Packaged: 2017-06-16 16:33:26 UTC; erinrossiter

Imports: methods, stats, Rcpp(>= 0.12.11), RcppParallel,
Packaged: 2017-06-26 20:54:40 UTC; erinrossiter

Packaged: 2017-07-05 19:06:24 UTC; erinrossiter

Description: Provides methods of computerized adaptive testing for survey researchers.  See Montgomery and Rossiter (2019) <doi:10.1093/jssam/smz027>. Includes functionality for data fit with the classic item response methods including the latent trait model, Birnbaum`s three parameter model, the graded response, and the generalized partial credit model.  Additionally, includes several ability parameter estimation and item selection routines.  During item selection, all calculations are done in compiled C++ code.
Imports: jsonlite, methods, stats, plyr, Rcpp(>= 1.0.1), RcppParallel,
LinkingTo: BH(>= 1.69.0.1), Rcpp(>= 1.0.1), RcppArmadillo, RcppGSL(>=
Packaged: 2019-11-18 16:36:44 UTC; erinrossiter

Packaged: 2019-12-09 20:48:11 UTC; erinrossiter

Packaged: 2020-10-06 19:57:22 UTC; erinrossiter

Authors@R: c(person("Jacob", "Montgomery", email =  "jacob.montgomery@wustl.edu", role = "aut"), person("Erin", "Rossiter", email = "erossite@nd.edu", role = c("aut", "cre")))
Description: Provides methods of computerized adaptive testing for survey researchers.  See Montgomery and Rossiter (2020) <doi:10.1093/jssam/smz027>. Includes functionality for data fit with the classic item response methods including the latent trait model, Birnbaum`s three parameter model, the graded response, and the generalized partial credit model.  Additionally, includes several ability parameter estimation and item selection routines.  During item selection, all calculations are done in compiled C++ code.

Title: Analysis of Check-All-that-Apply (CATA) Data
Author: J.C. Castura [aut, cre, ctb] (<https://orcid.org/0000-0002-1640-833X>)
Description: Functions for analyzing check-all-that-apply (CATA) data from consumer and sensory tests. Cochran's Q test, McNemar's test, and Penalty-Lift analysis provided, as described in for CATA data analysis by Meyners, Castura & Carr (2013) <doi:10.1016/j.foodqual.2013.06.010>. Cluster analysis can be performed using b-cluster analysis. The quality of cluster analysis solutions can be evaluated using various measures. The methods related to b-cluster analysis are described in a pre-print manuscript by Castura, Meyners, Varela & Naes (2021) <https://secure.compusense.com/research/wp-content/uploads/2021/12/Castura_bcluster_submitted_20211130.pdf>.