Cumulative accrual plots

Plot of cumulative recruitment using an accrual data frame produced by accrual_create_df.

Usage

accrual_plot_cum(
  accrual_df,
  ylim = NA,
  xlim = NA,
  ylab = "Recruited patients",
  xlabn = 5,
  xlabminn = xlabn%/%2,
  xlabformat = "%d%b%Y",
  xlabpos = NA,
  xlabsrt = 45,
  xlabadj = c(1, 1),
  xlabcex = 1,
  col = rep(1:8, 5),
  lty = rep(1:5, each = 8),
  legend.list = NULL,
  ...
)

gg_accrual_plot_cum(accrual_df, xlabformat = "%d%b%Y")

Arguments

accrual_df

object of class 'accrual_df' or 'accrual_list' produced by accrual_create_df.

ylim

limits for y-axis.

xlim

limits for x-axis.

ylab

y-axis label.

xlabn

integer giving the desired number of intervals for the xlabel, default=5.

xlabminn

negative integer giving the minimal number of intervals.

xlabformat

format of date on x-axis.

xlabpos

position of the x-label.

xlabsrt

rotation of x-axis labels in degrees.

xlabadj

adjustment of x-label, numeric vector with length 1 or 2 for different adjustment in x- and y-direction.

xlabcex

size of x-axis label.

col

color for line(s) in plot

lty

line type(s) in plot

legend.list

named list with options passed to legend().

...

further options passed to plot() and axis().

Value

accrual_plot_cum returns a plot of the cumulative accrual (per site if accrual_df is a list).

ggplot2 object

Details

When the accrual_df includes multiple sites, the dataframe passed to ggplot includes a site variable which can be used for faceting

Examples

set.seed(2020)
enrollment_dates <- as.Date("2018-01-01") + sort(sample(1:30, 50, replace=TRUE))
accrual_df<-accrual_create_df(enrollment_dates)
accrual_plot_cum(accrual_df)

accrual_plot_cum(accrual_df,cex.lab=1.2,cex.axis=1.1,xlabcex=1.1)


#several sites
set.seed(1)
centers<-sample(c("Site 1","Site 2","Site 3"),length(enrollment_dates),replace=TRUE)
accrual_df<-accrual_create_df(enrollment_dates,by=centers)
accrual_plot_cum(accrual_df)


#assuming a common start and current date
accrual_df<-accrual_create_df(enrollment_dates,by=centers,start_date="common",current_date="common")
accrual_plot_cum(accrual_df)


#plot and legend options
accrual_plot_cum(accrual_df,col=c("red",rep(1,3)),lty=c(1,1:3),cex.lab=1.2,cex.axis=1.1,xlabcex=1.1)

accrual_plot_cum(accrual_df,legend.list=list(ncol=2,bty=TRUE,cex=0.8))


#without overall
accrual_df<-accrual_create_df(enrollment_dates,by=centers,overall=FALSE)
accrual_plot_cum(accrual_df)


### ggplot2 approach
data(accrualdemo)
accrual_df<-accrual_create_df(accrualdemo$date)
gg_accrual_plot_cum(accrual_df)

gg_accrual_plot_cum(accrual_df) +
  ggplot2::theme_classic()


#several sites
accrual_df <- accrual_create_df(accrualdemo$date, by = accrualdemo$site)
gg_accrual_plot_cum(accrual_df)


#assuming a common start and current date
accrual_df <-
  accrual_create_df(
    accrualdemo$date,
    by = accrualdemo$site,
    start_date = "common",
    current_date = "common"
  )
gg_accrual_plot_cum(accrual_df)


#without overall
accrual_df <-
  accrual_create_df(accrualdemo$date, by = accrualdemo$site, overall = FALSE)
gg_accrual_plot_cum(accrual_df)