Events Calendar


Event Archive Dates: 

<p>Dr. Jean-Philippe Laurenceau, Psychology, University of Delaware<br>Dr. Niall Bolger, Psychology, Columbia University</p>

Event Dates: 
June 8 - June 11, 2009
Event Time: 
9:00 am- 5:00 pm
University of Massachusetts Amherst

This workshop is for social psychologists, family and medical sociologists, gerontologists, social workers, communication researchers, and researchers of marketing and organizational behavior.

Diary methods allow researchers to examine dyadic processes in daily life in a way that is not possible using traditional methods. Using diaries, researchers typically obtain many repeated observations on dyad members over days and weeks. Dyadic diary data, however, present several data analytic challenges stemming from the various sources of interdependence in these data. Not only is there non-independence between members of the dyad, there is also non-independence of observations within each dyad member. The multilevel or hierarchical linear model (HLM) provides a flexible set of analytic tools that can take account of these complexities. This workshop will begin by considering models for diary data on individuals. It will then cover models for the analysis of dyads, where individual responses are clustered within couples, sibships, caregiving dyads, or other matched pairs. Finally, it will cover models for dyadic diary data. The course will devote equal time to lectures/demonstrations by the presenters and computer lab work by the participants. The main software used will be HLM6 with some advanced applications using SAS PROC MIXED and Mplus. Participants should have strong backgrounds in multiple regression analysis. A list of likely topics includes:
* Introduction to multilevel models for diary data
* Allowing for auto-correlated error terms
* Testing mediation in diary data
* Dyadic consensus and discrepancy
* Partners as multivariate outcomes
* Power in multilevel models
* Actor-partner interdependence model
* Multilevel modeling for dyadic diary data
* Exchangeable vs. distinguishable dyads
* Extending multilevel modeling to dyadic diary data
* Separating state and trait effects with centering
* Dichotomous outcomes
* Psychometrics of diary measures