Least-Squares Means: The R Package lsmeans

Least-squares means are predictions from a linear model, or averages thereof. They are useful in the analysis of experimental data for summarizing the effects of factors, and for testing linear contrasts among predictions. The lsmeans package (Lenth 2016) provides a simple way of obtaining least-squ...

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Bibliographic Details
Published inJournal of statistical software Vol. 69; no. 1; pp. 1 - 33
Main Author Lenth, Russell V.
Format Journal Article
LanguageEnglish
Published Foundation for Open Access Statistics 2016
Subjects
experimental design
least-squares means
linear models
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Summary:Least-squares means are predictions from a linear model, or averages thereof. They are useful in the analysis of experimental data for summarizing the effects of factors, and for testing linear contrasts among predictions. The lsmeans package (Lenth 2016) provides a simple way of obtaining least-squares means and contrasts thereof. It supports many models fitted by R (R Core Team 2015) core packages (as well as a few key contributed ones) that fit linear or mixed models, and provides a simple way of extending it to cover more model classes.
ISSN:1548-7660
1548-7660
DOI:10.18637/jss.v069.i01