Topic
Interaction
About: Interaction is a research topic. Over the lifetime, 151 publications have been published within this topic receiving 10846 citations.
Papers published on a yearly basis
1 / 2
Papers
TL;DR: The authors discusses the concept of interaction, the use of product terms to test for its presence, the problems of multicollinearity and nonlinear interaction effects and the proper use of subgroup analysis.
Abstract: 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 additional independent variables. Tests are seldom made for the presence of interacting or modifier effects. This article discusses the concept of interaction, the use of product terms to test for its presence, the problems of multicollinearity and nonlinear interaction effects and the proper use of subgroup analysis.
2,072 citations
1,979 citations
TL;DR: In this paper, the authors present a data structure for yield trials with both significant main effects and a significant genotype x environment (GE) interaction, which is not always effective with this data structure: the usual analysis of variance (ANOVA), having a merely additive qualitative model, identifies the GE interaction as a source but does not analyze it; principal components analysis (PCA), on the other hand, is a multiplicative model and hence contains no sources for additive qualitative effects.
Abstract: Yield trials frequently have both significant main effects and a
significant genotype x environment (GE) interaction. Traditional
statistical analyses are not always effective with this data structure:
the usual analysis of variance (ANOVA), having a merely additive
model, identifies the GE interaction as a source but does not analyze
it; principal components analysis (PCA), on the other hand is a
multiplicative model and hence contains no sources for additive
genotype or environment main effects; and linear regression (LR)
analysis is able to effectively analyze interaction terms only where
the pattern fits a specific regression model. The consequence of fitting
inappropriate statistical models to yield trial data is that the
interaction may be declared nonsignificant, although a more appropriate
analysis would find agronomically important and statistically
significant patterns in the interaction. Therefore, agronomists and
plant breeders may fail to perceive important interaction effects.
1,581 citations
Book•
1 Jan 1980
TL;DR: In this paper, applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results, including residuals, interaction effects, specification error, multicollinearity, standardized coefficients, and dummy variables.
Abstract: Applied regression allows social scientists who are not specialists in quantitative techniques to arrive at clear verbal explanations of their numerical results. Provides a lucid discussion of more specialized subjects: analysis of residuals, interaction effects, specification error, multicollinearity, standardized coefficients, and dummy variables.
1,099 citations
TL;DR: It is argued that although additive transformations do not affect the overall test of statistical interaction, they do affect the interpretational value of regression coefficients.
Abstract: issues in the detection and interpretation of interaction effects between quantitative variables in multiple regression analysis are discussed. Recent articles by Cronbach (1987) and Dunlap and Kemery (1987) suggested the use of two transformations to reduce "problems" of multicollinearity. These transformations are discussed in the context of the conditional nature of multiple regression with product terms. It is argued that although additive transformations do not affect the overall test of statistical interaction, they do affect the interpretational value of regression coefficients. Factors other than multicollinearity that may account for failures to observe interaction effects are noted.
780 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2025 | 21 |
| 2024 | 40 |
| 2023 | 69 |
| 2022 | 105 |
| 2021 | 4 |
| 2020 | 2 |