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Medicine: Mind the Gap Seminar: Applying Mediation Analysis To Understand How Interventions Work

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Air date: Friday, April 8, 2016, 11:00:00 AM
Time displayed is Eastern Time, Washington DC Local
Views: Total views: 181, (116 Live, 65 On-demand)
Category: Medicine: Mind the Gap
Runtime: 00:58:18
Description: Medicine: Mind the Gap Seminar

Dr. MacKinnon will describe mediation analysis methods with attention to solutions for some of the limitations of these methods. Mediating variables have a long and important history in theoretical and applied research, because they describe how and why two variables are related. One common example is the study of the mediating processes that explain how a prevention or treatment program achieves its effects on an outcome variable. If the active ingredients are identified, then interventions can be made more powerful and more efficient. Other mediating variable examples include how a risk factor leads to disease and how early life experiences affect later development. Over the last decade, there has been considerable development of new methods and wider substantive application of mediation analysis. The presentation will describe the questions mediation analysis can answer and how mediating variables differ from moderators, confounders, and covariates. The analysis of the single- and multiple-mediator models are used to demonstrate several controversial issues in inference, sigficance testing, and confidence interval estimation. New models for longitudinal mediation and approaches to investigating assumptions of the mediation model are described. Dr. MacKinnon will also discuss future directions in mediation theory and statistical analysis.

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NLM Title: Applying mediation analysis to understand how interventions work / David P. MacKinnon ; NIH TV Studio.
Author: MacKinnon, David Peter.
NIH TV Studio,
Publisher:
Abstract: (CIT): Medicine: Mind the Gap Seminar Dr. MacKinnon will describe mediation analysis methods with attention to solutions for some of the limitations of these methods. Mediating variables have a long and important history in theoretical and applied research, because they describe how and why two variables are related. One common example is the study of the mediating processes that explain how a prevention or treatment program achieves its effects on an outcome variable. If the active ingredients are identified, then interventions can be made more powerful and more efficient. Other mediating variable examples include how a risk factor leads to disease and how early life experiences affect later development. Over the last decade, there has been considerable development of new methods and wider substantive application of mediation analysis. The presentation will describe the questions mediation analysis can answer and how mediating variables differ from moderators, confounders, and covariates. The analysis of the single- and multiple-mediator models are used to demonstrate several controversial issues in inference, sigficance testing, and confidence interval estimation. New models for longitudinal mediation and approaches to investigating assumptions of the mediation model are described. Dr. MacKinnon will also discuss future directions in mediation theory and statistical analysis.
Subjects: Behavioral Research
Models, Statistical
Publication Types: Lectures
Webcasts
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NLM Classification: WM 20
NLM ID: 101682314
CIT Live ID: 18792
Permanent link: https://videocast.nih.gov/launch.asp?19607