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.
Department of Psychology, University of Colorado Colorado Springs, Colorado Springs, CO, USA.
Ashita S
AS
Gurnani
Department of Psychology, University of Colorado Colorado Springs, Colorado Springs, CO, USA.
Samantha E
SE
John
Department of Psychology, University of Colorado Colorado Springs, Colorado Springs, CO, USA bgavett@uccs.edu.
Brandon E
BE
Gavett
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003071:Cognition / Q000502:physiology*; D003072:Cognition Disorders / Q000175:diagnosis* / Q000523:psychology; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008960:Models, Psychological; D009483:Neuropsychological Tests; D013689:Telephone; D014706:Verbal Learning / Q000502:physiology*
Cognitive assessment; Neuropsychology; Occupational status; Statistical norms; Statistical regression; Test norms