Bayesian Latent Variable Analysis

Fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models.


News

Changes in Version 0.2-1 o Major update to internals: Model matrices/parameters now correspond to the Lisrel representation used in lavaan.

o General parameter equality constraints using '==' are now available (with one parameter on the lhs).

o New function blavInspect() for extracting various pieces of the MCMC run, including HPDs using an optional 'level' argument.

o JAGS syntax now uses the original observed variable names. It also assigns all prior/constraints to a single parameter vector, then defines model matrices based on this parameter vector.

o A list of user-defined initial values can be supplied via the inits argument.

o Posterior predictive computations are parallelized, if package parallel is installed.

o Improved timings for various parts of the model estimation.

Changes in Version 0.1-4 o New convergence="auto" option to run chains until convergence.

o Bug fixes in model estimation: single-indicator lvs, equality constraints
  on exogenous lvs, models with n.chains=1, force runjags parameter summary.

Changes in Version 0.1-3 o Improved support for growth models, including latent variances fixed to 0.

o Extra monitors supplied via jagextra become defined parameters
  in summary().

Changes in Version 0.1-2 o Bayes factors for loadings/regressions now available from summary() via argument bf=TRUE. These are computed via the Savage-Dickey density ratio (assuming normal posterior).

o Bug fix in generation of random initial values when some
  covariance parameters are fixed to 0 (and we use srs priors).

o Explicit translations from JAGS parameterizations to R
  parameterizations. This leads to the availability of
  more fitMeasures under a wider variety of priors.

Changes in Version 0.1-1 o Added plot method related to plot.runjags().

o Added argument jagextra for supplying extra code to JAGS.

o Changes to summary():
  Improving look and operability with lavaan
  Posterior medians/modes now available

o runjags slot in blavaan objects is moved to 
  @external$runjags.

o fitMeasures() now includes BIC and loglik (at posterior means).

o do.fit=FALSE now works, returns only JAGS syntax.

o Random initial values less likely to fail.

o Bug fixes related to equality constraints on mv variances +
  std.lv=T vs TRUE.

Reference manual

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install.packages("blavaan")

0.3-1 by Edgar Merkle, 6 days ago


Browse source code at https://github.com/cran/blavaan


Authors: Edgar Merkle [aut, cre], Yves Rosseel [aut], Mauricio Garnier-Villarreal [ctb]


Documentation:   PDF Manual  


Task views: Psychometric Models and Methods


GPL (>= 2) license


Imports stats, utils, graphics, MASS, MCMCpack, coda, mnormt, nonnest2, loo

Depends on methods, runjags, lavaan

Suggests rstan, modeest, rjags, semTools, parallel


See at CRAN