makeItemList {conquestr}  R Documentation 
creates a list of item matrices.
Each matrix represent one item's set of item parameters. The structure of the
matrix is the same as used in conquestr::simplef
(a matrix of k categories by four (category score, delta dot, tau, discrimination)).
makeItemList(scores = NULL, deltaDot, tau = NULL, discrim = 1)
scores 
a data frame or matrix containing category scores for each item.
If NULL, it is assumed increasing integer scoring starting at 0 is used for all items (that is, the
first category is scored 0, the second category is scored 1, the If a data frame, column labels should be "id", "itemid", "step", "score".
If a matrix, the column order should be: "id", a unique item ID for each item matched with values in If a data frame, or a matrix:

deltaDot 
a data frame or matrix of delta dots (average item location/difficulty for each item). If a data frame, column labels should be: "id", "itemid", "delta". "itemid" should be populated with an item label or be missing for all values. If a matrix, column order should be: "id", a unique item ID for each row; "itemid", item labels for each item (or NA); "delta", a delta dot. If a data frame, or a matrix:

tau 
NULL if all items are dichotomies.
A data frame or matrix of taus for polytomous items. Only polytomous items should be in this file.
If an item ID in Where a polytomous item has k categories, there should be k2 rows for that item in If a data frame, column labels should be "id", "itemid", "step", "tau".
If a matrix, the column order should be: "id", a unique item ID for each item matched with values in If a data frame, or a matrix:

discrim 
a double, a data frame, or a matrix of item (or category) discrimination parameters. When a double is provided, the value is applied to all discrimination parameters. The default is 1. Setting the value to 1.7 is one approach to rescale to the normal ogive metric. Otherwise a data.frame or matrix defining the discrimination parameter for each response category. If a data frame, column labels should be "id", "itemid", "step", "discrim". If step is NA and there is only one entry for an item "itemid", the discrimination is assumed to be constant for all response categories with the item. This is the case for names models like the GPCM and 2PL models, and can be a short hand way of defining the discrimination without specifying all categories. When discrimination varies across scoring categories, the bocknominal model is implied. In the case of discrimination varying across scoring categories, all categories must be defined. If a data frame, or a matrix:

a list.
nItems < 10
myItemsDeltaDot < data.frame(
id= seq(nItems),
itemid= NA,
delta = runif (nItems, 4, 1) # nItems items in range 4,1
)
myItemsList < conquestr::makeItemList(deltaDot = myItemsDeltaDot)