Regression-Based Norms for a Bi-factor Model for Scoring the Brief Test of Adult Cognition by Telephone (BTACT).
The current study developed regression-based normative adjustments for a bi-factor model of the The Brief Test of Adult Cognition by Telephone (BTACT). Archival data from the Midlife Development in the United States-II Cognitive Project were used to develop eight separate linear regression models that predicted bi-factor BTACT scores, accounting for age, education, gender, and occupation-alone and in various combinations. All regression models provided statistically significant fit to the data. A three-predictor regression model fit best and accounted for 32.8% of the variance in the global bi-factor BTACT score. The fit of the regression models was not improved by gender. Eight different regression models are presented to allow the user flexibility in applying demographic corrections to the bi-factor BTACT scores. Occupation corrections, while not widely used, may provide useful demographic adjustments for adult populations or for those individuals who have attained an occupational status not commensurate with expected educational attainment.
['Gurnani|Ashita S|AS|', 'John|Samantha E|SE|', 'Gavett|Brandon E|BE|']
D000328:Adult D000368:Aged D000369:Aged, 80 and over D003071:Cognition D003072:Cognition Disorders D005260:Female D006801:Humans D008297:Male D008875:Middle Aged D008960:Models, Psychological D009483:Neuropsychological Tests D013689:Telephone D014706:Verbal Learning
Occupational status Cognitive assessment Neuropsychology Statistical norms Statistical regression Test norms