Draw plausible values (PVs) from an mml fit
drawPVs(x, npv, pvVariableNameSuffix = "_dire", ...)# S3 method for summary.mmlMeans
drawPVs(x, npv = 5L, pvVariableNameSuffix = "_dire", ...)
# S3 method for mmlMeans
drawPVs(
x,
npv = 5L,
pvVariableNameSuffix = "_dire",
stochasticBeta = FALSE,
normalApprox = TRUE,
newStuDat = NULL,
newStuItems = NULL,
returnPosterior = FALSE,
construct = NULL,
...
)
# S3 method for mmlCompositeMeans
drawPVs(
x,
npv = 5L,
pvVariableNameSuffix = "_dire",
stochasticBeta = FALSE,
normalApprox = TRUE,
newStuDat = NULL,
newStuItems = NULL,
verbose = TRUE,
...
)
when returnPosterior is FALSE returns a object of class DirePV which is a list of two elements.
first, a data frame with a row for every row of newStuDat (or the original stuDat object)
id the value of idVar in the model run
[construct][pvVariableNameSuffix][L] every other column is a plausible value of this format.
The [construct] is the name of the construct,
the [pvVariableNameSuffix] is the value of the pvVariableNameSuffix argument, and
the [L] part is the plausible value index, from 1 to npv.
The second argument is named newpvvars and is a list with an element for each set of construct that lists all of the variables in that construct.
When returnPosterior is TRUE returns list with three elements. One is named posterior and has one
row per idvar level in the newStuDat argument and three columns:
id the value of idVar in the model run
mu the posterior mean
sd the posterior standard deviation
the second list element is named X that is the design matrix for newStuDat (see Value for mml). The third list element is
the rr1 element returned from mml with one column for each individual in newStuDat (see Value in mml).
a fit from a call to mml
integer indicating the number of plausible values to draw
suffix added to new PV variables after construct name and before the plausible value ID. For example, if there is a construct math and the suffix is the default _dire, then the fourth plausible value would have a column name, math_dire4.
additional parameters
logical when TRUE the regression coefficients will be drawn from their posterior distribution. Can also be a data frame of values (see Details).
logical must be TRUE to use the normal approximation to the posterior distribution rather than drawing from the actual posterior distribution.
new stuDat object, (see mml) for which plausible values will be drawn
new stuItems object, (see mml); unlike in mml students with no items can be passed to this function
logical set to TRUE to change output to include two additional data frames (see Value).
character, changes the name of the columns in the final data frame
logical set to TRUE to see the status of the processing
Paul Bailey, Sun-joo Lee, and Eric Buehler
When the argument passed to stocasticBeta is a data frame then each column is an element that will be used as a
regression coefficient for that index of the coefficients vector. The row index used for the nth PV will be the nth row.