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46 lines
1.6 KiB
R
46 lines
1.6 KiB
R
utils::globalVariables(c("df","group","score","strata"))
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#' Generic stroke study outcome
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#'
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#' Includes table 1, grotta bars and ordinal logistic regression plot.
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#' Please just use this function for illustration purposes.
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#' To dos: modify grottaBar and include as own function.
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#'
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#' @param df Data set as data frame
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#' @param group Variable to group by
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#' @param score Outcome measure variable
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#' @param strata Optional variable to stratify by
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#' @param variables String of variable names to include in adjusted OLR-analysis
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#'
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#' @return Returns list with three elements
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#' @export
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#'
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#' @import ggplot2
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#' @importFrom gtsummary tbl_summary
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#' @importFrom gtsummary add_overall
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#' @importFrom MASS polr
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#' @importFrom rankinPlot grottaBar
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#'
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#' @examples
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#' generic_stroke(stRoke::talos, "rtreat", "mrs_6", variables = c("hypertension","diabetes","civil"))
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generic_stroke <- function(df, group, score, strata = NULL, variables = NULL)
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{
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# if (!is.factor(df[,group])){
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# df[,group] <- factor(df[,group])
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# }
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t1<-gtsummary::tbl_summary(data = df[,c(group,variables)],
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by = group) |>
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gtsummary::add_overall()
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x <- table(df[,c(group, score, strata)])
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f1 <- rankinPlot::grottaBar(x = x, groupName = group,
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scoreName = score,
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strataName = strata,
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colourScheme ="custom")
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df[,score] <- factor(df[,score],ordered = TRUE)
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f2 <- plot_olr(MASS::polr(formula(paste0(score,"~.")), data=df[,c(group, score, variables)], Hess=TRUE, method="logistic"), input="model")
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list("Table 1" = t1, "Figure 1" = f1, "Figure 2" = f2)
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}
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