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1 parent b1bf287 commit 263e4cddc010ed772fe745de777232517589136a @philchalmers committed Dec 31, 2012
Showing with 58 additions and 51 deletions.
  1. +5 −5 DESCRIPTION
  2. +53 −46 README.md
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@@ -1,5 +1,5 @@
Package: mirt
-Version: 0.4.2-2
+Version: 0.4.2-3
Date: 2012-10-19
Type: Package
Title: Multidimensional Item Response Theory
@@ -9,10 +9,10 @@ Authors@R: c(
Description: Analysis of dichotomous and polytomous response data using latent
trait models under the Item Response Theory paradigm. Includes univariate
and multivariate one-, two-, three-, and four-parameter logistic models,
- graded response models, rating scale graded response models, generalized
- partial credit models, nominal models, multiple choice models, and
- multivariate partially-compensatory models. These can be used in an
- exploratory or confirmatory manner with optional user defined linear
+ graded response models, rating scale graded response models, (generalized)
+ partial credit models, rating scale models, nominal models, multiple choice
+ models, and multivariate partially-compensatory models. Many of these models
+ can be used in an exploratory or confirmatory manner with optional user defined
constraints. Exploratory models can be estimated via quadrature or
stochastic methods, a generalized confirmatory bi-factor analysis is
included, and confirmatory models can be fit with a Metropolis-Hastings
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@@ -1,46 +1,53 @@
-#mirt
-
-Multidimensional item response theory in R.
-
-##Description
-
-Analysis of dichotomous and polytomous response data using latent trait models under the Item
-Response Theory paradigm. Includes univariate and multivariate one-, two-, three-, and
-four-parameter logistic models, graded response models, generalized partial credit models, nominal
-models, multiple choice models, and multivariate partially-compensatory models. These can be used in
-an exploratory or confirmatory manner with optional user defined linear constraints. Exploratory
-models can be estimated via quadrature or stochastic methods, a generalized confirmatory bi-factor
-analysis is included, and confirmatory models can be fit with a Metropolis-Hastings Robbins-Monro
-algorithm which can include polynomial or product constructed latent traits. Additionally, multiple
-group analysis may be performed for unidimensional or multidimensional item response models for
-detecting differential item functioning.
-
-##Installing from source
-
-It's recommended to use the development version of this package since it is more likely to be up to date
-than the version on CRAN. To install this package from source:
-
-1) Obtain recent gcc and g++ compilers. Windows users can install the
- [Rtools](http://cran.r-project.org/bin/windows/Rtools/) suite while Mac users will have to
- download the necessary tools from the [Xcode](https://itunes.apple.com/ca/app/xcode/id497799835?mt=12) suite and its
- related command line tools (found within Xcode's Preference Pane under Downloads/Components); most Linux
- distributions should already have up to date compilers (or if not they can be updated easily).
-
-2) Install the package dependencies (if necessary). In R, paste the following into the console:
-
-```r
-install.packages(c('psych','GPArotation','mvtnorm','Rcpp','numDeriv','devtools'))
-```
-
-3) Load the `devtools` package and install from the github source code.
-
-```r
-library(devtools)
-install_github('mirt','philchalmers')
-```
-
-#Extra
-
-Bug reports are always welcome and the preferred way to address these bugs is through
-the github 'issues'. Feel free to submit issues or feature requests on the site, and I'll
-address them ASAP. Cheers!
+#mirt
+
+Multidimensional item response theory in R.
+
+##Description
+
+Analysis of dichotomous and polytomous response data using latent
+trait models under the Item Response Theory paradigm. Includes univariate
+and multivariate one-, two-, three-, and four-parameter logistic models,
+graded response models, rating scale graded response models, (generalized)
+partial credit models, rating scale models, nominal models, multiple choice
+models, and multivariate partially-compensatory models. Many of these models
+can be used in an exploratory or confirmatory manner with optional user defined
+constraints. Exploratory models can be estimated via quadrature or
+stochastic methods, a generalized confirmatory bi-factor analysis is
+included, and confirmatory models can be fit with a Metropolis-Hastings
+Robbins-Monro algorithm which can include polynomial or product constructed
+latent traits. Additionally, multiple group analysis may be performed for
+unidimensional or multidimensional item response models for detecting
+differential item functioning.
+
+##Installing from source
+
+It's recommended to use the development version of this package since it is more likely to be up to date
+than the version on CRAN. To install this package from source:
+
+1) Obtain recent gcc and g++ compilers. Windows users can install the
+ [Rtools](http://cran.r-project.org/bin/windows/Rtools/) suite while Mac users will have to
+ download the necessary tools from the [Xcode](https://itunes.apple.com/ca/app/xcode/id497799835?mt=12) suite and its
+ related command line tools (found within Xcode's Preference Pane under Downloads/Components); most Linux
+ distributions should already have up to date compilers (or if not they can be updated easily).
+
+2) Install the `devtools` (if necessary). In R, paste the following into the console:
+
+```r
+install.packages('devtools')
+```
+
+3) Load the `devtools` package and install from the github source code.
+
+```r
+library('devtools')
+install_github('mirt', 'philchalmers', quick = TRUE)
+```
+
+If the install fails because an appropriate `pdflatex` compiler is missing install the developement
+version devtools (`devtools::install_github('devtools', 'wch')`) and re-run the above install chunk.
+
+#Extra
+
+Bug reports are always welcome and the preferred way to address these bugs is through
+the github 'issues'. Feel free to submit issues or feature requests on the site, and I'll
+address them ASAP. Cheers!

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