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Count the missing follow-up confounder values of a trial panel

Source: R/tteenrollment_fill.R
tteenrollment_fill_aggregates.Rd

The function returns one row per confounder that carries a .tte_entry__ snapshot column. Run it once before the fill and once after it, then pass both tables to tteenrollment_fill_summary().

Usage

tteenrollment_fill_aggregates(trial)

Arguments

trial

A TTEEnrollment object at trial level.

Value

A data.table of class tteenrollment_fill_aggregates, with columns:

confounder

The confounder name.

rows_n

Rows in the panel.

trials_n

Person-trials in the panel.

rows_na_n

Rows whose plain value is NA.

trials_na_n

Person-trials with at least one NA plain value.

trials_entry_na_n

Person-trials whose snapshot value is NA.

rows_leading_na_in_entry_na_trials_n

Rows the imputed snapshot value reaches. Within each person-trial whose snapshot is NA, it is the length of the NA run at the start of that person-trial.

key_digest

A digest of the ordered id_var, tstart_var and tstop_var columns. It is the same string on every row.

Details

The function orders a local copy of the key columns. It never reorders trial$data.

See also

tteenrollment_fill_followup_confounders() for the fill itself.

Other tte_methods: tteenrollment_combined_combine(), tteenrollment_fill_followup_confounders(), tteenrollment_fill_summary(), tteenrollment_irr_combine(), tteenrollment_rates_combine(), tteenrollment_rbind()

Examples

d <- data.table::data.table(
  enrollment_person_trial_id = rep(c("a", "b"), each = 3L),
  tstart = rep(c(0L, 4L, 8L), 2L),
  tstop = rep(c(4L, 8L, 12L), 2L),
  exposed = rep(c(TRUE, FALSE), each = 3L),
  event = 0L,
  income = c(NA, "mid", NA, NA, NA, "high"),
  .tte_entry__income = rep(c("low", "mid"), each = 3L)
)
design <- TTEDesign$new(
  treatment_var = "exposed",
  outcome_vars = "event",
  confounder_vars = "income",
  follow_up_time = 12L
)
tteenrollment_fill_aggregates(TTEEnrollment$new(d, design))
#>    confounder rows_n trials_n rows_na_n trials_na_n trials_entry_na_n
#>        <char>  <int>    <int>     <int>       <int>             <int>
#> 1:     income      6        2         4           2                 0
#>    rows_leading_na_in_entry_na_trials_n                       key_digest
#>                                   <int>                           <char>
#> 1:                                    0 d68f95b906d66b2ea4d45ff0afe6a07c