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HPLMIXED


The HPLMIXED procedure is a high-performance version of the MIXED procedure in SAS/STAT software. The HPLMIXED procedure fits a variety of mixed linear models to data and enables you to use these fitted models to make statistical inferences about the data. A mixed linear model is a generalization of the standard linear model used in the GLM procedure in SAS/STAT software; the generalization is that the data are permitted to exhibit correlation and nonconstant variability. Therefore, the mixed linear model provides you with the flexibility of modeling not only the means of your data (as in the standard linear model) but also their variances and covariances. PROC HPLMIXED runs in either single-machine mode or distributed mode. The procedure enables you to do the following:

  • fits general linear models with fixed and random effects under the assumption that the data are normally distributed. The types of models include:
    • simple regression
    • multiple regression
    • analysis of variance for balanced or unbalanced data
    • analysis of covariance
    • response surface models
    • weighted regression
    • polynomial regression
    • partial correlation
  • Restricted Maximum Likelihood (REML) and Maximum Likelihood (ML)
  • uses sparse matrix approach
  • fits 20 covariance structures including
    • variance components
    • compound symmetry (exchangeable)
    • unstructured correlation
    • AR(1) and ARMA(1,1)
  • provides appropriate standard errors for all specified estimable linear combinations of fixed and random effects, and corresponding t and F tests
  • enables you to construct custom hypothesis tests
  • enables you to construct custom scalar estimates and their confidence limits
  • computes least square means and least square mean differences for classification fixed effects
  • permits subject and group effects that enable blocking and heterogeneity, respectively
  • performs multiple comparison of main effect means
  • computes Type I, Type II, and Type III tests of fixed effects
  • performs weighted estimation
  • specify performance options
  • supports BY group processing, which allows separate analyses on grouped observations
  • creates a data set that contains predicted values and residual diagnostics
  • creates a SAS data set that corresponds to any output table

For further details see the SAS/STAT User's Guide: The HPLMIXED Procedure
( PDF | HTML )

Examples