[su_tabs] [su_tab title=“xxM”]

Load xxM and data

Construct R-matrices

For each parameter matrix, construct three related matrices:

  1. pattern matrix: A matrix indicating free or fixed parameters.
  2. value matrix: with start or fixed values for corresponding parameters.
  3. label matrix: with user friendly label for each parameter. label matrix is optional.

Construct main model object

xxmModel() is used to declare level names. The function returns a model object that is passed as a parameter to subsequent stattements.

Add submodels to the model objects

For each declared level xxmSubmodel() is invoked to add corresponding submodel to the model object. The function adds three pieces of information: 1. parents declares a list of parents of the current level. 2. variables declares names of observed dependent (ys), observed independent (xs) and latent variables (etas) for the level. 3. data R data object for the current level.

Add Within-level parameter matrices for each submodel

For each declared level xxmWithinMatrix() is used to add within-level parameter matrices. For each parameter matrix, the function adds the three matrices constructed earlier:

Add Across-level parameter matrices to the model

Pairs of levels that share parent-child relationship have regression relationships. xxmBetweenMatrix() is used to add corresponding parameter matrices connecting the two levels.

For each parameter matrix, the function adds the three matrices constructed earlier:

Estimate model parameters

Estimation process is initiated by xxmRun(). If all goes well, a quick printed summary of results is produced.

Estimate profile-likelihood confidence intervals

Once parameters are estimated, confidence inetrvals are estimated by invoking xxmCI() . Depending on the the number of observations and the complexity of the dependence structure xxmCI() may take very long. xxMCI() displays a table of parameter estimates and CIS.

View results

A summary of results may be retrived as an R list by a call to xxmSummary()

Free moodel object

xxM model object may hog a large amount of RAM outside of R's memory. This memory will automatically be released, when R's workspace is cleared by a call to rm(list=ls()) or at the end of the R session. Alternatively, xxmFree() may be called to release memory.

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