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Diary Methods, Microgenetic Designs and Intensive Longitudinal Data Analysis |
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Broad emergence of technology-based diary studies has promoted new empirical designs and development of new statistical models for intensive longitudinal data. We report on our studies using diary designs and synthesize our collective experiences. We consider the research epistemology of these studies in light of an emerging idiographic research paradigm.
Mike Todd
[Email Presenter]
Prevention Research Center/Pacific Institute for Research and Evaluation
A Daily Process Approach for Examining Stress, Affect and Alcohol Use
We examined how dispositional coping styles, alcohol-outcome expectancies and drinking motives predict stress- and negative affect-related alcohol use. Our findings indicate some discrepancies among associations found at the within-person versus the between-persons levels of analysis. These discrepancies highlight phenomena that cannot be addressed using traditional cross-sectional or long-term longitudinal designs. Co-authors Stephen Armeli, Pace University, and Howard Tennen, University of Connecticut Health Center.
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Jean-Philippe Laurenceau
[Email Presenter]
University of Miami
Examining Social and Behavioral Processes Using Diary Methods: An Overview and Application of Dynamical System Modeling
Diary methods enable researchers to examine social and behavioral processes within the context of daily life effectively. We present findings from an application of dynamical system modeling to the analysis of diary data to examine intimacy regulation in marriage. We discuss several advantages of diary methods for studying psychological processes. Co-author Steven M. Boker, University of Notre Dame.
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Theodore A. Walls
[Email Presenter]
University of Rhode Island
Intensive Longitudinal Data Analysis
Diary study design and new statistical methods for intensive longitudinal data analysis are considered. Attention is devoted to design selection such as criteria timescale selection and spacing of measurements. Multilevel (HLM), point process, time series and many other models are discussed with attention to design selection and analytical planning. Co-author Joseph Schafer, The Pennsylvania State University.
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Michael J. Rovine
(Discussant)
The Pennsylvania State University
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Time and Location
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