
Latent GOLD
 Referenced in 94 articles
[sw11673]
 factor analysis, structural equation models, and randomeffects regression models that are based on continuous...

FRK
 Referenced in 119 articles
[sw19172]
 Rank Kriging is a tool for spatial/spatiotemporal modelling and prediction with large datasets. The approach ... building block of the Spatial Random Effects (SRE) model, on which this package is based...

PROC NLMIXED
 Referenced in 68 articles
[sw11039]
 which both fixed and random effects enter nonlinearly. These models have a wide variety ... distribution for your data (given the random effects) having either a standard form (normal, binomial ... mixed models by maximizing an approximation to the likelihood integrated over the random effects. Different ... model to construct predictions of arbitrary functions by using empirical Bayes estimates of the random...

MIXED
 Referenced in 75 articles
[sw06480]
 experimental units can be modeled using random effects and through the specification of a covariance ... MIXED provides a useful covariance structures or modeling both in time and space, including discrete...

FODE
 Referenced in 296 articles
[sw08377]
 effective in a rich variety of scenarios such as continuous time random walk models, generalized ... corresponding stability condition is got. The effectiveness of this numerical algorithm is evaluated by comparing...

frailtypack
 Referenced in 43 articles
[sw06070]
 models for proportional hazard models with two correlated random effects (intercept random effect with random ... slope). 3) Nested frailty models for hierarchically clustered data (with 2 levels of clustering ... including two iid gamma random effects. 4) Joint frailty models in the context of joint...

TMB
 Referenced in 23 articles
[sw16279]
 package TMB: Template Model Builder: A General Random Effect Tool Inspired by ’ADMB’. With this ... able to quickly implement complex random effect models through simple C++ templates. The package combines...

glmmAK
 Referenced in 26 articles
[sw13218]
 logistic and Poisson regression model with random effects whose distribution is specified as a penalized ... linear mixed model with a penalized Gaussian mixture as a randomeffects distribution. Computational Statistics...

metafor
 Referenced in 33 articles
[sw12291]
 outcome measures, fit fixed, random, and mixedeffects models to such data, carry out moderator...

ConfBands
 Referenced in 34 articles
[sw12330]
 effect) nonparametric model, (b) using the mixedmodel framework with the spline coefficients as random ... frequentist perspective. We show that the mixedmodel formulation of penalized splines can help obtain...

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

glmmML
 Referenced in 9 articles
[sw07509]
 models with clustered data: fixed and random effects models The statistical analysis of mixed effects ... random intercepts. It also allows for the estimation of a fixed effects model, assuming that ... implemented to replace asymptotic analysis. The random intercepts model is fitted using a maximum likelihood ... approximations of the likelihood function. The fixed effects model is fitted through a profiling approach...

meta
 Referenced in 11 articles
[sw17233]
 Knapp and PauleMandel method for random effects model;  cumulative metaanalysis and leave...

coxme
 Referenced in 13 articles
[sw19055]
 coxme: Mixed Effects Cox Models. Cox proportional hazards models containing Gaussian random effects, also known...

BartPy
 Referenced in 83 articles
[sw40584]
 develop a Bayesian “sumoftrees” model where each tree is constrained by a regularization ... posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis ... particular, BART is defined by a statistical model: a prior and a likelihood. This approach ... regression function as well as the marginal effects of potential predictors. By keeping track...

BradleyTerry2
 Referenced in 22 articles
[sw09554]
 penalized quasilikelihood (for models which involve a random effect), or by biasreduced maximum...

dhglm
 Referenced in 7 articles
[sw21272]
 linear models in which the mean, dispersion parameters for variance of random effects, and residual ... overdispersion) can be further modeled as randomeffect models...

BayesTree
 Referenced in 64 articles
[sw07995]
 develop a Bayesian “sumoftrees” model where each tree is constrained by a regularization ... posterior. Effectively, BART is a nonparametric Bayesian regression approach which uses dimensionally adaptive random basis ... particular, BART is defined by a statistical model: a prior and a likelihood. This approach ... regression function as well as the marginal effects of potential predictors. By keeping track...

joineR
 Referenced in 11 articles
[sw19777]
 package joineR: Joint Modelling of Repeated Measurements and TimetoEvent Data. Analysis of repeated ... timetoevent data via random effects joint models. Some plotting functions and the variogram...

npmlreg
 Referenced in 7 articles
[sw08191]
 npmlreg: Nonparametric maximum likelihood estimation for random effect models. Nonparametric maximum likelihood estimation or Gaussian...