Creates a data frame or a list of data frames that contains the absolute and cumululative number of participants recruited at each date from a vector with enrollment dates. Used as input for accrual plot functions.
Usage
accrual_create_df(
enrollment_dates,
by = NA,
start_date = "site",
current_date = "common",
overall = TRUE,
name_overall = "Overall",
pos_overall = c("last", "first"),
force_start0 = TRUE
)Arguments
- enrollment_dates
date vector with one entry per participants.
- by
factor or character vector with sites, has to have the same length as enrollment dates. If not NA, a list with an accrual data frame for each site is generated.
- start_date
date when recruitment started. Single date (used for all sites in by), named date vector (with length and names corresponding to the levels of by), "common" (first date overall) or "site" (first date for each site, default).
- current_date
date of the data export or database freeze. Single date, named date vector (with length and names corresponding to the levels of by), "common" (last date overall, default) or "site" (last date for each site).
- overall
logical indicates that accrual_df contains a summary with all sites (only if by is not NA).
- name_overall
name of the summary with all sites (if by is not NA and overall==TRUE).
- pos_overall
overall as last or first element of the list (if by is not NA and overall==TRUE).
- force_start0
logical, adds an extra 0 line to the accrual data frame in cases where a start date is given and corresponds to the earliest enrollment date.
Value
Returns a data frame of class 'accrual_df' or a list of class 'accrual_list' with an 'accrual_df' for each level of by (if by is not NA). The 'accrual_df' contains a row per accrual day and the following three columns:
- Date
date of accrual
- Freq
absolute number accrued at Date
- Cumulative
cumulative number accrued up to Date
See also
accrual_plot_cum(), accrual_plot_abs() and accrual_plot_predict()
to generate cumulative, absolute and prediction plots, and accrual_table() to generate an accrual table.
Examples
# \donttest{
data(accrualdemo)
accrual_create_df(accrualdemo$date)
#> 250 participants recruited between 2020-07-09 and 2020-10-09
#> Date Freq Cumulative
#> 1 2020-07-09 0 0
#> 2 2020-07-09 1 1
#> 3 2020-07-14 3 4
#> 4 2020-07-16 1 5
#> 5 2020-07-19 1 6
#> 6 2020-07-20 1 7
# different start and current date
accrual_create_df(accrualdemo$date, start_date=as.Date("2020-07-08"),
current_date=as.Date("2020-10-15"))
#> 250 participants recruited between 2020-07-08 and 2020-10-15
#> Date Freq Cumulative
#> 1 2020-07-08 0 0
#> 2 2020-07-09 1 1
#> 3 2020-07-14 3 4
#> 4 2020-07-16 1 5
#> 5 2020-07-19 1 6
#> 6 2020-07-20 1 7
#by site
accrual_create_df(accrualdemo$date,by=accrualdemo$site)
#> Site 1:
#> 141 participants recruited between 2020-07-09 and 2020-10-09
#> Date Freq Cumulative
#> 1 2020-07-09 0 0
#> 2 2020-07-09 1 1
#> 3 2020-07-14 3 4
#> 4 2020-07-16 1 5
#> 5 2020-07-19 1 6
#> 6 2020-07-21 1 7
#>
#> Site 2:
#> 88 participants recruited between 2020-07-20 and 2020-10-09
#> Date Freq Cumulative
#> 1 2020-07-20 0 0
#> 2 2020-07-20 1 1
#> 3 2020-07-21 1 2
#> 4 2020-07-22 1 3
#> 5 2020-07-23 1 4
#> 6 2020-07-26 1 5
#>
#> Site 3:
#> 21 participants recruited between 2020-09-04 and 2020-10-09
#> Date Freq Cumulative
#> 1 2020-09-04 0 0
#> 2 2020-09-04 1 1
#> 3 2020-09-05 1 2
#> 4 2020-09-07 2 4
#> 5 2020-09-12 1 5
#> 6 2020-09-13 1 6
#>
#> Overall:
#> 250 participants recruited between 2020-07-09 and 2020-10-09
#> Date Freq Cumulative
#> 1 2020-07-09 0 0
#> 2 2020-07-09 1 1
#> 3 2020-07-14 3 4
#> 4 2020-07-16 1 5
#> 5 2020-07-19 1 6
#> 6 2020-07-20 1 7
#>
# }