How accurate is the Pearson r-from-Z approximation? A Monte Carlo simulation study.
The Pearson r-from-Z approximation estimates the sample correlation (as an effect size measure) from the ratio of two quantities: the standard normal deviate equivalent (Z-score) corresponding to a one-tailed p-value divided by the square root of the total (pooled) sample size. The formula has utility in meta-analytic work when reports of research contain minimal statistical information. Although simple to implement, the accuracy of the Pearson r-from-Z approximation has not been empirically evaluated. To address this omission, we performed a series of Monte Carlo simulations. Results indicated that in some cases the formula did accurately estimate the sample correlation. However, when sample size was very small (N = 10) and effect sizes were small to small-moderate (ds of 0.1 and 0.3), the Pearson r-from-Z approximation was very inaccurate. Detailed figures that provide guidance as to when the Pearson r-from-Z formula will likely yield valid inferences are presented.
['Hittner|James B|JB|', 'May|Kim|K|']
D003627:Data Interpretation, Statistical D006801:Humans D015201:Meta-Analysis as Topic D009010:Monte Carlo Method D011589:Psychology, Experimental D018401:Sample Size D016008:Statistical Distributions D013223:Statistics as Topic
Pearson r-from-Z Monte Carlo simulation correlation effect size meta-analysis