’ response: A number of abbreviations are missing in this legend, such as ALM, YSLV, ATP, PRO, MCP, and pPOLB : POLB, ATPase, cysteine protease, MCP, and one unclassified protein (“24”), other 15 unclassified proteins are not shown (they are not present in other virophages).Authors’ response:


N = 34). This crosslinguistic transfer effect is well-documented in the scholarly literature for first language (L1) and second language (L2) learners  lower level of linguistic proficiency in the first language, as affected by acquiring a second, while children in the “additive” bilingual programs had the benefit of continued support of their first language. As Cummins .Cummins  develope Cummins  put it,In later work, Cummins  extendedinteraction between socio-cultural, linguistic and school program factors,” in which “the level of competence bilingual children achieve in their two languages acts as an intervening variable in mediating the effects of their bilingual learning experiences”  in the interpretation of the Threshold Hypothesis. Cummins seems to use the term “language proficiency” to refer to both competence and performance, including school literacy. MacSwan We suggest, then, that “transfer” of literacy across languages occurs because in the bilingual brain, both languages have access to the same cognitive resources. As Genesee et al.  observe It is apparent, then, that one does not see a relationship between “first language ability,” however that is to be conceived, and second language literacy, but between literacy in the first language and literacy in the second language; in other words, literacy is relatively independent of the particular language for which it was initially acquired. In this regard, the usual meaning of transfer, which implies that a process “moves” knowledge from one language to another, should be seen as strictly a metaphor: Rather than move, both languages have access to the same store of knowledge, available to learners regardless of how the knowledge was acquired in the first place, as Riches and Genesee  also sugThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Psychological Science to reinforce the journal's 2014 publication guidelines. It exhorts substituting confidence intervals (CIs) for Null Hypothesis Significance Testing (NHST) as a way of increasing the scientific value of psychological research. Cumming's article is somehow biased, hence the aims of my commentary: to balance out the presentation of statistical tests and to fend CIs against misinterpretations. Researchers with an interest in the correct philosophical application of tests and CIs are my target audience.Cumming's  article NHST is a philosophical mismatch of three incompatible theories: Fisher's, Neyman-Pearson's, and Bayes's , critical test values, and power (1–β)—p-values are not relevant here but can be used as proxies for deciding between hypotheses  is not suitable for representing Fisher's ad hoc approach . It is, however, adequate for representing Neyman-Pearson's repeated sampling approach, a simple count of significant tests irrespective of their p-value. As it turns out, Cumming's figure is a textbook example of what to expect given power , which is partly correct. CIs were developed by Neyman  versus the power results presented in Table The common philosophy underlying CIs and tests implies that they share similar fallacies. Cumming touches on some but does not pre-emptily resolve them for CIs.p reveals truth… ” (p. 12). It is not clear what truth Cumming refers to, most probably about two known fallacies: that p is the probability of the main hypothesis being true and, consequently, that 1–p is the probability of the alternative hypothesis being true  have little to do with replication in the usual scientific sense” (Kline, Another fallacy touched upon is that ” Kline, , p. 66. ” Kline, , althougad hoc probability of personal confidence (Hoekstra et al., Finally, there is the ever present risk that CIs will be used as mindlessly as tests. For one, CIs share the same philosophical background than Neyman-Pearson's tests, yet many researchers take them to mean an Both CIs and tests are useful tools (Gigerenzer, The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Lead the subject from the dark room to the market place and then find out what it is he sees moving and under what conditions, and Korte's Laws, though still valid, describe the situation about as well as the Laws of Color Mixture describe one's feelings before an El Greco canvas.”Bruner and Goodman , p. 33Macrocognition research is concerned with cognitive processing in complex environments, goal-oriented action, goal combination and competition, cognitive-affective and cognitive-social interactions, distributed processing, and situatedness. These interests are critical to the theoretical modeling of cognitive systems for at least two reasons: (1) complexity is pervasive , and (2) efforts are needed within (and across) all scientific fields to give meaning to, and a more global picture of, usually separate(d) knowledge fields.epistemologically, “macrocognition” should not be regarded as different from other forms of cognition, including what has been called “microcognition”  can change microcognition  even in laboratory settings , as opposed to more regional mutual influences . In this perspective “macrocognition” is often seen as being more “ecologically valid,” or as enhancing “external validity” because it focuses on wide-range interactions that can be encountered in daily situations:Macrocognition is a term coined by Pietro Cacciabue and Erik Hollnagel to indicate a level of description of cognitive functions that are performed in natural  decision-making settings […] the methodology for macrocognition focuses on the world outside the lab. This includes contexts designated by such terms as the ‘field setting’, the ‘natural laboratory’, and the ‘real world.”’“, but we anticipate limitations to the second view, which may imply a new reductionist functionalism—a large-scale equivalent to functionalist views over microcognition. Indeed, social complexity, is grounded in self-reported measures and individual interpretation of external complexity. In order to produce self-reports, internal construction of what is reported is a prerequisite to data communication and processing; this internal construction involves microscale activity .The term “macrocognition” usefully highlights the need for a larger scope of analysis than the one characterizing most laboratory-based experiments. However, what is usually thought of as an “external” or “environmental” factor actually combines with the organism state so that one cannot exclude any term of the interaction at any single moment. The activity of any part of an organism depends on the activity of the other parts to which it is linked. For instance, even when social-environmental complexity related to the task at hand is high , factors affecting low-level biological parameters  prior biological or psychological integration of the values associated with the factors of influence and (b) competition between and/or combination with the current goals and needs of the organism. Failing to recognize the complex nature of the phenomena constituting a human being can give rise to reductionism, be at the microscale or at the macroscale level. From this standpoint, suprapersonal , personal, and subpersonal , levels of analysis should meet. The terms “suprapersonal” and “subpersonal” refer to different scale levels in the analysis of cognition but do not imply an opposition between complexity and simplicity. Suprapersonal factors  are currently more easily detectable from a macroscale level of analysis whereas “subpersonal” factors  are currently more easily observable from a microscale level of analysis. However, considering one as being complex and the other one as being elementary transaction between embodied personal history , goals, needs or orientations and external stimulation. Put differently, macrocognition cannot be correctly thought of without describing the interactions between the current biological state and motivation of the organism on the one hand and macroscale stimulation on the other hand.Enactive systems produce information and knowledge by acting in their environment. In MEM Laurent, , each cedistribution has no pre-set scale of analysis. Rather, distribution should be considered in every network that allows for information exchange and influences need/goal/aim satisfaction or frustration, be at cellular, cognitive, or social-affective levels. By relating micro and macroscale information integration to internal goals and needs, this multiscale approach provides us with tools to reunite macro and microscopic processes and levels of analysis.Distributed cognition is pervasive, not only at the subpersonal level, but also at the suprapersonal level . There should be no epistemological rupture in the conception of distributed cognition, at physical, biological, and psychological levels. Huebner  reviewedWhat is a thing at one level may be relations among (different) things at another.”“Kelso, , p. 97Though we subscribe to the macrocognition perspective for its emphasis on complexity, we warn the reader against the risks associated with a fixed-scale approach to cognition. Because macrocognition researchers stress the role of complexity, they should develop scale flexibility in their analyses. Even what is referred to as “macrocognition” by some researchers working on emotional context of behavior is identified as microscopic by others working on social networks. This does not change anything to the fact that, in order to analyze complex behaviors, we need to contextualize them. As a function of the scale of analysis, what can be considered a “context” varies.Arguably what should be regarded as “ecologically valid” is the capture of multiscale interactions in experimental—or, more largely, empirical—settings that are found in everyday situations . On those bases, and following what we discussed earlier, neglecting microscopic factors may be as harmful as neglecting macroscopic factors. In any instance of fixed-scale analysis, cognition is most probably regarded as a set of “functions” that process information under the influence of a limited number of “causes.”We invite the reader to pay attention to a blind spot that we have identified in the literature on macrocognition. The “macrocognition research blind spot” consists in associating “emergence,” “dynamics” and “complexity” with macrocognition as opposed to “invariant processes” or “building blocks” of cognition, which would be identified by microcognition research  found in the Macrocognition literature on what “reality” is:Microcognition relinquishes the coupling between the phenomenon and the real context to the advantage of the coupling with the underlying theory or model.”“ the biomechanical constraints, goals, prescriptions, machines, pervasive information systems, and social context surrounding task realization and (ii) the parameters to be coordinated, which participate in emerging cognition and behaviors.We rather call for a true If macrocognition is to become a reference framework for the cognitive science of embedded agents, then the contexts under scrutiny should be flexibly defined, and their role theoretically reconstructed and empirically tested.each higher level of description must add to our knowledge about lower levels, rather than replace it” (p. 26). We note that this addition of knowledge should not be merely scale-specific. Rather, it should involve working on the interactions between different scales and reporting what identifies/differentiates distributed cognition at different scales. This is a basic condition to approach behavioral complexity and to develop more unitary frameworks in psychology and life sciences.We hope that researchers interested in complexity will not add a new scale to functionalism. In other words, macrocognition should not exclude microcognition. As put by Minsky , “each hEL wrote the initial draft of the manuscript. EL and RB contributed to review several versions of the manuscript and have approved the final manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


I am thankful to Quillien  for his I put forward that the sampling units for macro-level cross-cultural correlations are finite. In contrast, Quillien argues that this does not have to be the case. I believe for the examples I cited Pollet, : Table 1a priori, otherwise it seems reasonable that the unit of analysis is indeed a U.S. state score. Let us tentatively define this alternative unit of analysis as “a social unit in which humans live(d) relevant to an evolutionary process.” Why would a U.S. state then be representative of the pool of such social units in which humans lived? Perhaps these data can indeed tell us something about U.S. states, but it is unclear whether any documented statistical relationship would hold for other units fitting the broader definition. It is unclear whether any statistical inference can be done beyond U.S. states, as that is all we have. There is no logical reason to assume that any statistical relationship found for U.S. states should hold, for other “human social units,” such as for example: world regions, Canadian provinces, Polynesian chiefdoms, 19th century German states, hunter gatherer populations,…. Let alone that these different “human social units” can be meaningfully lumped together and assumed to be governed by the same evolutionary process, as Quillien seems to imply. In addition, suppose that we do follow Quillien's logic and pretend the pool is larger, and even infinite, then a different problem still arises: we have clearly drawn a biased sample , as several authors including Quillien seem to suggest, then the ecological fallacy looms: inferences from one level of statistical analysis need not correspond to a different level of analysis (see Robinson, Finally, if we take these state level data to be representative of processes at an only unit being sampled. One might want to strengthen the statistical and logical inference based on those data but this is likely invalid: either due to sampling bias and/or the ecological fallacy. I therefore maintain that the p-values commonly used for statistical inference are inappropriate for macro-level cross-cultural correlations when the sample matches the population closely.In summary, in my view, the statistical inferences we can make based on units such as U.S. state scores can be about nothing else but U.S. states, as this is the The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.