PropensitySub (version 0.2.0)

forest_bygroup: Forest plot: colored by groups

Description

Forest plot: colored by groups

Usage

forest_bygroup(
  data,
  summarystat,
  upperci,
  lowerci,
  population.name,
  group.name = population.name,
  color.group.name = population.name,
  stat.label = "Hazard Ratio",
  text.column = NULL,
  text.column.addition = NULL,
  color = NULL,
  stat.type.hr = TRUE,
  log.scale = FALSE,
  extra.stat = NULL,
  extra.stat.label = NULL,
  endpoint.name = "OS",
  study.name = "",
  draw = TRUE,
  shape.column = NULL,
  shape.vec = NULL
)

Arguments

data

data frame. plotting order will be following the order in the data frame.

summarystat

column name that indicates the summary statistics column (e.g. HR, ORR)

upperci, lowerci

column names that indicate the lower and upper CI of the summary statistics

population.name

column name of the column which indicates population names of the summary statistics

group.name

column name of the column which indicates which group each population is in. group names will be shown in the left panel of the forest plot

color.group.name

column name of the column which indicates how to color different groups

stat.label

Y axis label text

text.column

column name of the column which provides texts to be display on the right side of the forest plot. If it is NULL, the text will be generated by pasting summary stat column, the lowerci column and the upperci column

text.column.addition

additional columns to put (will be placed on the right of the figures), could be a vector of multiple column names

color

customized colors to different groups.

stat.type.hr

whether the summary statistics is HR. If so, the forest plot will be centered at 1

log.scale

whether show summary statistics in log scale

extra.stat

column name of the column which indicates the extra statistics to be drawn on the forest plot. The extra statistics will be drawn by "+". Could be NULL

extra.stat.label

label of the extra.stat (to be shown on y axis)

endpoint.name, study.name

text to be shown in title

draw

whether to draw

shape.column

column to pass to adjust shape. Use NULL for none

shape.vec

a vector to sepecify shapes, e.g. c(15, 16).

Value

return forest plot of class grob.

Examples

# NOT RUN {
 
library(dplyr)
clinical_1 <- clinical %>% mutate( 
  indicator = case_when(
    STRATUM == "strata_1" ~ 0, 
    STRATUM == "strata_2" ~ 1,
    is.na(STRATUM) & ARM == "experimental" ~ 1,
    TRUE ~ -1 
  ),
  ARM  = factor(ARM, levels = c("control","experimental")),
  BNLR = case_when(
    is.na(BNLR) ~ median(BNLR, na.rm = TRUE),
    TRUE ~ BNLR
  )
) 
ipw_res <- ipw_strata(
  data.in = clinical_1, formula = indicator ~ BECOG + SEX + BNLR,
  indicator.var = "indicator", tte = "OS_MONTH", event = "OS_EVENT", trt = "ARM",
  class.of.int = list("strata_1" = 1, "strata_2" = 0)
 )
boot_ipw <- bootstrap_propen(
  data.in = clinical_1, formula = indicator ~ BECOG + SEX + BNLR,
  indicator.var = "indicator", tte = "OS_MONTH", event = "OS_EVENT", trt = "ARM",
  class.of.int = list("strata_1" = 1, "strata_2" = 0),
  estimate.res = ipw_res, method = "ipw", n.boot = 5
)
ps_res <- ps_match_strata(
  data.in = clinical_1, formula = indicator ~ BECOG + SEX + BNLR,
  indicator.var = "indicator", tte = "OS_MONTH", event = "OS_EVENT", trt = "ARM",
  class.of.int = list("strata_1" = 1, "strata_2" = 0)
 )
boot_ps <- bootstrap_propen(
  data.in = clinical_1, formula = indicator ~ BECOG + SEX + BNLR, 
  indicator.var = "indicator", tte = "OS_MONTH", event = "OS_EVENT", trt = "ARM",
  class.of.int = list("strata_1" = 0, "strata_2" = 1),
  estimate.res = ps_res, method = "ps", n.boot = 5
)
boot.out.ipw <- boot_ipw$boot.out.est
boot.out.ps <- boot_ps$boot.out.est
ipw.ci.mat <- boot_ipw$est.ci.mat
ps.ci.mat <- boot_ps$est.ci.mat

data.fp <- data.frame(
  HR = round(exp(c(ipw.ci.mat[, 1], ps.ci.mat[, 1])), 2),
  LOWER = round(exp(c(ipw.ci.mat[, 2], ps.ci.mat[, 2])), 2),
  UPPER = round(exp(c(ipw.ci.mat[, 3], ps.ci.mat[, 3])), 2),
  ADA_Group = rep(rownames(ipw.ci.mat), 2),
  n = paste("n =", rep(table(clinical_1$indicator)[c("0", "1")], 2)),
  Methods_ADA = paste(
    rep(c("IPW", "PS"), each = 2), rep(rownames(ipw.ci.mat), 2)
  ),
  Methods = rep(c("IPW", "PS"), each = 2),
  bootstrapHR = c(
    boot.out.ipw[grep("HR", rownames(boot.out.ipw)), "Median"],
    boot.out.ps[grep("HR", rownames(boot.out.ps)), "Median"]
  )
)
forest_bygroup(
  data = data.fp, summarystat = "HR", upperci = "UPPER", lowerci = "LOWER",
  population.name = "Methods_ADA", group.name = "Methods",
  color.group.name = "ADA_Group", text.column.addition = "n",
  stat.label = "Hazard Ratio", text.column = NULL,
  stat.type.hr = TRUE, log.scale = FALSE, extra.stat = "bootstrapHR",
  extra.stat.label = "bootstrap median",
  endpoint.name = "OS", study.name = "Example Study", draw = TRUE
 ) 
# }