• lme4

  • Referenced in 204 articles [sw04515]
  • Linear mixed-effects models using S4 classes , Fit linear and generalized linear mixed-effects models...
  • nlme

  • Referenced in 127 articles [sw04481]
  • package nlme: Linear and Nonlinear Mixed Effects Models , Fit and compare Gaussian linear and nonlinear...
  • faraway

  • Referenced in 23 articles [sw04357]
  • Extending the linear model with R. Generalized linear, mixed effects and nonparametric regression models. Linear ... Julian J. Faraway’s critically acclaimed Linear Models with R examined regression and analysis ... Linear Model with R surveys the techniques that grow from the regression model, presenting three ... extensions to that framework: generalized linear models (GLMs), mixed effect models, and nonparametric regression models...
  • multcomp

  • Referenced in 30 articles [sw10485]
  • hypotheses in parametric models, including linear, generalized linear, linear mixed effects, and survival models...
  • metafor

  • Referenced in 30 articles [sw12291]
  • outcome measures, fit fixed-, random-, and mixed-effects models to such data, carry out moderator ... variety of suitable generalized linear (mixed-effects) models (i.e., mixed-effects (conditional) logistic and Poisson...
  • Lmertest

  • Referenced in 8 articles [sw14397]
  • lmerTest: Tests in Linear Mixed Effects Models. Different kinds of tests for linear mixed effects...
  • Monolix

  • Referenced in 12 articles [sw06988]
  • analysis of non linear mixed effects models. The objective of this software is to perform...
  • IFISS

  • Referenced in 236 articles [sw04398]
  • problems. It includes algorithms for discretization by mixed finite element methods and a posteriori error ... discrete linear equation systems that arise in incompressible flow modelling. A unique feature ... interaction between the two and the resulting effect on overall efficiency...
  • glmmAK

  • Referenced in 25 articles [sw13218]
  • Package glmmAK: Generalized Linear Mixed Models. This package implements maximum-likelihood estimation in the logistic ... model) and multinomial response (cumulative logit model), and in the Poisson regression (log-linear model ... logistic and Poisson regression model with random effects whose distribution is specified as a penalized ... Generalized linear mixed model with a penalized Gaussian mixture as a random-effects distribution. Computational...
  • PSM

  • Referenced in 8 articles [sw13695]
  • Linear Mixed-Effects modelling using Stochastic Differential Equations. This package provides functions for estimation ... linear and non-linear mixed-effects models using stochastic differential equations. Moreover it provides functions ... model states and for simulation. The package allows for any multivariate non-linear time-variant...
  • glimmix

  • Referenced in 28 articles [sw11740]
  • GLMM). GLMMs, like linear mixed models, assume normal (Gaussian) random effects. Conditional on these random...
  • nlmeU

  • Referenced in 4 articles [sw07431]
  • Linear mixed-effects models using R. A step-by-step approach. “Linear mixed effects models ... part of the book, on linear mixed effects models, commences with the description ... specify and fit a linear mixed effects model. Chapter 15 is dedicated to the lmer ... tools for the linear mixed effects models, briefly presented in chapter 20. In addition...
  • pbkrtest

  • Referenced in 6 articles [sw24087]
  • mixed effects models. Attention is on mixed effects models as implemented in the ’lme4’ package ... modification of F-tests for linear mixed effects models and a parametric bootstrap test...
  • STJM

  • Referenced in 7 articles [sw19776]
  • survival data. stjm fits shared parameter joint models for longitudinal and survival data using maximum ... survival outcome are allowed. A linear mixed effects model is used for the longitudinal submodel...
  • robustlmm

  • Referenced in 4 articles [sw23530]
  • Linear Mixed-Effects Models. As any real-life data, data modeled by linear mixed-effects ... package, robustlmm, to robustly fit linear mixed-effects models. The package’s functions and methods ... package that implements classic linear mixed-effects model estimation in R. The robust estimation method ... show how to fit robust linear mixed-effects models using robustlmm, how to assess...
  • MMS

  • Referenced in 5 articles [sw31391]
  • Package MMS: Fixed Effects Selection in Linear Mixed Models. Perform Fixed effects Selection in Linear...
  • aod

  • Referenced in 5 articles [sw14700]
  • estimating equations (GEE) or generalized linear mixed effect models (GLMM...
  • tlmec

  • Referenced in 11 articles [sw11119]
  • response using the multivariate-t distribution. Mixed-effects models are commonly used to fit longitudinal ... normal distributions are commonly assumed for random effects and residual errors, such assumptions make inferences ... likelihood-based inference for linear and nonlinear mixed effects models with censored response (NLMEC/LMEC) based...
  • curvclust

  • Referenced in 6 articles [sw07435]
  • Wavelet-based clustering for mixed-effects functional models in high dimension. We propose a method ... using splines to account for functional random effects. However, splines are not appropriate when dealing ... random effect variance, we ensure that both fixed and random effects lie in the same ... model resumes to a linear mixed-effects model that can be used for a model...
  • MIXED

  • Referenced in 73 articles [sw06480]
  • summarizes the methodology of the linear mixed model approach for the analysis of repeated measurements ... Software. PROC MIXED in SAS provides a very flexible environment in which models ... experimental units can be modeled using random effects and through the specification of a covariance...