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#' Produce a table and plot
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#'
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#' Wraps \code{\link{or_plot}}, \code{\link{hr_plot}}, and
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#' \code{\link{coefficient_plot}} and sends to the appropriate method depending
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#' on the dependent variable type.
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#' @param .data Data frame.
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#' @param dependent Character vector of length 1.
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#' @param explanatory Character vector of any length: name(s) of explanatory
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#' variables.
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#' @param ... Pass arguments \code{\link{or_plot}}, \code{\link{hr_plot}}, or
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#' \code{\link{coefficient_plot}}
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#'
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#' @return A table and a plot using \code{\link{ggplot2}}
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#' @export
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#' @family finalfit plot functions
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#' @examples
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#' # Coefficient plot
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#' explanatory = c("age.factor", "sex.factor", "obstruct.factor", "perfor.factor")
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#' dependent = "nodes"
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#' colon_s %>%
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#' ff_plot(dependent, explanatory)
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#'
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#' # Odds ratio plot
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#' dependent = "mort_5yr"
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#' colon_s %>%
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#' ff_plot(dependent, explanatory)
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#'
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#' # Hazard ratio plot
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#' dependent = "Surv(time, status)"
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#' colon_s %>%
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#' ff_plot(dependent, explanatory, dependent_label = "Survival")
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ff_plot <- function(.data, dependent, explanatory, ...){
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if(is.data.frame(.data)==FALSE) stop(".data is not dataframe")
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if(is.null(explanatory)) stop("No explanatory variable(s) provided")
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if(is.null(dependent)) stop("No dependent variable provided")
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# Args
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args = list(.data, dependent, explanatory, ...)
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# What is dependent variable
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d_variable = .data[,names(.data) %in% dependent]
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if(is.survival(dependent)){
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d_type = "survival"
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}else{
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d_type = variable_type(d_variable)
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}
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# Send to method
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if (d_type == "survival"){
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do.call(hr_plot, args)
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} else if (d_type == "factor" || d_type == "character" || d_type == "logical"){
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do.call(or_plot, args)
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} else if (d_type == "numeric"){
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do.call(coefficient_plot, args)
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} else {
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stop("Plotting not support for this dependent variable type")
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}
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}
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#' @rdname ff_plot
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#' @export
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finalfit_plot = ff_plot
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Nelson-Gon