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Roll CRAN release 1.3.1 (#6)
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* Re-generate documentation...

* Change order...

* Avoid building vignettes...

* Bump news [skip-ci]

* Missed the build args...

* Fix spelling errors
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coatless authored Mar 22, 2020
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11 changes: 6 additions & 5 deletions DESCRIPTION
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Package: cIRT
Type: Package
Title: Choice Item Response Theory
Version: 1.3.0.900
Version: 1.3.1
Authors@R: c(
person("Steven Andrew", "Culpepper",
email = "sculpepp@illinois.edu",
Expand All @@ -15,7 +15,7 @@ Authors@R: c(
)
)
Description: Jointly model the accuracy of cognitive responses and item choices
within a bayesian hierarchical framework as described by Culpepper and
within a Bayesian hierarchical framework as described by Culpepper and
Balamuta (2015) <doi:10.1007/s11336-015-9484-7>. In addition, the package
contains the datasets used within the analysis of the paper.
License: GPL (>= 2)
Expand All @@ -29,8 +29,9 @@ Suggests:
knitr,
rmarkdown,
covr
VignetteBuilder: knitr
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.1
Language: en-US
VignetteBuilder: knitr
RoxygenNote: 7.1.0
Roxygen: list(markdown = TRUE)
LazyData: true
4 changes: 2 additions & 2 deletions NEWS.md
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# cIRT 1.3.0.900
# cIRT 1.3.1

## Changes

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# cIRT 1.0.0

## Modeling Framework
- Implementation of the hiercharical framework described in "A Hierarchical Model for Accuracy and Choice on Standardized Tests"
- Implementation of the hierarchical framework described in "A Hierarchical Model for Accuracy and Choice on Standardized Tests"
- Specifically, a choice inclusive Probit HLM and a Two Parameter Ogive Model.

## C++ Functions
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4 changes: 2 additions & 2 deletions R/RcppExports.R
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Expand Up @@ -130,9 +130,9 @@ TwoPLChoicemcmc <- function(unique_subject_ids, subject_ids, choices_nk, fixed_e
.Call(`_cIRT_TwoPLChoicemcmc`, unique_subject_ids, subject_ids, choices_nk, fixed_effects, B, rv_effects_design, gamma, beta, zeta_rv, Sigma_zeta_inv, Y, theta0, a0, b0, mu_xi0, Sig_xi0)
}

#' Probit Hierarchial Level Model
#' Probit Hierarchical Level Model
#'
#' Performs modeling procedure for a Probit Hierarchial Level Model.
#' Performs modeling procedure for a Probit Hierarchical Level Model.
#'
#' @param unique_subject_ids A `vector` with length N x 1 containing
#' unique subject IDs.
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2 changes: 1 addition & 1 deletion README.Rmd
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<!-- badges: end -->

Jointly model the accuracy of cognitive responses and item choices
within a bayesian hierarchical framework as described by Culpepper and
within a Bayesian hierarchical framework as described by Culpepper and
Balamuta (2015) <doi:10.1007/s11336-015-9484-7>.

## Installation
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2 changes: 1 addition & 1 deletion README.md
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Expand Up @@ -19,7 +19,7 @@ Downloads](http://cranlogs.r-pkg.org/badges/grand-total/cIRT?color=brightgreen)]
<!-- badges: end -->

Jointly model the accuracy of cognitive responses and item choices
within a bayesian hierarchical framework as described by Culpepper and
within a Bayesian hierarchical framework as described by Culpepper and
Balamuta (2015) <doi:10.1007/s11336-015-9484-7>.

## Installation
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4 changes: 3 additions & 1 deletion cIRT.Rproj
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Expand Up @@ -14,5 +14,7 @@ LaTeX: pdfLaTeX

BuildType: Package
PackageUseDevtools: Yes
PackageInstallArgs: --no-multiarch --with-keep.source
PackageInstallArgs: --no-multiarch --with-keep.source --no-build-vignettes
PackageBuildArgs: --no-build-vignettes
PackageCheckArgs: --no-build-vignettes
PackageRoxygenize: rd,collate,namespace
16 changes: 14 additions & 2 deletions man/Generate_Choice.Rd

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21 changes: 18 additions & 3 deletions man/TwoPLChoicemcmc.Rd

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6 changes: 3 additions & 3 deletions man/cIRT-package.Rd

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12 changes: 10 additions & 2 deletions man/cIRT.Rd

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6 changes: 4 additions & 2 deletions man/choice_matrix.Rd

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6 changes: 4 additions & 2 deletions man/payout_matrix.Rd

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31 changes: 24 additions & 7 deletions man/probitHLM.Rd

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6 changes: 4 additions & 2 deletions man/survey_data.Rd

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6 changes: 4 additions & 2 deletions man/trial_matrix.Rd

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4 changes: 2 additions & 2 deletions src/project_source.cpp
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Expand Up @@ -305,9 +305,9 @@ Rcpp::List TwoPLChoicemcmc(/* New Parameters */
Rcpp::Named("Wzeta_0", Wzeta_0));
}

//' Probit Hierarchial Level Model
//' Probit Hierarchical Level Model
//'
//' Performs modeling procedure for a Probit Hierarchial Level Model.
//' Performs modeling procedure for a Probit Hierarchical Level Model.
//'
//' @param unique_subject_ids A `vector` with length N x 1 containing
//' unique subject IDs.
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2 changes: 1 addition & 1 deletion vignettes/Estimating-the-Model-in-the-Paper.Rmd
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Expand Up @@ -17,7 +17,7 @@ each section in the example displayed in `cIRT()` function.
# Data

Within this vignette, we used two different data sets to generate a Choice
Item Response Theory Model with the rountine located in `cIRT`.
Item Response Theory Model with the routine located in `cIRT`.

```{r load_pkg}
library(cIRT)
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4 changes: 2 additions & 2 deletions vignettes/Package-Overview.Rmd
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# Intro

The package is a companion to the paper A hierarchical model for accuracy and choice on standardized tests in [Psychometrika](http://link.springer.com/article/10.1007/s11336-015-9484-7) written by Culpepper, S. A. & Balamuta, J. J. Within this package, we make available the code used for the analysis within the paper as well as the data.
The package is a companion to the paper "A hierarchical model for accuracy and choice on standardized tests" in [Psychometrika](http://link.springer.com/article/10.1007/s11336-015-9484-7) written by Culpepper, S. A. & Balamuta, J. J. Within this package, we make available the code used for the analysis within the paper as well as the data.

# Functions

The package provides C++ implementations of the hierarchial bayesian modeling framework for choice. The primary functions that are novel contributions to psychometric literature are the `probitHLM()` and `TwoPLChoicemcmc()` that respectively provide a choice inclusive Probit HLM and a Two Parameter Ogive Model and are called by an overall wrapper function `cIRT()`. These functions do have an overall dependency on other components that have also been coded within C++ and may benefit a practitioner seeking to do use the same functionality elsewhere.
The package provides C++ implementations of the hierarchical bayesian modeling framework for choice. The primary functions that are novel contributions to psychometric literature are the `probitHLM()` and `TwoPLChoicemcmc()` that respectively provide a choice inclusive Probit HLM and a Two Parameter Ogive Model and are called by an overall wrapper function `cIRT()`. These functions do have an overall dependency on other components that have also been coded within C++ and may benefit a practitioner seeking to do use the same functionality elsewhere.

* Random Number Generation for the following distributions: Wishart `rwishart()`, Inverse Wishart `riwishart()`, and Multivariate Normal `rmvnorm()`.
* Matrix Centering `center_matrix()`
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2 changes: 1 addition & 1 deletion vignettes/Simulation-Study-with-cIRT.Rmd
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Expand Up @@ -14,7 +14,7 @@ The document addresses the simulation study that was performed to understand whe

# Simulation

The simulation study below is configured to generate results one might obtain from a pool of 1,000 subjects taking a 20 item test. We obtain summarize the results obtained from running the model 100 times over slightly differring $\theta$ and $\eta$.
The simulation study below is configured to generate results one might obtain from a pool of 1,000 subjects taking a 20 item test. We obtain summarize the results obtained from running the model 100 times over slightly differing $\theta$ and $\eta$.

```{r sim_setup, eval = F}
### Variables
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