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Last data update: 2014.03.03

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merTools : Tools for Analyzing Mixed Effect Regression Models

Package: merTools
Title: Tools for Analyzing Mixed Effect Regression Models
Version: 0.2.1
Authors@R: c(person(c("Jared", "E."), "Knowles", email = "jknowles@gmail.com",
role = c("aut", "cre")), person("Carl", "Frederick", email="carlbfrederick@gmail.com",
role = c("aut")))
Description: Provides methods for extracting results from mixed-effect model
objects fit with the 'lme4' package. Allows construction of prediction intervals
efficiently from large scale linear and generalized linear mixed-effects models.
Depends: R (>= 3.0.2), arm, lme4 (>= 1.1-11), methods, plyr
Suggests: testthat, knitr, rmarkdown, dplyr, foreach, parallel
Imports: mvtnorm, DT, shiny, abind, ggplot2, blme, broom
License: GPL (>= 2)
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 5.0.1
BugReports: https://www.github.com/jknowles/merTools
NeedsCompilation: no
Packaged: 2016-03-30 14:53:24 UTC; KNOWLJE
Author: Jared E. Knowles [aut, cre],
Carl Frederick [aut]
Maintainer: Jared E. Knowles <jknowles@gmail.com>
Repository: CRAN
Date/Publication: 2016-03-30 20:35:22

● Data Source: CranContrib
● 0 images, 43 functions, 1 datasets
● Reverse Depends: 0

interplot : Plot the Effects of Variables in Interaction Terms

Package: interplot
Title: Plot the Effects of Variables in Interaction Terms
Version: 0.1.2.1
Author: Frederick Solt <frederick-solt@uiowa.edu>, Yue Hu <yue-hu-1@uiowa.edu>
Maintainer: Yue Hu <yue-hu-1@uiowa.edu>
Description: Plots the conditional coefficients ("marginal effects") of
variables included in multiplicative interaction terms.
Depends: R (>= 3.1.1), ggplot2, abind, arm
Imports: stats
License: MIT + file LICENSE
LazyData: true
Suggests: knitr
VignetteBuilder: knitr
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-03-24 13:37:11 UTC; Sammo
Repository: CRAN
Date/Publication: 2016-03-24 23:54:35

● Data Source: CranContrib
● 0 images, 6 functions, 0 datasets
● Reverse Depends: 0

wfe : Weighted Linear Fixed Effects Regression Models for Causal Inference

Package: wfe
Version: 1.3
Date: 2014-08-09
Title: Weighted Linear Fixed Effects Regression Models for Causal
Inference
Author: In Song Kim <insong@mit.edu>, Kosuke Imai <kimai@Princeton.edu>
Maintainer: In Song Kim <insong@mit.edu>
Depends: R (>= 2.11.0), utils, arm (>= 1.4-6), Matrix, MASS
Description: This R package provides a computationally efficient way
of fitting weighted linear fixed effects estimators for
causal inference with various weighting schemes. Imai
and Kim (2012) show that weighted linear fixed effects
estimators can be used to estimate the average treatment
effects under different identification strategies. This
includes stratified randomized experiments, matching and
stratification for observational studies, first
differencing, and difference-in-differences. The package
also provides various robust standard errors and a
specification test for standard linear fixed effects
estimators.
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)
Packaged: 2014-08-11 00:00:20 UTC; insong
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2014-08-11 05:56:52

● Data Source: CranContrib
● 0 images, 2 functions, 0 datasets
● Reverse Depends: 0