• PROC NLMIXED

  • Referenced in 65 articles [sw11039]
  • likelihood integrated over the random effects. Different integral approximations are available, the principal ones being ... second derivative matrix of the likelihood function. PROC NLMIXED enables you to use the estimated ... estimates of the random effects. You can also estimate arbitrary functions of the nonrandom parameters...
  • FRK

  • Referenced in 93 articles [sw19172]
  • naturally allows for non-stationary, anisotropic covariance functions and the use of observations with varying ... building block of the Spatial Random Effects (SRE) model, on which this package is based ... package FRK provides helper functions to model, fit, and predict using an SRE with relative...
  • curvclust

  • Referenced in 6 articles [sw07435]
  • Wavelet-based clustering for mixed-effects functional models in high dimension. We propose a method ... especially using splines to account for functional random effects. However, splines are not appropriate when ... that both fixed and random effects lie in the same functional space even when dealing ... package that performs curve clustering with random effects in the high dimensional framework (available...
  • WFMM

  • Referenced in 6 articles [sw36436]
  • method extends linear mixed models to functional data consisting of n curves sampled ... design matrix X and random effects matrix Z, and other parameters controlling the computation ... output nonparametric estimates of fixed and random effects functions that have been adaptively regularized...
  • metafor

  • Referenced in 30 articles [sw12291]
  • includes functions to calculate various effect sizes or outcome measures, fit fixed-, random-, and mixed ... person-time data, the package also provides functions that implement specialized methods, including the Mantel...
  • BayesTree

  • Referenced in 59 articles [sw07995]
  • posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis ... unknown regression function as well as the marginal effects of potential predictors. By keeping track...
  • joineR

  • Referenced in 9 articles [sw19777]
  • event data via random effects joint models. Some plotting functions and the variogram are also...
  • rmeta

  • Referenced in 5 articles [sw17235]
  • package rmeta: Meta-analysis. Functions for simple fixed and random effects meta-analysis...
  • nlmeU

  • Referenced in 4 articles [sw07431]
  • linear mixed effects model. Chapter 15 is dedicated to the lmer() function and the description ... nested random effects. The detailed description of concepts and R functions based on them...
  • mvmeta

  • Referenced in 5 articles [sw17236]
  • Meta-Regression. Collection of functions to perform fixed and random-effects multivariate and univariate meta...
  • frailtypack

  • Referenced in 40 articles [sw06070]
  • penalized likelihood estimation on the hazard function but also a parametric estimation. 1) A shared ... proportional hazard models with two correlated random effects (intercept random effect with random slope...
  • ordinal

  • Referenced in 24 articles [sw12561]
  • adaptive Gauss-Hermite quadrature. Multiple random effect terms are allowed and they may be nested ... slice methods for visualizing the likelihood function and checking convergence...
  • bayesmeta

  • Referenced in 1 article [sw22042]
  • package bayesmeta: Bayesian Random-Effects Meta-Analysis. A collection of functions allowing to derive ... parameters in a random-effects meta-analysis, and providing functionality to evaluate joint and marginal...
  • glmmML

  • Referenced in 8 articles [sw07509]
  • allows for the estimation of a fixed effects model, assuming that all cluster intercepts ... implemented to replace asymptotic analysis. The random intercepts model is fitted using a maximum likelihood ... quadrature approximations of the likelihood function. The fixed effects model is fitted through a profiling...
  • HGLMMM

  • Referenced in 6 articles [sw08092]
  • gamma distribution. The distribution of random effects can be specified as Gaussian, gamma, inverse-gamma ... random components and the residual dispersion (overdispersion) can be modeled as a function of covariates ... parameter can be fixed or estimated. Fixed effects in the mean structure can be estimated...
  • streg

  • Referenced in 3 articles [sw37360]
  • random effects. A frailty is a latent multiplicative effect on the hazard function ... shared frailty model is a random effects model where the frailties are common (or shared...
  • HLM

  • Referenced in 44 articles [sw06516]
  • level, but it also predicts the random effects associated with each sampling unit at every ... nominal outcome variables and assumes a functional relationship between the expectation of the outcome...
  • metaSEM

  • Referenced in 5 articles [sw12398]
  • metaSEM package provides functions to conducting univariate and multivariate meta-analysis using a structural equation ... TSSEM) approach to conducting fixed- and random-effects meta-analytic structural equation modeling (MASEM...
  • mixedsde

  • Referenced in 1 article [sw35989]
  • with one or two random effects in the drift function...
  • merlin

  • Referenced in 1 article [sw34074]
  • user to define variables, random effects, spline and fractional polynomial functions, functions of other outcome ... dependent effects are seamlessly incorporated into the predictor. ’merlin’ allows multivariate normal random effects, which...