Statistical analysis of repeated measures data using SAS procedures.

Clicks: 4
ID: 290182
1998
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Abstract
Mixed linear models were developed by animal breeders to evaluate genetic potential of bulls. Application of mixed models has recently spread to all areas of research, spurred by availability of advanced computer software. Previously, mixed model analyses were implemented by adapting fixed-effect methods to models with random effects. This imposed limitations on applicability because the covariance structure was not modeled. This is the case with PROC GLM in the SAS System. Recent versions of the SAS System include PROC MIXED. This procedure implements random effects in the statistical model and permits modeling the covariance structure of the data. Thereby, PROC MIXED can compute efficient estimates of fixed effects and valid standard errors of the estimates. Modeling the covariance structure is especially important for analysis of repeated measures data because measurements taken close in time are potentially more highly correlated than those taken far apart in time.
Reference Key
openalex_W85196187 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Ramon C. Littell, P. R. Henry, C. B. Ammerman
Journal italian journal of animal science
Year 1998
DOI
10.2527/1998.7641216x
URL
https://doi.org/10.2527/1998.7641216x
Keywords Keywords not found

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