Multiple regression is widely used for the analysis of nonexperimental data by investigators in social work and social welfare. Most published studies test additive models in which the effects of each independent variable on the dependent variable are assumed to be constant across all levels of ...
K. (1990). The detection and interpretation of interaction effects between continuous variables in multiple regression. Multivariate Behavioral Research, 25, 467-478.Jaccard James, Choi K Wan, Robert Turrisi. The detection and interpretation of interaction effects between continuous variables in multiple...
plotInteraction(mdl,var1,var2) creates a plot of the main effects of the two selected predictors var1 and var2 and their conditional effects in the linear regression model mdl. Horizontal lines through the effect values indicate their 95% confidence intervals. example plotInteraction(mdl,var1,va...
An interaction effect occurs when the effect of one variable depends on the value of another variable. Interaction effects are common in regression models, ANOVA, and designed experiments. In this post, I explain interaction effects, the interaction effect test, how to interpret interaction models, ...
Moderated multiple regression (MMR) is frequently employed to analyse interaction effects between continuous predictor variables. The procedure of mean centring is commonly recommended to mitigate the potential threat of multicollinearity between predictor variables and the constructed cross-product term. Also...
We provide practical advice for applied economists regarding robust specification and interpretation of linear regression models with interaction terms. We replicate a number of prominently published results using interaction effects and examine if they are robust to reasonable specification permutations. ...
Through comparisons to three models (two fuzzy regression models and one multiple linear regression model) without interaction effects, the proposed approach shows superior performance over its counterparts. This paper also offers critical comments to a notable but questionable paper in this field. ...
The model achieved impressive performance with AUCs of 0.962 in the cross-validation set and 0.939 in the independent test set. By incorporating interaction effects and multimodal data in our model, we observed significant accuracy improvements of 4.76% and 4.29%, respectively. Moreover, our model ...
run a multiple regression analysis with 3 predictors: the mean centered predictors and the interaction predictor.Steps 1 and 2 can be done with basic syntax as covered in How to Mean Center Predictors in SPSS? However, we'll present a simple tool below that does these steps for you.Downloadi...
In subject area: Pharmacology, Toxicology and Pharmaceutical Science An additive interaction refers to the combined effect of two stressors equaling the sum of the two effects in isolation and are thought to arise when two stressors act on different physiological processes (see Glossary; From: Ency...