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Final tweaks to satisfy R CMD
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graemeleehickey committed Mar 27, 2017
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2 changes: 1 addition & 1 deletion DESCRIPTION
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Expand Up @@ -16,7 +16,7 @@ Authors@R: c(
role = "ctb"),
person("Dimitris", "Rizopoulos", email = "[email protected]",
role = c("ctb", "dtc"),
comment = "R/renal.R, R/hessian.R, R/vcov.R")
comment = "data/renal.rda, R/hessian.R, R/vcov.R")
)
Maintainer: Graeme L. Hickey <[email protected]>
Date: 2017-03-25
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2 changes: 1 addition & 1 deletion NEWS.md
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# joineRML 0.1.1.9000 (devel version).
# joineRML 0.2.0

## New features

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4 changes: 2 additions & 2 deletions README.Rmd
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[![Travis-CI Build Status](https://travis-ci.org/graemeleehickey/joineRML.svg?branch=master)](https://travis-ci.org/graemeleehickey/joineRML)
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[![](http://cranlogs.r-pkg.org/badges/joineRML)](http://cran.rstudio.com/web/packages/joineRML/index.html)
[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/joineRML)](https://CRAN.R-project.org/package=joineRML)
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[![codecov](https://codecov.io/gh/graemeleehickey/joineRML/branch/master/graph/badge.svg)](https://codecov.io/gh/graemeleehickey/joineRML)

`joineRML` is an extension of the joineR package for fitting joint models of time-to-event data and multivariate longitudinal data. The model fitted in joineRML is an extension of the Wulfsohn and Tsiatis (1997) and Henderson et al. (2000) models, which is comprised on $(K+1)$-sub-models: a Cox proportional hazards regression model (Cox, 1972) and a $K$-variate linear mixed-effects model - a direct extension of the Laird and Ware (1982) regression model. The model is fitted using a Monte Carlo Expectation-Maximization (MCEM) algorithm, which closely follows the methodology presented by Lin et al. (2002).
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2 changes: 1 addition & 1 deletion README.md
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joineRML
========

[![Travis-CI Build Status](https://travis-ci.org/graemeleehickey/joineRML.svg?branch=master)](https://travis-ci.org/graemeleehickey/joineRML) [![AppVeyor Build Status](https://ci.appveyor.com/api/projects/status/github/graemeleehickey/joineRML?branch=master&svg=true)](https://ci.appveyor.com/project/graemeleehickey/joineRML) [![License](https://img.shields.io/badge/License-GPL%20%28%3E=%203%29-brightgreen.svg)](http://www.gnu.org/licenses/gpl-3.0.html) [![CRAN\_Status\_Badge](http://www.r-pkg.org/badges/version/joineRML)](https://cran.r-project.org/package=joineRML) [![](http://cranlogs.r-pkg.org/badges/joineRML)](http://cran.rstudio.com/web/packages/joineRML/index.html) [![codecov](https://codecov.io/gh/graemeleehickey/joineRML/branch/master/graph/badge.svg)](https://codecov.io/gh/graemeleehickey/joineRML)
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`joineRML` is an extension of the joineR package for fitting joint models of time-to-event data and multivariate longitudinal data. The model fitted in joineRML is an extension of the Wulfsohn and Tsiatis (1997) and Henderson et al. (2000) models, which is comprised on (*K* + 1)-sub-models: a Cox proportional hazards regression model (Cox, 1972) and a *K*-variate linear mixed-effects model - a direct extension of the Laird and Ware (1982) regression model. The model is fitted using a Monte Carlo Expectation-Maximization (MCEM) algorithm, which closely follows the methodology presented by Lin et al. (2002).

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20 changes: 8 additions & 12 deletions cran-comments.md
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## Resubmission
This is a resubmission owing to an installation ERROR reported by CRAN checks for r-oldrel-windows-ix86+x86_64. In this version I have:

* Patched sigma.mjoint.R to reference S3 method for sigma depending on version number.

## Test environments
* local OS X install, R 3.3.1
* ubuntu 12.04 (on travis-ci), R 3.3.1
* local Windows 7 Enterprise SP1 install, R 3.3.1 (via github_install)
* win-builder (devel and release)
* r-oldrel-windows (via R-hub)
* local OS X install, R 3.3.3
* ubuntu 12.04 (on travis-ci), R 3.3.2 (+ devel, oldrel)
* windows (on appveyor)
* win-builder (devel, release)
* tested on several R-hub platforms

## R CMD check results

0 errors | 0 warnings | 0 notes
0 errors | 0 warnings | 1 notes

## Reverse dependencies

There are no reverse dependencies.

## Other notes

The vignette code can take about 15-20 minutes to run due to the Monte Carlo simulation example.
* win-builder NOTE refers to a spelling error, but word (covariates) is correct.
* The vignette code can take about 15-20 minutes to run due to the Monte Carlo simulation example.

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