Fit a variety of Bayesian latent variable models, including confirmatory factor analysis, structural equation models, and latent growth curve models.
Changes in Version 0.2-4 o Add 'seed' argument for setting the random seeds in each JAGS chain.
o Bug fixes found in previous version.
Changes in Version 0.2-3 o New function blavCompare() for comparing models via ICs and BFs (code from Mauricio Garnier-Villarreal).
o Defined parameters are now sampled via MCMC, vs estimated via delta method. o blavInspect() gains 'jagnames' option, showing correspondence between blavaan parameter names and JAGS parameter names. o Fix bugs in (i) marginal log-lik computation under cp='fa', and (ii) calculated number of parameters under complex equality constraints.
Changes in Version 0.2-2 o Fix bug in 0.2-1 causing model estimation to crash on Windows only.
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.