-
Notifications
You must be signed in to change notification settings - Fork 0
/
generic_stroke.R
61 lines (55 loc) · 1.71 KB
/
generic_stroke.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
utils::globalVariables(c("df","group","score","strata"))
#' Generic stroke study outcome
#'
#' Includes table 1, grotta bars and ordinal logistic regression plot.
#' Please just use this function for illustration purposes.
#' To dos: modify grottaBar and include as own function.
#'
#' @param df Data set as data frame
#' @param group Variable to group by
#' @param score Outcome measure variable
#' @param strata Optional variable to stratify by
#' @param variables String of variable names to include in adjusted OLR-analysis
#'
#' @return Returns list with three elements
#' @export
#'
#' @import ggplot2
#' @importFrom gtsummary tbl_summary
#' @importFrom gtsummary add_overall
#' @importFrom MASS polr
#' @importFrom rankinPlot grottaBar
#' @importFrom stats as.formula
#'
#' @examples
#' # generic_stroke(df = stRoke::talos, group = "rtreat", score = "mrs_6",
#' # variables = c("hypertension","diabetes","civil"))
generic_stroke <-
function(df,
group,
score,
strata = NULL,
variables = NULL){
t1 <- gtsummary::tbl_summary(data = df[, c(group, variables)],
by = group) |>
gtsummary::add_overall()
x <- table(df[, c(group, score, strata)])
f1 <- rankinPlot::grottaBar(
x = x,
groupName = group,
scoreName = score,
strataName = strata,
colourScheme = "custom"
)
df[, score] <- factor(df[, score], ordered = TRUE)
f2 <- ci_plot(MASS::polr(
as.formula(paste0(score, "~.")),
data = df[, c(group, score, variables)],
Hess = TRUE,
method = "logistic"
),
method = "model")
list("Table 1" = t1,
"Figure 1" = f1,
"Figure 2" = f2)
}