R Development Page
Contributed R Packages
Below is a list of all packages provided by project Structural equation modeling.
Important note for package
binaries: R-Forge provides these binaries only for
the most recent version of R, but not for older
versions. In order to successfully install the
packages provided on R-Forge, you have to switch
to the most recent version of R or, alternatively,
install from the package sources (.tar.gz).
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RAMpath | Structural Equation Modeling using the reticular action model (RAM) Notation
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RAMpath is a rewrite of RAMpath software developed by John
McArdle and Steven Boker. However, it does more than the
original software by providing flexible fit of growth curve
models, univariate and bivariate latent change score models. It
can also generate the vector field plot for the bivariate
latent change score models. |
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Version: 0.3.6 |
Last change: 2013-06-28 21:37:06+02 |
Rev.: 104 |
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Download:
 (.tar.gz) |
 (.zip) |
Build status: Current | Stable Release: Get RAMpath 0.5.1 from CRAN |
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R install command:
install.packages("RAMpath", repos="http://R-Forge.R-project.org") |
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autocorr | Testing Autocorrelation through bootstrap and surrogate methods
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Different methods for testing autocorrelation are implemented. Two asymptotic methods including the 1/T approximation method and the Bartletts formula method are implemented. Two resampling techniques including the moving block bootstrap and the surrogate data method are also provided. |
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Version: 0.1 |
Last change: 2015-10-18 20:57:38+02 |
Rev.: 108 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current |
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R install command:
install.packages("autocorr", repos="http://R-Forge.R-project.org") |
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bmem | Mediation analysis with missing data using bootstrap
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Four methods for mediation analysis with missing data: Listwise deletion, Pairwise deletion, Multiple imputation, and Two Stage Maximum Likelihood algorithm. For MI and TS-ML, auxiliary variables can be included. Bootstrap confidence intervals for mediation effects are obtained. The robust method is also implemented for TS-ML. Since version 1.4, bmem adds the capability to conduct power analysis for mediation models. |
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Version: 1.4 |
Last change: 2013-06-28 21:37:49+02 |
Rev.: 105 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get bmem 2.1 from CRAN |
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R install command:
install.packages("bmem", repos="http://R-Forge.R-project.org") |
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coefficientalpha | Robust Cronbachs alpha with missing and non-normal data
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Cronbachs alpha is one of the most widely used reliability or internal consistency measures in social, behavioral and education sciences. Alpha is reported in nearly every study that involves measuring a construct through multiple test items. The package coefficientalpha calculates Cronbachs coefficient alpha with missing data and non-normal data. Robust standard error and confidence interval are also provided. |
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Version: 0.2.6 |
Last change: 2013-04-22 22:53:25+02 |
Rev.: 85 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get coefficientalpha 0.7.2 from CRAN |
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R install command:
install.packages("coefficientalpha", repos="http://R-Forge.R-project.org") |
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gcmdiag | Growth curve modeling diagnostics
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This is a package for outlier and leverage observation diagnostics for growth curve modeling. |
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Version: 1.0 |
Last change: 2015-12-15 17:39:31+01 |
Rev.: 110 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current |
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R install command:
install.packages("gcmdiag", repos="http://R-Forge.R-project.org") |
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logistic4p | Logistic Regression with Misclassification in Dependent Variables
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Error in a binary dependent variable, also known as misclassification, has not drawn much attention in psychology. Ignoring misclassification in logistic regression can result in misleading parameter estimates and statistical inference. This package conducts logistic regression analysis with misspecification in outcome variables. |
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Version: 1.4 |
Last change: 2016-05-16 22:22:19+02 |
Rev.: 120 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get logistic4p 1.6 from CRAN |
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R install command:
install.packages("logistic4p", repos="http://R-Forge.R-project.org") |
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pautocorr | Testing Autocorrelation and Partial Autocorrelation Through Bootstrap and Surrogate Methods
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Different methods for testing autocorrelation and partial autocorrelation are implemented. Two asymptotic methods including the 1/T approximation method and the Bartletts formula method are implemented. Two resampling techniques including the moving block bootstrap and the surrogate data method are also provided. |
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Version: 0.5 |
Last change: 2016-12-02 21:12:40+01 |
Rev.: 129 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current |
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R install command:
install.packages("pautocorr", repos="http://R-Forge.R-project.org") |
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rpkgstats | R package usage statistics
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Usage statistics about a package can help its developers, and ultimately its users, in many ways. However, such information is rarely available. This package is developed to better collect and utilize package usage statistics. The package allow users to share download information, rate, comment, and ask questions on a package within R directly. The packages sends the information to the package developer directly and also allows other users to respond to it through email. |
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Version: 0.11 |
Last change: 2013-06-28 21:31:04+02 |
Rev.: 103 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current |
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R install command:
install.packages("rpkgstats", repos="http://R-Forge.R-project.org") |
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rsem | Robust Structural Equation Modeling with Missing Data and Auxiliary Variables
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This package estimates means and covariance matrix of multiple variables with missing data using Huber weight and then estimates a SEM model using lavaan or EQS. |
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Version: 0.4.4 |
Last change: 2012-09-27 19:06:32+02 |
Rev.: 22 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get rsem 0.5.1 from CRAN |
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R install command:
install.packages("rsem", repos="http://R-Forge.R-project.org") |
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semdiag | Structural equation modeling diagnostics
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Outlier and leverage diagnostics for SEM. |
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Version: 0.1 |
Last change: 2011-10-03 18:25:18+02 |
Rev.: 3 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Current | Stable Release: Get semdiag 0.1.2 from CRAN |
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R install command:
install.packages("semdiag", repos="http://R-Forge.R-project.org") |
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webpower | Statistical Power Analysis (One Line)
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This is a collection of tools for conducting statistical power analysis. WebPower can be used by anyone for free. To use the software, install the R package webpower or visit webpower.psychstat.org. The development of WebPower is supported by a grant from the Department of Education (R305D140037). However, the contents of WebPower do not necessarily represent the policy of the Department of Education, and you should not assume endorsement by the Federal Government. |
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Version: 0.0.0.9000 |
Last change: 2017-07-20 15:14:33+02 |
Rev.: 130 |
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Download:
(.tar.gz) |
(.zip) |
Build status: Failed to build |
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R install command:
install.packages("webpower", repos="http://R-Forge.R-project.org") |
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Build status codes
0 - Current: the package is available for download. The corresponding package passed checks on the Linux and Windows platform without ERRORs.
1 - Scheduled for build: the package has been recognized by the build system and provided in the staging area.
2 - Building: the package has been sent to the build machines. It will be built and checked using the latest patched version of R. Note that it is included in a batch of several packages. Thus, this process will take some time to finish.
3 - Failed to build: the package failed to build or did not pass the checks on the Linux and/or Windows platform. It is not made available since it does not meet the policies.
4 - Conflicts: two or more packages of the same name exist. None of them will be built. Maintainers are asked to negotiate further actions.
5 - Offline: the package is not available. The build system may be offline or the package maintainer did not trigger a rebuild (done e.g., via committing to the package repository).
If your package is not shown on this page or not building, then check the build system status report.
