daDoctoR/man/strobe_pred.Rd

27 lines
1.2 KiB
Plaintext
Raw Normal View History

2018-10-11 16:31:46 +02:00
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/strobe_pred.R
\name{strobe_pred}
\alias{strobe_pred}
\title{Regression model of predictors according to STROBE, bi- and multivariate.}
2018-10-11 16:31:46 +02:00
\usage{
2019-11-12 14:12:27 +01:00
strobe_pred(meas, adj, data, dec = 2, n.by.adj = FALSE,
p.val = FALSE)
2018-10-11 16:31:46 +02:00
}
\arguments{
\item{meas}{binary outcome meassure variable, column name in data.frame as a string. Can be numeric or factor. Result is calculated accordingly.}
\item{adj}{variables to adjust for, as string.}
\item{data}{dataframe of data.}
\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1.}
2018-10-12 11:26:20 +02:00
2018-10-12 12:51:56 +02:00
\item{n.by.adj}{flag to indicate wether to count number of patients in adjusted model or overall for outcome meassure not NA.}
2019-11-12 14:12:27 +01:00
2019-11-13 10:05:53 +01:00
\item{p.val}{flag to include p-values in table, set to FALSE as standard.}
2018-10-11 16:31:46 +02:00
}
\description{
2019-11-12 14:12:27 +01:00
Printable table of regression model according to STROBE. Includes borth bivariate and multivariate in the same table. Output is a list, with the first item being the main "output" as a dataframe. Automatically uses logistic regression model for dichotomous outcome variable and linear regression model for continous outcome variable. Linear regression will give estimated adjusted true mean in list.
2018-10-11 16:31:46 +02:00
}
\keyword{logistic}