Multilevel modeling in psychosomatic medicine research

Nicholas D. Myers*, Ahnalee M. Brincks, Allison J. Ames, Guillermo J. Prado, Frank J. Penedo, Catherine Benedict

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

The primary purpose of this study is to provide an overview of multilevel modeling for Psychosomatic Medicine readers and contributors. The article begins with a general introduction to multilevel modeling. Multilevel regression modeling at two levels is emphasized because of its prevalence in psychosomatic medicine research. Simulated data sets based on some core ideas from the Familias Unidas effectiveness study are used to illustrate key concepts including communication of model specification, parameter interpretation, sample size and power, and missing data. Input and key output files from Mplus and SAS are provided. A cluster randomized trial with repeated measures (i.e., three-level regression model) is then briefly presented with simulated data based on some core ideas from a cognitive-behavioral stress management intervention in prostate cancer.

Original languageEnglish (US)
Pages (from-to)925-936
Number of pages12
JournalPsychosomatic medicine
Volume74
Issue number9
DOIs
StatePublished - 2012

Keywords

  • centering
  • hierarchical linear models
  • missing data
  • mixed regression models
  • power
  • random coefficient models

ASJC Scopus subject areas

  • Applied Psychology
  • Psychiatry and Mental health

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