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Additional Example Analyses

In: Modeling Correlated Outcomes Using Extensions of Generalized Estimating Equations and Linear Mixed Modeling

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  • George J. Knafl

    (University of North Carolina at Chapel Hill, School of Nursing)

Abstract

Adaptive analyses are conducted in this chapter of data sets not considered in prior analyses using analysis strategies determined from those prior analyses. Analyses are conducted of cross-sectionally measured correlated outcomes provided by single mothers on three scales measuring family management of a child’s chronic condition (e.g., diabetes, Crohn’s disease, cystic fibrosis). Analyses are also provided of cross-sectionally measured correlated dyadic outcomes with some missing outcome values as provided by partnered parents of a child having a chronic condition using measures assessing the child’s conduct-disordered behaviors. These dyadic analyses are based on three related outcomes including a continuous outcome treated as normally distributed, a count outcome treated as Poisson distributed, and a dichotomous outcome treated as Bernoulli distributed. Extended linear mixed modeling (ELMM) is used to conduct all analyses. Whether non-constant or unit dispersions are appropriate is addressed as well as adaptive additive and adaptive moderation modeling. A comparison of results for extended variance modeling and direct variance modeling is also provided when appropriate.

Suggested Citation

  • George J. Knafl, 2023. "Additional Example Analyses," Springer Books, in: Modeling Correlated Outcomes Using Extensions of Generalized Estimating Equations and Linear Mixed Modeling, chapter 0, pages 485-512, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-41988-1_16
    DOI: 10.1007/978-3-031-41988-1_16
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