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CLME (version 2.0-6)

Constrained Inference for Linear Mixed Effects Models

Description

Estimation and inference for linear models where some or all of the fixed-effects coefficients are subject to order restrictions. This package uses the robust residual bootstrap methodology for inference, and can handle some structure in the residual variance matrix.

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Version

Install

install.packages('CLME')

Monthly Downloads

206

Version

2.0-6

License

GPL-3

Maintainer

Casey M Jelsema

Last Published

November 8th, 2016

Functions in CLME (2.0-6)

Akaike information criterion

Constrained Inference for Linear Mixed Effects Models

Constructor method for objects S3 class clme

Individual confidence intervals

Constrained EM algorithm for linear fixed or mixed effects models.

Computes various types of residuals

Constrained inference for linear mixed models.

Bayesian information criterion

Fibroid Growth Study

create.constraints

Generate common order constraints

Number of observations

model_terms_clme

Create model matrices for clme

MINQUE Algorithm

Extract fixed effects

Likelihood ratio type statistic (global)

Extract formula

S3 method to plot objects of class clme

model.frame.clme

Extracts the model frame

model.matrix.clme

Extract the model design matrix.

Extract random effects

print.summary.clme

S3 method to print a summary for objects of class clme

Printout of fitted object.

Shiny GUI for CLME

Extract random effects

Various types of residuals

Experiment on mice

plot.summary.clme

S3 method to plot objects of class clme

print.varcorr_clme

Printout for variance components

Obtain Residual Bootstrap

Produce summary values for objects of class clme

Variance components

sigma.summary.clme

Residual variance components

Residual variance components

Variance-covariance matrix

Williams' Type Test Statistic.