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Tests in Linear Mixed Effects Models
Provides p-values in type I, II or III anova and summary tables for lmer model fits (cf. lme4) via Satterthwaite's degrees of freedom method. A Kenward-Roger method is also available via the pbkrtest package. Model selection methods include step, drop1 and anova-like tables for random effects (ranova). Methods for Least-Square means (LS-means) and tests of linear contrasts of fixed effects are also available.
Generalized Linear Mixed Models using Adaptive Gaussian Quadrature
Fits generalized linear mixed models for a single grouping factor under
maximum likelihood approximating the integrals over the random effects with an
adaptive Gaussian quadrature rule; Jose C. Pinheiro and Douglas M. Bates (1995)
Linear Quantile Mixed Models
Functions to fit quantile regression models for hierarchical
data (2-level nested designs) as described in Geraci and
Bottai (2014, Statistics and Computing)
Linear Mixed Model Solver
An efficient and flexible system to solve sparse mixed model
equations. Important applications are the use of splines to model spatial or temporal
trends as described in Boer (2023). (
Extended Mixed Models Using Latent Classes and Latent Processes
Estimation of various extensions of the mixed models including latent class mixed models, joint latent class mixed models, mixed models for curvilinear outcomes, mixed models for multivariate longitudinal outcomes using a maximum likelihood estimation method (Proust-Lima, Philipps, Liquet (2017)
Genetic Data Handling (QC, GRM, LD, PCA) & Linear Mixed Models
Manipulation of genetic data (SNPs). Computation of GRM and dominance matrix, LD, heritability with efficient algorithms for linear mixed model (AIREML). Dandine et al
Piece-Wise Exponential Additive Mixed Modeling Tools for Survival Analysis
The Piece-wise exponential (Additive Mixed) Model
(PAMM; Bender and others (2018)
Mixed Model ANOVA and Statistics for Education
The main functions perform mixed models analysis by least squares or REML by adding the function r() to formulas of lm() and glm(). A collection of text-book statistics for higher education is also included, e.g. modifications of the functions lm(), glm() and associated summaries from the package 'stats'.
Mixed Effects Cox Models
Fit Cox proportional hazards models containing both fixed and random effects. The random effects can have a general form, of which familial interactions (a "kinship" matrix) is a particular special case. Note that the simplest case of a mixed effects Cox model, i.e. a single random per-group intercept, is also called a "frailty" model. The approach is based on Ripatti and Palmgren, Biometrics 2002.
Generalized Linear Mixed Model Trees
Recursive partitioning based on (generalized) linear mixed models
(GLMMs) combining lmer()/glmer() from 'lme4' and lmtree()/glmtree() from
'partykit'. The fitting algorithm is described in more detail in Fokkema,
Smits, Zeileis, Hothorn & Kelderman (2018;