
Latent GOLD
 Referenced in 93 articles
[sw11673]
 factor analysis, structural equation models, and randomeffects regression models that are based on continuous...

FRK
 Referenced in 90 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 59 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 72 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 245 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 40 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...

glmmAK
 Referenced in 25 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...

TMB
 Referenced in 15 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...

glimmix
 Referenced in 27 articles
[sw11740]
 GLMMs, like linear mixed models, assume normal (Gaussian) random effects. Conditional on these random effects...

metafor
 Referenced in 29 articles
[sw12291]
 outcome measures, fit fixed, random, and mixedeffects models to such data, carry out moderator...

ConfBands
 Referenced in 29 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...

meta
 Referenced in 10 articles
[sw17233]
 Knapp and PauleMandel method for random effects model;  cumulative metaanalysis and leave...

glmmML
 Referenced in 8 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...

BradleyTerry2
 Referenced in 19 articles
[sw09554]
 penalized quasilikelihood (for models which involve a random effect), or by biasreduced maximum...

coxme
 Referenced in 10 articles
[sw19055]
 coxme: Mixed Effects Cox Models. Cox proportional hazards models containing Gaussian random effects, also known...

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

BayesTree
 Referenced in 58 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...

HLM
 Referenced in 42 articles
[sw06516]
 estimates model coefficients at each level, but it also predicts the random effects associated with...

joineR
 Referenced in 9 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...

dhglm
 Referenced in 4 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...