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30 lines
1.3 KiB
R
30 lines
1.3 KiB
R
% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/print_pred.R
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\name{print_pred}
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\alias{print_pred}
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\title{Regression model of predictors according to STROBE, bi- and multivariable. Printable result.}
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\usage{
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print_pred(meas, adj, data, dec = 2, n.by.adj = FALSE, p.val = FALSE)
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}
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\arguments{
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\item{meas}{binary outcome measure variable, column name in data.frame as a string. Can be numeric or factor. Result is calculated accordingly.}
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\item{adj}{variables to adjust for, as string.}
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\item{data}{dataframe of data.}
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\item{dec}{decimals for results, standard is set to 2. Mean and sd is dec-1.}
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\item{n.by.adj}{flag to indicate whether to count number of patients in adjusted model or overall for outcome measure not NA.}
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\item{p.val}{flag to include p-values in table, set to FALSE as standard.}
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}
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\description{
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Printable table of regression model according to STROBE for linear or binary outcome-variables.
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Includes both bivariate and multivariate in the same table.
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Output is a list, with the first item being the main "output" as a dataframe.
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Automatically uses logistic regression model for dichotomous outcome variable and linear regression model for continuous outcome variable. Linear regression will give estimated adjusted true mean in list.
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For logistic regression gives count of outcome variable pr variable level.
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}
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\keyword{logistic}
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