simulateThetas {catSurv}

Estimates theta under different adaptive battery specifications

Description

Takes in response profiles from multiple respondents and multiple Cat object (i.e., adaptive battery) specifications and returns a set of theta estimates

Usage

simulateThetas(catObjs = list(), responses, return_adaptive = FALSE)

Arguments

catObjs

A list of Cat objects of the same model with different adaptive battery specifications

responses

A matrix of response profiles

return_adaptive

Boolean indicating if user wants dataframe containing only answers chosen via the adaptive design for each Cat object in catObjs list.

Details

The function takes multiple Cat objects, stored in a list, and generates an estimation for theta.

Value

The function simulateThetas returns a dataframe where each Cat object corresponds to a column and each respondent corresponds to a row if return_adaptive is FALSE, the default. Optionally, simulateThetas returns a list containing that dataframe plus dataframes for the answer profiles simulated via each adaptive design if return_adaptive is TRUE.

Author(s)

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

See Also

Cat-class, apply, selectItem

Examples

# 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(cat1 = grm_MAP, cat2 = grm_EAP)

# Results
theta_est_results <- simulateThetas(catObjs = grmList, responses = respondents)