Authors@R: person("Abhishek", "Sinha", email = "abhishek.sparta@gmail.com", role = c("aut", "cre"))
Description: Can be used to query data from data from Microsoft SQL Server (MSSQL, see <http://www.microsoft.com/sqlserver/> for more information). Based on the concepts of Entity Framework, the package allows querying data from MSSQL Database.

Title: A Collection of DIF Tests for Multistage Tests
Authors@R: c(person(given = "Rudolf", family = "Debelak", role = c("aut", "cre"), email = "rudolf.debelak@gmail.com"),
person(given = "Dries", family = "Debeer", role = c("aut"), email = "debeer.dries@gmail.com"),
person(given = "Sebastian", family = "Appelbaum", role = "ctb"),
person(given = "Mark J.", family = "Gierl", role = "ctb"))
Imports: expm, Matrix, PP, mirt (>= 1.31), scDIFtest, eRm, strucchange
Suggests: mvtnorm, testthat, knitr, rmarkdown
Description: A collection of statistical tests for the detection of differential
item functioning (DIF) in multistage tests. Methods entail logistic regression,
an adaptation of the simultaneous item bias test (SIBTEST), and various score-based tests.
The presented tests provide itemwise test for DIF along categorical, ordinal or metric covariates. Methods for uniform and non-uniform
DIF effects are available depending on which method is used.

Imports: expm, Matrix, PP, mirt (>= 1.31), scDIFtest, eRm
Suggests: mvtnorm, testthat, knitr, rmarkdown, strucchange

Title: Procedures to Generate Patterns under Multistage Testing
Author: David Magis (U Liege, Belgium), Duanli Yan (ETS, USA), Alina von Davier (ACTNext, USA)
Description: Generation of response patterns under dichotomous and polytomous computerized multistage testing (MST) framework. It holds various IRT- and score-based methods to select the next module and estimate ability levels.

Description: Generation of response patterns under dichotomous and polytomous computerized multistage testing (MST) framework. It holds various item response theory (IRT) and score-based methods to select the next module and estimate ability levels (Magis, Yan and von Davier (2017, ISBN:978-3-319-69218-0)).