abstract: Methodologists have developed mediation analysis techniques for a broad range of substantive applications, yet methods for estimating mediating mechanisms with missing data have been understudied. This study outlined a general Bayesian missing data handling approach that can accommodate mediation analyses with any number of manifest variables. Computer simulation studies showed that the Bayesian approach produced frequentist coverage rates and power estimates that were comparable to those of maximum likelihood with the bias-corrected bootstrap. We share an SAS macro that implements Bayesian estimation and use 2 data analysis examples to demonstrate its use."This is an Author's Accepted Manuscript of an article published in Multiva...
Background: Statistical mediation is an important tool in behavioral health sciences, but it has bee...
textPartially clustered design is common in medicine, social sciences, intervention and psychologica...
We propose a nonparametric Bayesian approach to estimate the natural direct and indirect effects thr...
Bayesian methods have the potential for increasing power in mediation analysis (Koopman, Howe, Holle...
In order to quantify the relationship between multiple variables, researchers often carry out a medi...
Mediation analysis in social psychology is currently somewhat confused. Many competing techniques ar...
Mediation and moderated mediation models are two commonly used models for indirect effects analysis....
In human sciences, mediation designates a particular causal phenomenon where the effect of a variabl...
Bayesian statistics provide researchers a powerful tool when analyzing data. The purpose of this pro...
3 figures. A missing appendix sections added and a text about prior specification added in section 4...
Many research studies aim to unveil the causal mechanism underlying a particular phenomenon; mediati...
In mediational settings, the main focus is on the estimation of the indirect effect of an exposure o...
In crossed random effects designs, observations are nested in the combination of two random factors,...
Mediation analysis is widely used for investigating direct and indirect causal pathways through whic...
Mediation analysis is a standard approach to understanding how and why an intervention works in soci...
Background: Statistical mediation is an important tool in behavioral health sciences, but it has bee...
textPartially clustered design is common in medicine, social sciences, intervention and psychologica...
We propose a nonparametric Bayesian approach to estimate the natural direct and indirect effects thr...
Bayesian methods have the potential for increasing power in mediation analysis (Koopman, Howe, Holle...
In order to quantify the relationship between multiple variables, researchers often carry out a medi...
Mediation analysis in social psychology is currently somewhat confused. Many competing techniques ar...
Mediation and moderated mediation models are two commonly used models for indirect effects analysis....
In human sciences, mediation designates a particular causal phenomenon where the effect of a variabl...
Bayesian statistics provide researchers a powerful tool when analyzing data. The purpose of this pro...
3 figures. A missing appendix sections added and a text about prior specification added in section 4...
Many research studies aim to unveil the causal mechanism underlying a particular phenomenon; mediati...
In mediational settings, the main focus is on the estimation of the indirect effect of an exposure o...
In crossed random effects designs, observations are nested in the combination of two random factors,...
Mediation analysis is widely used for investigating direct and indirect causal pathways through whic...
Mediation analysis is a standard approach to understanding how and why an intervention works in soci...
Background: Statistical mediation is an important tool in behavioral health sciences, but it has bee...
textPartially clustered design is common in medicine, social sciences, intervention and psychologica...
We propose a nonparametric Bayesian approach to estimate the natural direct and indirect effects thr...