IPR Methods Workshop: “Statistical Mediation, Moderation, and Conditional Process Analysis."

December 13 - December 14, 2012

2:00PM - 9:30PM

Add to Calendar 2012-12-13 15:00:00 2012-12-14 22:30:00 IPR Methods Workshop: “Statistical Mediation, Moderation, and Conditional Process Analysis." “Statistical Mediation, Moderation, and Conditional Process Analysis” Instructor - Professor Andrew Hayes, School of Communication and Department of Psychology, Ohio State University   Special RequirementsParticipants must bring her/his own laptop.  Applications will be in SPSS or SAS. To derive maximum benefit from workshop, participants should come to the workshop with one or the other installed: (i) SPSS 19 (or later); (ii) SAS 9.1 (or later) with PROC IML already installed.   EligibilityCurrent Ohio State University faculty and graduate students are eligible to attend. Space is limited. ApplyingIf you are interested in attending, please email Susan Pennington by November 28. Make sure to include:your affiliation,position (faculty or graduate student),and research interest.You will be notified via email by November 30 regarding your application status. DetailsThis workshop is focused on the application of principles of linear modeling, primarily using OLS regression, to exploring questions about mediated (i.e., indirect) and moderated (i.e., interaction) effects. Topics include classic and contemporary approaches to testing mediation and moderation hypotheses, path analysis, indirect and direct effects, probing and plotting interactions, and analytically integrating moderation and mediation analysis. We will spend roughly one-third of the workshop talking about partitioning effects into direct and indirect components and how to quantify and test hypotheses about indirect effects, one-third talking about estimating, testing, probing, and visualizing interactions in linear models, and then one-third discussing the integration of moderation and mediation by discussing how to conceptualize and test for conditional indirect effects (“moderated mediation”) and whether moderated effects are mediated (mediated moderation). Examples will focus on the use of the PROCESS procedure (available for both SPSS and SAS) written by Dr. Hayes, which implements the methods described in this workshop and greatly simplifies computational tasks that historically have been tedious. Participants should have a good working knowledge of the principles and practice of multiple regression and elementary statistical inference. No knowledge of matrix algebra is required or assumed. Andrew F. Hayes, Ph.D. (Cornell University, 1996) is Associate Professor of Quantitative Psychology and Associate Professor of Communication at The Ohio State University. He is author of the forthcoming “An Introduction to Mediation, Moderation, and Conditional Process Analysis” (Guilford Press), and currently serves as editor-in-chief of Communication Methods and Measures (Taylor & Francis). OSU ASC Drupal 8 ascwebservices@osu.edu America/New_York public

Add to Calendar 2012-12-13 14:00:00 2012-12-14 21:30:00 IPR Methods Workshop: “Statistical Mediation, Moderation, and Conditional Process Analysis."  “Statistical Mediation, Moderation, and Conditional Process Analysis” Instructor - Professor Andrew Hayes, School of Communication and Department of Psychology, Ohio State University   Special RequirementsParticipants must bring her/his own laptop.  Applications will be in SPSS or SAS. To derive maximum benefit from workshop, participants should come to the workshop with one or the other installed: (i) SPSS 19 (or later); (ii) SAS 9.1 (or later) with PROC IML already installed.   EligibilityCurrent Ohio State University faculty and graduate students are eligible to attend. Space is limited. ApplyingIf you are interested in attending, please email Susan Pennington by November 28. Make sure to include:your affiliation,position (faculty or graduate student),and research interest.You will be notified via email by November 30 regarding your application status.  DetailsThis workshop is focused on the application of principles of linear modeling, primarily using OLS regression, to exploring questions about mediated (i.e., indirect) and moderated (i.e., interaction) effects. Topics include classic and contemporary approaches to testing mediation and moderation hypotheses, path analysis, indirect and direct effects, probing and plotting interactions, and analytically integrating moderation and mediation analysis. We will spend roughly one-third of the workshop talking about partitioning effects into direct and indirect components and how to quantify and test hypotheses about indirect effects, one-third talking about estimating, testing, probing, and visualizing interactions in linear models, and then one-third discussing the integration of moderation and mediation by discussing how to conceptualize and test for conditional indirect effects (“moderated mediation”) and whether moderated effects are mediated (mediated moderation).  Examples will focus on the use of the PROCESS procedure (available for both SPSS and SAS) written by Dr. Hayes, which implements the methods described in this workshop and greatly simplifies computational tasks that historically have been tedious. Participants should have a good working knowledge of the principles and practice of multiple regression and elementary statistical inference. No knowledge of matrix algebra is required or assumed. Andrew F. Hayes, Ph.D. (Cornell University, 1996) is Associate Professor of Quantitative Psychology and Associate Professor of Communication at The Ohio State University.  He is author of the forthcoming “An Introduction to Mediation, Moderation, and Conditional Process Analysis” (Guilford Press), and currently serves as editor-in-chief of Communication Methods and Measures (Taylor & Francis). Institute for Population Research popcenter@osu.edu America/New_York public

“Statistical Mediation, Moderation, and Conditional Process Analysis”

 Instructor - Professor Andrew Hayes, School of Communication and Department of Psychology, Ohio State University  

Special Requirements

Participants must bring her/his own laptop.  
Applications will be in SPSS or SAS. To derive maximum benefit from workshop, participants should come to the workshop with one or the other installed: (i) SPSS 19 (or later); (ii) SAS 9.1 (or later) with PROC IML already installed.

Eligibility

Current Ohio State University faculty and graduate students are eligible to attend. Space is limited.

Applying

If you are interested in attending, please email Susan Pennington by November 28. Make sure to include:

your affiliation,
position (faculty or graduate student),
and research interest.

You will be notified via email by November 30 regarding your application status.

Details

This workshop is focused on the application of principles of linear modeling, primarily using OLS regression, to exploring questions about mediated (i.e., indirect) and moderated (i.e., interaction) effects. Topics include classic and contemporary approaches to testing mediation and moderation hypotheses, path analysis, indirect and direct effects, probing and plotting interactions, and analytically integrating moderation and mediation analysis. We will spend roughly one-third of the workshop talking about partitioning effects into direct and indirect components and how to quantify and test hypotheses about indirect effects, one-third talking about estimating, testing, probing, and visualizing interactions in linear models, and then one-third discussing the integration of moderation and mediation by discussing how to conceptualize and test for conditional indirect effects (“moderated mediation”) and whether moderated effects are mediated (mediated moderation). Examples will focus on the use of the PROCESS procedure (available for both SPSS and SAS) written by Dr. Hayes, which implements the methods described in this workshop and greatly simplifies computational tasks that historically have been tedious.

Participants should have a good working knowledge of the principles and practice of multiple regression and elementary statistical inference. No knowledge of matrix algebra is required or assumed.

Andrew F. Hayes, Ph.D. (Cornell University, 1996) is Associate Professor of Quantitative Psychology and Associate Professor of Communication at The Ohio State University. He is author of the forthcoming “An Introduction to Mediation, Moderation, and Conditional Process Analysis” (Guilford Press), and currently serves as editor-in-chief of Communication Methods and Measures (Taylor & Francis).