• tlmec

  • Referenced in 15 articles [sw11119]
  • with censored response using the multivariate-t distribution. Mixed-effects models are commonly used ... nonlinear mixed effects models with censored response (NLMEC/LMEC) based on the multivariate Student-t distribution...
  • mlmmm

  • Referenced in 6 articles [sw11268]
  • missing values. Computational strategies for multivariate linear mixed-effects models with missing values, Schafer...
  • heavy

  • Referenced in 4 articles [sw13216]
  • package includes linear regression, linear mixed-effect models, multivariate location and scatter estimation, penalized splines...
  • Latent GOLD

  • Referenced in 94 articles [sw11673]
  • factor analysis, structural equation models, and random-effects regression models that are based on continuous ... field of finite mixture (FM) models for multivariate normal distributions began to emerge, through ... models seek to separate out or ’un-mix’ data that is assumed to arise...
  • GLLAMM

  • Referenced in 63 articles [sw06517]
  • estimates GLLAMMs (Generalized Linear Latent And Mixed Models) by maximum likelihood (see help gllamm after ... case of discrete random effects or factors, the marginal log-likelihood is evaluated exactly whereas ... numerical integration is used for continuous (multivariate) normal random effects or factors. Two methods...
  • CARBayes

  • Referenced in 14 articles [sw15288]
  • class of univariate and multivariate spatial generalised linear mixed models for areal unit data, with ... modelled by a set of random effects, which are assigned a conditional autoregressive (CAR) prior ... available for the random effects, including a multivariate CAR (MCAR) model for multivariate spatial data...
  • flip

  • Referenced in 5 articles [sw06779]
  • Permutation Tests. It implements many univariate and multivariate permutation (and rotation) tests. Allowed tests ... allows to test for fixed effects in mixed effects models...
  • PSM

  • Referenced in 9 articles [sw13695]
  • estimation of linear and non-linear mixed-effects models using stochastic differential equations. Moreover ... simulation. The package allows for any multivariate non-linear time-variant model to be specified...
  • glmmPQL

  • Referenced in 2 articles [sw12077]
  • Linear Mixed Models via PQL. Fit a GLMM model with multivariate normal random effects, using...
  • longQDA

  • Referenced in 1 article [sw20397]
  • unaddressed issues as model selection and several multivariate extensions. A complementary software implementation ... determining the most appropriate univariate linear mixed model structures for each group and quantify ... with random effects. Subsequently, we present multivariate extensions of long QDA.Two multivariate mixed model classes...
  • abn

  • Referenced in 2 articles [sw31036]
  • equivalent to multivariate generalised linear modelling (including mixed models with iid random effects). The usual...
  • merlin

  • Referenced in 2 articles [sw34074]
  • mixed effects regression models following the framework developed by Crowther (2017) . ’merlin’ can fit multivariate...
  • lmenssp

  • Referenced in 1 article [sw18784]
  • effects coefficients for mixed models with stationary and non-stationary stochastic processes under multivariate normal...
  • DMU

  • Referenced in 1 article [sw30486]
  • Package For Analyzing Multivariate Mixed Models. DMU is a package directed towards applications in quantitative ... variance components and fixed effects (BLUE) and to predict random effects (BLUP). Most ... perform a Derivative-free approach to MUltivariate analysis by Restricted Maximum Likelihood (REML), therefore...
  • SABRE

  • Referenced in 2 articles [sw24536]
  • statistical analysis of multi-process random effect response data. These responses can take the form ... Berridge, D.M., Crouchley, R., (2011), Multivariate Generalized Linear Mixed Models Using R, CRC Press, Boca...
  • GI

  • Referenced in 2 articles [sw37308]
  • effects on outcomes of interest. In addition, GI is tested by means of a multivariate ... many groups are examined. %GI works with mixed categorical, ordinal and continuous covariates. Continuous baseline...
  • ICLUS

  • Referenced in 1 article [sw02611]
  • components analysis (ICA), is used to separate mixed data sources into statistically independent patterns ... reduction technique for multivariate data analysis. We apply ICA to transform multivariate time series data ... experiments show that this method is effective and efficient, which also significantly outperforms other comparable...
  • squid

  • Referenced in 0 articles [sw15534]
  • those who are already familiar with mixed-effects models, as it enables the generation ... power and sensitivity analysis of multilevel and multivariate data...
  • mHMMbayes

  • Referenced in 1 article [sw41419]
  • multilevel (also known as mixed or random effects) hidden Markov model using Bayesian estimation ... model can be fitted on multivariate data with a categorical distribution, and include individual level...
  • CGAL

  • Referenced in 402 articles [sw00118]
  • The goal of the CGAL Open Source Project...