parallized_tests: conducts and controls the parallelisation of the tests,...

In exhaustiveRasch: Item Selection and Exhaustive Search for Rasch Models

conducts and controls the parallelisation of the tests, Intentionally, there are no defauklt values for the parameters, as this internal function is called by exhaustive_tests that also defines the default values for this function.

Description

conducts and controls the parallelisation of the tests, Intentionally, there are no defauklt values for the parameters, as this internal function is called by exhaustive_tests that also defines the default values for this function.

Usage

parallized_tests(
  dset,
  modelType,
  combos,
  models,
  p.par,
  na.rm,
  testfunction,
  itemfit_param,
  splitcr = NULL,
  icat_wald,
  alpha,
  bonf,
  DIFvars,
  gap_prop,
  max_contrast,
  PSI,
  extremes,
  ignoreCores,
  estimation_param,
  tests_count,
  verbose = TRUE,
  ...
)

Arguments

dset	a data.frame containing the data
modelType	a character value defining the rasch model to fit. Possible values: RM, PCM, RSM
combos	either 1) a list of item combinations to be tested, e.g. from apply_combo_rules or the passed_combos slot of an object of passed_exRa-class from a previous call to this function. Or 2) an object of passed_exRa-class. In this case, the previously fit models froms its passed_Models slot will also be used and will be passed to the test functions. This will speed up the analysis. If the parameter is NULL, all possible combinations of the items (columns) in dset will be tested
na.rm	a boolean value. If TRUE, in the respective item combination all cases with any NA are removed (na.omit). If FALSE, only cases with full NA responses are removed. NOTE: test_mloef currently does not allow for missing values (because erm::MLoef doesn't). If test_mloef is under the tests to perform, na.rm will automatically be set TRUE for ALL tests.
testfunction	a character defining the actual test (the internal testfunction) to perform. Possible values: all_rawscores, test_itemfit, test_LR, test_mloef, test_waldtest, threshold_order, test_DIFtree, test_personsItems, test_respca.
itemfit_param	a list from itemfit_control with options for test_itemfit
splitcr	the split criterion to use, if the actual testfunction is test_LR or test_waldtest.Split criterion for subject raw score splitting. "all.r" corresponds to a full raw score split, "median" uses the median as split criterion, "mean" performs a mean split. Optionally splitcr can also be a vector which assigns each person to a certain subgroup (e.g., following an external criterion). This vector can be numeric, character or a factor.
icat_wald	a boolean value indicating if the waldtest will be conducted on item level (TRUE, default value) or on item category level. This parameter only effects estimations using psychotools or pairwise and will be ignored for eRm estimations.
alpha	a numeric value for the alpha level. Will be ignored for test_itemfit if use.pval in itemfit_control is FALSE
bonf	a boolean value wheter to use a Bonferroni correction. Will be ignored if use.pval is FALSE
DIFvars	a data.frame containing the variables and their data to use for differential item functioning analysis with test_DIFtree
gap_prop	a numeric value between 0 and 1 that sets the criterion for the minimum proportion of neighboring person parameters with an item/threshold location in between. If set to 0, this criterion will not be checked (used in test_personsItems only)
max_contrast	a numeric value defining the maximum loading of a factor in the principal components analysis of the standardised residuals. Only relevant, if test_respca is one of the tests.
extremes	a boolean value indicating if a check for the item/threshold locations left of the 2nd lowest and right of the 2nd highest person parameter (used in test_personsItems only).
ignoreCores	a numeric value for the number of cpu cores to hold out in parallelizing the test run.
estimation_param	options for parameter estimation using estimation_control
verbose	a boolean value. If set to FALSE, all output during the analysis will be suppressed.
...	options for itemfit_control can be passed directly to this function.

Value

a list containing 3 elements is returned: a list of the item combinations, a list of the models (depending on modelType and estimation_param$est) with the fit models and a list with the person parameter objects (depending on estimation_param$est).

exhaustiveRasch documentation built on April 3, 2025, 6:18 p.m.