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ARMD Trial: Linear Model with Homogeneous Variance

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Linear Mixed-Effects Models Using R

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Abstract

In this chapter, we illustrate the use of the R tools, described in Sects. 5.2–5.5.We apply them to fit an LM with independent, homoscedastic residual errors to the visual acuity measurements from the ARMD dataset. Note that the model is considered for software illustration purposes only. In view of the structure of the data and of the results of the exploratory analysis presented in Sect. 3.2, the assumptions of the independence and homoscedasticity of the visual acuity measurements are not correct. More advanced LMs, which properly take into account the structure of the data and do not require these assumptions, will be presented in Chaps. 12 and 16.

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Authors and Affiliations

  1. University of Michigan, 300 North Ingalls Building, Ann Arbor, Michigan, USA

    Andrzej Gałecki

  2. Center for Statistics, Hasselt University, Agoralaan D, Diepenbeek, Belgium

    Tomasz Burzykowski

Authors
  1. Andrzej Gałecki
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  2. Tomasz Burzykowski
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Gałecki, A., Burzykowski, T. (2013). ARMD Trial: Linear Model with Homogeneous Variance. In: Linear Mixed-Effects Models Using R. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-3900-4_6

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