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Create a Subject History Table

Source: R/CreateHistory.R
CreateHistory.Rd

Create a Subject History Table

Usage

CreateHistory(
  rawData_ls,
  personsTable = "everybody",
  firstDay_int = NULL,
  lastDay_int = NULL
)

Arguments

rawData_ls

a list of tibbles returned by loadRawData

personsTable

What is the name of the data table that contains all the subject IDs? Defaults to "everybody". If no such table exists, then set this value to "none" and the unique subject IDs will be drawn from all tables in rawData_ls

firstDay_int

(OPTIONAL) What should be the first "day" counter for all subjects? This may be beneficial to set if you wish to have the History ignore all days before a certain point.

lastDay_int

(OPTIONAL) What should be the last "day" counter for all subjects?

Value

A tibble with columns who and when. Each subject will have one row for each day in the study range.

Details

We may want to perform SQL-like operations on a set of tables. This data table will form the "backbone" for future join operations. It creates one record per person for each day in the study. The default behavior is to set the date range to the smallest observed value for "when" across all data tables to the largest observed value for "when" across all tables, inclusive. Necessarily, this is very sensitive to outliers or coding errors (for instance, if one subject has a "first day" 200 days before Study Day 0, then this History table will include days -200 to -1 for ALL subjects, regardless of any recorded contact in this period).

If this behavior is not desirable, you must specify a study range. For example, you may have a short recruitment period followed by a 6-month clinical trial. In this instance, you may want to ignore any data more than 30 days prior to Study Day 0 for each subject or more than a few weeks after the end of the trial. Thus, you would set firstDay_int = -30L and lastDay_int = 6 * 30 + 14.

Examples

   data_ls <- loadRawData(c("tlfb", "all_drugs", "everybody"))
   CreateHistory(rawData_ls = data_ls, firstDay_int = -30)
#> # A tibble: 2,459,960 × 2
#>      who  when
#>    <int> <dbl>
#>  1     8   -30
#>  2     8   -29
#>  3     8   -28
#>  4     8   -27
#>  5     8   -26
#>  6     8   -25
#>  7     8   -24
#>  8     8   -23
#>  9     8   -22
#> 10     8   -21
#> # ℹ 2,459,950 more rows