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updated desc, fixed 2 warnings

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agdamsbo 2019-11-26 14:11:37 +01:00
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11
DESCRIPTION
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@ -1,12 +1,11 @@
Package: daDoctoR
Type: Package
Title: FUNCTIONS FOR HEALTH RESEARCH
Version: 0.1.0.9036
Author: c(person("Andreas", "Gammelgaard Damsbo", email = "agdamsbo@pm.me", role = c("cre", "aut")))
Title: Functions For Health Research.
Version: 0.1.0.9037
Year: 2019
Author: person("Andreas", "Gammelgaard Damsbo", email = "agdamsbo@pm.me", role = c("cre", "aut"))
Maintainer: Andreas Gammelgaard Damsbo <agdamsbo@pm.me>
Description: I am a Danish medical doctor involved in neuropsychiatric research.
Here I have collected functions I use for my data analysis. You are very
welcome to get inspired or to use my work.
Description: R functions for convenient data management an danalysis in health research.
Imports: broom, dplyr, epiR, ggplot2, MASS, carData, eulerr
Suggest: shiny
License: GPL (>= 2)

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R/rep_glm.R
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#' @param meas Effect meassure. Input as c() of columnnames, use dput().
#' @param vars variables in model. Input as c() of columnnames, use dput().
#' @param string variables to test. Input as c() of columnnames, use dput().
#' @param ci flag to get results as OR with 95% confidence interval.
#' @param ci flag to get results as OR with 95 percent confidence interval.
#' @param data dataframe to pull variables from.
#' @param fixed.var flag to set "vars" as fixed in the model. When FALSE, then true bivariate logistic regression is performed.
#' @keywords logistic

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R/rep_lm.R
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@ -4,7 +4,7 @@
#' @param meas Effect meassure. Input as c() of columnnames, use dput().
#' @param vars variables in model. Input as c() of columnnames, use dput().
#' @param string variables to test. Input as c() of columnnames, use dput().
#' @param ci flag to get results as OR with 95% confidence interval.
#' @param ci flag to get results as OR with 95 percent confidence interval.
#' @param data data frame to pull variables from.
#' @param fixed.var flag to set "vars" as fixed in the model. When FALSE, then true bivariate linear regression is performed.
#' @keywords linear regression

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R/rep_olr.R
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@ -4,8 +4,8 @@
#' @param meas Effect meassure. Input as c() of columnnames, use dput().
#' @param vars variables in model. Input as c() of columnnames, use dput().
#' @param string variables to test. Input as c() of columnnames, use dput().
#' @param ci flag to get results as OR with 95% confidence interval.
#' @param data data frame to pull variables from.
#' @param ci flag to get results as OR with 95 percent confidence interval.
#' @param data data.frame to pull variables from.
#' @keywords olr
#' @export

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man/rep_glm.Rd
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@ -14,7 +14,7 @@ rep_glm(meas, vars = NULL, string, ci = FALSE, data,
\item{string}{variables to test. Input as c() of columnnames, use dput().}
\item{ci}{flag to get results as OR with 95% confidence interval.}
\item{ci}{flag to get results as OR with 95 percent confidence interval.}
\item{data}{dataframe to pull variables from.}

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man/rep_lm.Rd
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@ -14,7 +14,7 @@ rep_lm(meas, vars = NULL, string, ci = FALSE, data,
\item{string}{variables to test. Input as c() of columnnames, use dput().}
\item{ci}{flag to get results as OR with 95% confidence interval.}
\item{ci}{flag to get results as OR with 95 percent confidence interval.}
\item{data}{data frame to pull variables from.}

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man/rep_olr.Rd
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@ -13,9 +13,9 @@ rep_olr(meas, vars, string, ci = FALSE, data)
\item{string}{variables to test. Input as c() of columnnames, use dput().}
\item{ci}{flag to get results as OR with 95% confidence interval.}
\item{ci}{flag to get results as OR with 95 percent confidence interval.}
\item{data}{data frame to pull variables from.}
\item{data}{data.frame to pull variables from.}
}
\description{
For bivariate analyses. The confint() function is rather slow, causing the whole function to hang when including many predictors and calculating the ORs with CI.