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Package: Greg
Version: 1.2
Date: 2016-03-28
Title: Regression Helper Functions
Maintainer: Max Gordon <max@gforge.se>
Authors@R: c(person("Max", "Gordon", email = "max@gforge.se", role = c("aut", "cre")),
person("Reinhard", "Seifert", role = "aut", comment = "Author of original plotHR"))
Description: Methods for manipulating regression models and for describing these in a style adapted for medical journals.
Contains functions for generating an HTML table with crude and adjusted estimates, plotting hazard ratio, plotting model
estimates and confidence intervals using forest plots, extending this to comparing multiple models in a single forest plots.
In addition to the descriptives methods, there are addons for the robust covariance matrix provided by the sandwich
package, a function for adding non-linearities to a model, and a wrapper around the Epi package's Lexis functions for
time-spliting a dataset when modeling non-proportional hazards in Cox regressions.
License: GPL (>= 3)
URL: http://gforge.se
Biarch: yes
Imports: Hmisc, stringr, rms, sandwich, stats, nlme, methods,
htmlTable, magrittr, knitr, Epi, utils, graphics, grDevices
Depends: forestplot, Gmisc (>= 1.0.3)
Suggests: boot, testthat, cmprsk, survival, dplyr, ggplot2
VignetteBuilder: knitr
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2016-03-28 19:20:50 UTC; max
Author: Max Gordon [aut, cre],
Reinhard Seifert [aut] (Author of original plotHR)
Repository: CRAN
Date/Publication: 2016-03-28 23:24:58
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Package: bmeta
Type: Package
Title: Bayesian Meta-Analysis and Meta-Regression
Version: 0.1.2
Date: 2016-01-08
Author: Tao Ding, Gianluca Baio
Maintainer: Gianluca Baio <gianluca@stats.ucl.ac.uk>
Depends: R2jags, forestplot
Description: Provides a collection of functions for conducting meta-analyses under Bayesian context in R. The package includes functions for computing various effect size or outcome measures (e.g. odds ratios, mean difference and incidence rate ratio) for different types of data based on MCMC simulations. Users are allowed to fit fixed- and random-effects models with different priors to the data. Meta-regression can be carried out if effects of additional covariates are observed. Furthermore, the package provides functions for creating posterior distribution plots and forest plot to display main model output. Traceplots and some other diagnostic plots are also available for assessing model fit and performance.
License: GPL (>= 2)
URL: http://www.statistica.it/gianluca/bmeta
http://www.statistica.it/gianluca
NeedsCompilation: no
Packaged: 2016-01-08 09:22:11 UTC; gianluca
Repository: CRAN
Date/Publication: 2016-01-08 10:53:20
● Data Source:
CranContrib
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0 images,
10 functions,
0 datasets
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Reverse Depends: 0
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providing 
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