The framework was outlined by three major components: the interface features of a product as design variables, the evaluation context consisting of user, product, activity, and environment as context variables, and the usability measures as dependent variables.
General linear models with ISIP variability measures as dependent variables, condition (Low Motivation or High Motivation) as a repeated-measures variable and intelligence as a between-subject variable, revealed a significant effect of intelligence, but no effects of incentive, nor of the intelligence × incentive interaction.
We apply four different publication success measures as dependent variables.
Separate hierarchical linear regression models were developed, with clinical (health status, pain intensity, and disability) and psychological (kinesiophobia, catastrophizing, fear avoidance, anxiety, depressive symptoms, and self-efficacy) measures as dependent variables.
We fit three unconditional logistic regression models: (1) unadjusted model, (2) adjusted model for selected variables, and (3) adjusted random-effects model for selected variables and potential clustering of patients within EDs, with each of the four outcome measures as dependent variables.
Behavioral scores were analyzed using a multifactor or repeated measures ANOVA including genotype or treatment as independent variables, and escape latencies during training and probe trial measures as dependent variables.
A rotatable central composite design with five center points was used and powder yield (PY), moisture content (MC), purity value (PV) and glass transition temperature (Tg) of powders were measured as dependent variables.
Logistic regressions were made with each outcome measure as dependent variable.
Models were run for each combination of oral health measure (as dependent variable) and SEP indicator (as categorical explanatory variable) adjusting for age, gender, marital status, geographical location, self-rated general health, and long-standing illness.
1Figures in the tables represent standardized regression coefficients estimated using a multivariable regression model having the summary measure as dependent variables and items as independent The internal consistency measuring the extent to which the items are interrelated were expressed by the coefficients Cronbach's Alpha calculated for each study.
Multivariate ANOVA's were carried out with sex of face as the fixed factor and masculinity measures as the dependent variables.
