Mixed-Effects Models in S and S-PLUS pp 97-132 | Cite as

# Describing the Structure of Grouped Data

## Chapter Summary

In this chapter we have shown examples of constructing, summarizing, and graphically displaying grouped Data objects. These objects include the data, stored as a data frame, and a formula that designates different variables as a response, a primary covariate, and as one or more grouping factors. Other variables can be designated as outer or inner factors relative to the grouping factors. Accessor or extractor functions are available to extract either the formula for these variables or the value of these variables.

Informative and visually appealing trellis graphics displays of the data can be quickly and easily generated from the information that is stored with the data. The regular data summary functions in S can be applied to the data as well as the gsummary and gapply functions that are especially designed for these data.

Informative plots and summaries of the data are very useful for the preliminary phase of the statistical analysis. Many important features of the data are identified at this stage, but usually one is interested in going a step further in the analysis and fitting parametric models, such as the linear mixed-effects models described in the next chapter.

## Keywords

Grouping Factor Data Frame Transmembrane Pressure Pixel Data Summary Function## Preview

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