Background: Statistical mediation is an important tool in behavioral health sciences, but it has been confined primarily to continuous variables. As prevention studies become increasingly common, more often the mediator or outcome is binary. Recent work by D. P. MacKinnon and J. H. Dwyer (1993) has explicated the steps necessary to estimate models for mediation when the mediator or the outcome is binary. Objective: To report the release of a set of SAS macros used to implement the statistical analyses required to analyze data with binary and continuous-level data. Approach: A brief introduction to the methodology of mediation analysis in the presence of a binary outcome, mediator, or both is provided. The macros are tested on a sample of 84...
Mediation is a type of analysis used to determine the causal mechanism linking a predictor and an ou...
Analysis of covariance serves two important purposes in a randomized clinical trial. First, there is...
Testing mediation models is critical for identifying potential variables that need to be targeted to...
Abstract: Background: Statistical mediation is an important tool in behavioral health sciences, but ...
Researchers often conduct mediation analysis in order to indirectly assess the effect of a proposed ...
abstract: Methodologists have developed mediation analysis techniques for a broad range of substanti...
A SAS macro for fitting an extension of the Dale (1986) regression model to bivariate ordinal data i...
In recent literature, researchers have put a lot of time and effort in expanding mediation to multil...
Mediation analysis is an important statistical method in prevention research, as it can be used to d...
Measures of effect size are recommended to communicate information on the strength of relationships....
Mediation analysis is one of the most widely used statistical techniques in the social, behavioral, ...
Recent attempts to improve on the quality of psychological research focus on good practices required...
A proper study design assures adequate power to detect statistically significant differences. Existi...
Statistical mediation analysis has become the technique of choice in consumer research to make causa...
Recent attempts to improve on the quality of psychological research focus on good practices required...
Mediation is a type of analysis used to determine the causal mechanism linking a predictor and an ou...
Analysis of covariance serves two important purposes in a randomized clinical trial. First, there is...
Testing mediation models is critical for identifying potential variables that need to be targeted to...
Abstract: Background: Statistical mediation is an important tool in behavioral health sciences, but ...
Researchers often conduct mediation analysis in order to indirectly assess the effect of a proposed ...
abstract: Methodologists have developed mediation analysis techniques for a broad range of substanti...
A SAS macro for fitting an extension of the Dale (1986) regression model to bivariate ordinal data i...
In recent literature, researchers have put a lot of time and effort in expanding mediation to multil...
Mediation analysis is an important statistical method in prevention research, as it can be used to d...
Measures of effect size are recommended to communicate information on the strength of relationships....
Mediation analysis is one of the most widely used statistical techniques in the social, behavioral, ...
Recent attempts to improve on the quality of psychological research focus on good practices required...
A proper study design assures adequate power to detect statistically significant differences. Existi...
Statistical mediation analysis has become the technique of choice in consumer research to make causa...
Recent attempts to improve on the quality of psychological research focus on good practices required...
Mediation is a type of analysis used to determine the causal mechanism linking a predictor and an ou...
Analysis of covariance serves two important purposes in a randomized clinical trial. First, there is...
Testing mediation models is critical for identifying potential variables that need to be targeted to...