View source: R/simulateFisherInfo.R View source: R/simulateFisherInfo.R
simulateFisherInfo | R Documentation |
Takes in a a Cat
object, a set of respondents, and their corresponding theta
values, and calculates the amount of information given an adaptive battery.
simulateFisherInfo(catObjs = list(), theta, responses)
catObjs |
A list of |
theta |
A vector of numerics representing the true value of theta. |
responses |
A dataframe of answer profiles corresponding to the true values of theta. |
The function takes a Cat
object, theta
, and response profiles.
The user defines the selection type, estimation type, etc. so that the questions can be applied adaptively
These adaptive profiles are then used to calculate the total inforamtion gained for a respondent for all answered
items, conditioned on theta
.
The function simulateFisherInfo
returns a dataframe where each Cat
object corresponds to a column and each respondent corresponds to a row.
Haley Acevedo, Ryden Butler, Josh W. Cutler, Matt Malis, Jacob M. Montgomery, Tom Wilkinson, Erin Rossiter, Min Hee Seo, Alex Weil, Jaerin Kim, Dominique Lockett
Cat-class
, fisherTestInfo
, selectItem
# Load Cat object data(grm_cat) # Simulate respondents respondents <- plyr::adply(.data = matrix(c(-1, 0, 1)), .margins = 1, .id = NULL, .fun = simulateRespondents, cat = grm_cat, n = 10) # A stopping rule (here, a common one) is required grm_cat@lengthThreshold <- 3 # Specify different adaptive inventory procedures grm_MAP <- grm_EAP <- grm_cat grm_MAP@estimation <- "MAP" grm_EAP@estimation <- "EAP" # List of Cat objects grmList <- list(grm_MAP, grm_EAP) # Results fisher_inf_results <- simulateFisherInfo(catObjs = grmList, theta = rep(c(-1, 0, 1), each = 10), responses = respondents)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.