# Testing the format of the list for content balancing under dichotomous or polytomous IRT models This command tests whether format of the list to be assigned to `cbControl` argument of function `nextItem` is appropriate for content balancing, and returns a warning message otherwise. ```r test.cbList(list, cbGroup) ``` ## Arguments - `list`: a list of arguments to be tested. See Details . - `cbGroup`: a vector of character or factor names of the subgroups of items in the bank, or `NULL`. ## Returns A list with two arguments: - **test**: a logical value indicating whether the format of the list is accurate (`TRUE`) or not (`FALSE`). - **message**: either a message to indicate the type of misspecification, or `"ok"` if the format is accurate. ## Details The `test.cbList` function checks whether the list provided in the `cbControl` argument of the `nextItem` and `randomCAT` functions, is accurate for controlling for content balancing. It mainly serves as an initial check for the `randomCAT` function. The function returns an `"ok"` message if the arguments of `list` match the requirement of the list `cbControl` for content balancing. Otherwise, a message is returned with information about list - type mismatch. This will be the case if: * `list` is not a list or has not exactly two elements, * at least one of the argument names is incorrect, * the lengths of the arguments are different, or different from the number of subgroups of items, * the 'names' element does not match with the subgroups' names, * the 'props' element is not numeric or holds negative values. Each mismatch yields a different output message to help in debugging the problem. ## References Magis, D. and Barrada, J. R. (2017). Computerized Adaptive Testing with R: Recent Updates of the Package **catR**. **Journal of Statistical Software**, **Code Snippets**, **76(1)**, 1-18. tools:::Rd_expr_doi("10.18637/jss.v076.c01") Magis, D., and Raiche, G. (2012). Random Generation of Response Patterns under Computerized Adaptive Testing with the R Package **catR**. **Journal of Statistical Software**, **48 (8)**, 1-31. tools:::Rd_expr_doi("10.18637/jss.v048.i08") ## Author(s) David Magis Department of Psychology, University of Liege, Belgium david.magis@uliege.be ## See Also `nextItem`, `randomCAT` ## Examples ```r ## Dichotomous models ## # Loading the 'tcals' parameters data(tcals) # Vector of group membership for 'tcals' data set group <- tcals$Group # Creation of a correct list with arbitrary proportions cbList <- list(names = c("Audio1", "Audio2", "Written1", "Written2", "Written3"), props = c(0.1, 0.2, 0.2, 0.2, 0.3)) # Testing 'cbList' test.cbList(cbList, group) # Creation of an incorrect list (mismatch in first name) cbList <- list(names = c("audio1", "Audio2", "Written1", "Written2", "Written3"), props=c(0.1, 0.2, 0.2, 0.2, 0.3)) test.cbList(cbList, group) # Creation of an incorrect list (mismatch in name of second # element) cbList <- list(names = c("Audio1", "Audio2", "Written1", "Written2", "Written3"), prop = c(0.1, 0.2, 0.2, 0.2, 0.3)) test.cbList(cbList, group) # Creation of an incorrect list (second element shorter than # first element) cbList <- list(names = c("Audio1", "Audio2", "Written1", "Written2", "Written3"), props=c(0.1, 0.2, 0.2, 0.2)) test.cbList(cbList, group) # Creation of an incorrect list (adding a third element) cbList <- list(names = c("Audio1", "Audio2", "Written1", "Written2", "Written3"), props = c(0.1, 0.2, 0.2, 0.2), third = "hi") test.cbList(cbList, group) ## Polytomous models ## # Creation of an appropriate list for content balancing # Equal proprotions across subgroups of items cbList <- list(names = c("Group1", "Group2", "Group3", "Group4"), props = rep(1, 4)) # Creation of a "wrong" list cbList2 <- list(names=c("group1","group2"),props = c(1, 1)) # Generation of an item bank under GRM with 100 items and at most 4 categories m.GRM <- genPolyMatrix(100, 4, "GRM", cbControl = cbList) # Breaking the 'm.GRM' bank bank <- breakBank(m.GRM) # Testing 'cbList' and 'cbList2' test.cbList(cbList, bank$cbGroup) test.cbList(cbList2, bank$cbGroup) # Generation of an item bank under PCM with 100 items, 4 categories and groups m.PCM <- genPolyMatrix(100, 4, "PCM", same.nrCat = TRUE, cbControl = cbList2) # Breaking the 'm.PCM' bank bank2 <- breakBank(m.PCM) # Testing 'cbList' and 'cbList2' test.cbList(cbList, bank2$cbGroup) test.cbList(cbList2, bank2$cbGroup) ```

test.cbList function