Formal testing using multiple regression with interaction terms showed no evidence of interaction between severity of disease and randomised treatment on treatment effect for worst episode of itch.
In the multiple regression analyses multiplicative interaction effects were entered to explore whether early weight is modifying the effect of later weight size on adult overweight with a type I error rate of 0.10 [28].
Multiple regression confirmed the interaction effect of competence level and accommodation level on psychic costs and that psychic costs affected shopping satisfaction.
Multiple regression analysis (psychophysiological interaction analysis) of resting-state fMRI before and after TMS intervention (N = 15).
Analyses included multiple regressions with interactions.
To demonstrate the capability of the computational model, the GA SVR modeling results were compared with those obtained using numeric predictive models (i.e., classification and regression tree, chi-squared automatic interaction detector, multiple regression, artificial neural network, and ensemble models) and empirical methods.
Log transformation of HOMA-IR did not improve the R value in the multiple regression equation but eliminated the interaction between index and race.
In the first contrast of the multiple regression analysis, a significant linear interaction was found in "step time variability fast-DTC" with no change in the two cognitive physical interventions (DANCE and MEMORY) and rising DTC in PHYS =2.95, P=0.044, one-tailed, R=0.010).
However, the multiple regression analyses indicated that the interactions between CHD and body weight contributed significantly to explain the improvement in pain signs.
The modprobe SPSS macro (Hayes & Matthes, 2009) for exploration of interactions in multiple regression was used, with training condition (stop or double, dummy-coded) as the focal predictor variable, dietary restraint as the moderator variable, and calorie intake as the dependent variable.
