mxExpectationBA81 {OpenMx} | R Documentation |
When a two-tier covariance matrix is recognized, this expectation automatically enables analytic dimension reduction (Cai, 2010).
mxExpectationBA81(ItemSpec, item = "item", ..., qpoints = 49L, qwidth = 6, mean = "mean", cov = "cov", verbose = 0L, weightColumn = NA_integer_, EstepItem = NULL, debugInternal = FALSE)
ItemSpec |
a single item model (to replicate) or a list of
item models in the same order as the column of |
item |
the name of the mxMatrix holding item parameters with one column for each item model with parameters starting at row 1 and extra rows filled with NA |
... |
Not used. Forces remaining arguments to be specified by name. |
qpoints |
number of points to use for equal interval quadrature integration (default 49L) |
qwidth |
the width of the quadrature as a positive Z score (default 6.0) |
mean |
the name of the mxMatrix holding the mean vector |
cov |
the name of the mxMatrix holding the covariance matrix |
verbose |
the level of runtime diagnostics (default 0L) |
weightColumn |
the name of the column in the data containing the row weights (default NA) |
EstepItem |
a simple matrix of item parameters for the E-step. This option is mainly of use for debugging derivatives. |
debugInternal |
when enabled, some of the internal tables are returned in $debug. This is mainly of use to developers. |
The standard Normal distribution of the quadrature acts like a prior distribution for difficulty. It is not necessary to impose any additional Bayesian prior on difficulty estimates (Baker & Kim, 2004, p. 196).
Bock, R. D., & Aitkin, M. (1981). Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm. Psychometrika, 46, 443-459.
Cai, L. (2010). A two-tier full-information item factor analysis model with applications. Psychometrika, 75, 581-612.
Seong, T. J. (1990). Sensitivity of marginal maximum likelihood estimation of item and ability parameters to the characteristics of the prior ability distributions. Applied Psychological Measurement, 14(3), 299-311.