Table 13.

Simple and multiple regressions with demographic variables as predictors of gains scores on the AARC-50 cognitive functioning subscale

(N = 8639)	Demographic variables as predictors of AARC gains: Simple regressions				Demographic variables as predictors of AARC gains: Multiple regression
	AARC-50 cognitive functioning gains
Variables	Coeff.	[95% CI]	p-value	Standardized Coeff.	Coeff.	[95% CI]	p-value	Standardized Coeff.
Age	−.06	[−.07, −.05]	< .0001	−.10	−.04	[−.06, −.03]	< .001	−.07
Sex	1.30	[1.08, 1.52]	< .0001	.12	1.06	[.84, 1.29]	< .001	.10
Marital status	−.51	[−.74, −.28]	< .0001	−.05	−.51	[−.75, −.28]	< .001	−.05
Employment	.78	[.59, .96]	< .0001	.09	.41	[.18, .63]	< .001	.05
University education	−.63	[−.84, −.41]	< .0001	−.06	−.63	[−.85, −.42]	< .001	−.06
Total R2					.03
Adjusted R2					.03
Model F-test					51.36 (5, 8633); p < .001

Note: In the regression models we included only those participants that have no missing data. AARC-50 cognitive functioning gains = Subscale of the AARC 50-item questionnaire assessing gains in the cognitive functioning domain. Marital status was operationalized as a dichotomous variable capturing whether the participant is married/ civil partnership/ co-habiting or widowed/ separated/ divorced/ single. Employment was operationalized as a dichotomous variable capturing whether the participant is working or not. University education was operationalized as a dichotomous variable. Standardized beta coefficients are calculated by subtracting the mean from the variable and dividing it by its standard deviation