mplus.traceplot: Plot the samples for each MCMC chain as a function of...

In MplusAutomation: An R Package for Facilitating Large-Scale Latent Variable Analyses in Mplus

Plot the samples for each MCMC chain as a function of iterations

Description

Displays a traceplot of the MCMC draws from the poster distribution of each parameter estimate for a Bayesian Mplus model. This function requires that 1) PLOT: TYPE=PLOT2; be included in the Mplus input file, 2) a gh5 file be present corresponding to the Mplus output file (and containing a bayesian_data section), and 3) that the rhdf5 package be installed to allow the gh5 file to be imported.

Usage

mplus.traceplot(mplus.model, rows = 4, cols = 4, parameters_only = TRUE)

Arguments

mplus.model	An Mplus model extracted by the readModels function.
rows	Number of rows to display per plot.
cols	Optional. Number of columns to display per plot.
parameters_only	Optional. If TRUE, only the unstandardized parameter estimates from the MCMC draws will be displayed (as opposed to standardized estimates, r-square estimates, etc.). The unstandardized estimates all begin with "Parameter" in the Mplus gh5 output.

Details

A multi-panel plot is drawn to the screen and the user is prompted to display the next plot if more than rows x columns estimates are in the model.

Value

No value is returned by this function. Called for the side effect of displaying an MCMC chains traceplot.

Note

Trace and density plots can also be obtained using the coda package and the bparameters element of the mplus.model object. This requires that the posterior draws be saved using SAVEDATA: BPARAMETERS syntax. See example below.

Author(s)

Joseph Glass, Michael Hallquist

See Also

plot.mcmc

Examples

## Not run: 
  myModel <- readModels("BayesModel_WithGH5MCMC.out")
  mplus.traceplot(myModel, rows=2, cols=3)

  #alternative using the coda package
  library(coda)
  plot(myModel$bparameters$valid_draw)

## End(Not run)

MplusAutomation documentation built on April 7, 2022, 1:06 a.m.