Example Analyses of the Blood Lead Level Data

George J. Knafl ()
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George J. Knafl: University of North Carolina at Chapel Hill, School of Nursing

Chapter Chapter 9 in Modeling Correlated Outcomes Using Extensions of Generalized Estimating Equations and Linear Mixed Modeling, 2026, pp 225-265 from Springer

Abstract: Abstract Adaptive analyses are presented of blood lead levels for children at 0, 1, 4, and 6 weeks using exponential regression with the natural log link function. The choice of the number of folds is addressed as well as the choice of the directly specified correlation structure. Results are compared for partially modified generalized estimating equations (GEE), fully modified GEE, and extended linear mixed modeling (ELMM). Linearity of the log of the means in week with constant dispersions is addressed as well as a comparison to standard GEE modeling and the dependence of means and dispersions on week. Adaptive additive and adaptive moderation models are generated for week and the indicator for being on the chelating agent succimer. Direct variance modeling of the blood lead levels is addressed. Models based on directly specified correlation structures are compared to models based on random effects/coefficients. A summary of the analysis results is provided. SAS code for generating these analyses is described along with output generated by that code.

Keywords: Direct variance modeling; Extended linear mixed modeling; Generalized estimating equations; Exponential regression; Moderation; Non-constant dispersions; Random effects/coefficients (search for similar items in EconPapers)
Date: 2026
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DOI: 10.1007/978-3-032-00989-0_9

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