Daily dairies and other intensive measurement methods are increasingly used to study the relationships between two time varying variables X and Y. These data are commonly analyzed using longitudinal multilevel or bivariate growth curve models that allow for random effects of intercept (and sometimes also slope) but which do not address the effects of weekly cycles in the data. Three Monte Carlo studies investigated the impact of omitting the weekly cycles in daily dairy data under the multilevel model framework.
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- Partial requirement for: M.A., Arizona State University, 2013Note typethesis
- Includes bibliographical references (p. 60-62)Note typebibliography
- Field of study: Psychology