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25 changes: 15 additions & 10 deletions DESCRIPTION
@@ -1,23 +1,28 @@
Package: bridgedist
Title: An Implementation of the Bridge Distribution with Logit-Link as in Wang and Louis (2003)
Title: An Implementation of the Bridge Distribution with Logit-Link as in Wang
and Louis (2003)
Version: 0.1.0
Authors@R: person("Bruce", "Swihart", email = "bruce.swihart@gmail.com", role = c("aut", "cre"))
Description: An implementation of the bridge distribution with logit-link in R.
In Wang and Louis (2003), such a univariate bridge distribution was derived as the distribution of
the random intercept that 'bridged' a marginal logistic regression and a conditional logistic
regression. The conditional and marginal regression coefficients are a scalar multiple of each other.
Such is not the case if the random intercept distribution was Gaussian.
Description: An implementation of the bridge distribution with logit-link in
R. In Wang and Louis (2003) <DOI:10.1093/biomet/90.4.765>, such a univariate
bridge distribution was derived as the distribution of the random intercept that
'bridged' a marginal logistic regression and a conditional logistic regression.
The conditional and marginal regression coefficients are a scalar multiple
of each other. Such is not the case if the random intercept distribution was
Gaussian.
Depends:
R (>= 3.0.0)
License: GPL-2
LazyData: true
RoxygenNote: 5.0.1.9000
Suggests: knitr,
RoxygenNote: 5.0.1
Suggests:
knitr,
rmarkdown,
reshape2,
ggplot2,
testthat
Imports: stats
Imports:
stats
VignetteBuilder: knitr
URL: http://github.com/swihart/bridgedist
URL: http://github.com/swihart/bridgedist
BugReports: http://github.com/swihart/bridgedist/issues
10 changes: 5 additions & 5 deletions R/Bridge.R
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##'
##' @seealso \link{Distributions} for other standard distributions.
##' @references Wang, Z. and Louis, T.A. (2003) Matching conditional and marginal shapes in binary random intercept models using
##' a bridge distribution function. \emph{Biometrika}, 90(4), 765-775.
##' a bridge distribution function. \emph{Biometrika}, 90(4), 765-775. <DOI:10.1093/biomet/90.4.765>
##'
##' See also:
##'
##' Swihart, B.J., Caffo, B.S., and Crainiceanu, C.M. (2013). A Unifying Framework for Marginalized Random-Intercept Models of Correlated Binary Outcomes. \emph{International Statistical Review}, 82 (2), 275-295 1-22.
##' Swihart, B.J., Caffo, B.S., and Crainiceanu, C.M. (2013). A Unifying Framework for Marginalized Random-Intercept Models of Correlated Binary Outcomes. \emph{International Statistical Review}, 82 (2), 275-295 1-22. <DOI: 10.1111/insr.12035>
##'
##' Griswold, M.E., Swihart, B.J., Caffo, B.S and Zeger, S.L. (2013). Practical marginalized multilevel models. Stat, 2(1), 129-142.
##' Griswold, M.E., Swihart, B.J., Caffo, B.S and Zeger, S.L. (2013). Practical marginalized multilevel models. Stat, 2(1), 129-142. <DOI: 10.1002/sta4.22>
##'
##' Heagerty, P.J. (1999). Marginally specified logistic-normal models for longitudinal binary data. Biometrics, 55(3), 688-698.
##' Heagerty, P.J. (1999). Marginally specified logistic-normal models for longitudinal binary data. Biometrics, 55(3), 688-698. <DOI: 10.1111/j.0006-341X.1999.00688.x>
##'
##' Heagerty, P.J. and Zeger, S.L. (2000). Marginalized multilevel models and likelihood inference (with comments and a rejoinder by the authors). Stat. Sci., 15(1), 1-26.
##' Heagerty, P.J. and Zeger, S.L. (2000). Marginalized multilevel models and likelihood inference (with comments and a rejoinder by the authors). Stat. Sci., 15(1), 1-26. <DOI: 10.1214/ss/1009212671>
##'
##' @source \code{[dpq]bridge} are calculated directly from the definitions.
##'
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4 changes: 4 additions & 0 deletions cran-comments.md
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* 1st submission

## CRAN Review process

* Added DOI in DESCRIPTION and man

## Downstream dependencies
None.
10 changes: 5 additions & 5 deletions man/Bridge.Rd

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