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Table 14 Simple and multiple regressions with demographic variables as predictors of losses scores on the AARC-50 cognitive functioning subscale

From: International relevance of two measures of awareness of age-related change (AARC)

(N = 8639) Demographic variables as predictors of AARC losses: Simple regressions Demographic variables as predictors of AARC losses: Multiple regressions
  AARC-50 cognitive functioning losses
Variables Coeff. [95% CI] p-value Standardized Coeff. Coeff. [95% CI] p-value Standardized Coeff.
Age .08 [.07, .09] < .001 .17 .07 [.05, .08] < .001 .13
Sex −.88 [−1.06, −.70] < .001 −.11 −.76 [−.95, −.58] < .001 −.09
Marital status −.33 [−.51, −.14] < .001 −.04 −.17 [−.36, .03] .09 −.02
Employment −.84 [−.99, −.69] < .001 −.12 −.24 [−.43, −.06] .01 −.03
University education −.47 [−.64, −.30] < .001 −.06 −.41 [−.59, −.24] < .001 −.05
Total R2   .04
Adjusted R2   .04
Model F-test   70.07 (5, 8633); p < .001
  1. Note: In the regression models we included only those participants that have no missing data. AARC-50 cognitive functioning losses = Subscale of the AARC 50-item questionnaire assessing losses in the cognitive functioning domains. 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