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Subject disposition

Source: R/builders-table.R
tbl_disposition.Rd

n (%) for population flags ("Y" = yes), subjects discontinued from the study, and the discontinuation reasons.

Usage

tbl_disposition(
  adsl,
  trt_var = "TRT01A",
  flags = list(RANDFL = "Randomized", SAFFL = "Safety population", COMPLFL =
    "Completed study"),
  eos_var = "EOSSTT",
  discontinued = "DISCONTINUED",
  reason_var = "DCSREAS",
  config = NULL
)

Arguments

adsl

Subject-level data.

trt_var

Treatment variable (resolved with tlf_resolve_trt()).

flags

Named list: flag column = row label. Flags missing from the data are skipped.

eos_var

End-of-study status column.

discontinued

Values of eos_var meaning discontinued (matched case-insensitively).

reason_var

Discontinuation reason column.

config

A tlf_config(); NULL resolves through tlf_get_config().

Value

A tlf_table.

See also

Other table builders: tbl_ae(), tbl_ae_severity(), tbl_demographics(), tbl_eff(), tbl_listing(), tbl_shift(), tbl_tte()

Examples

tbl_disposition(ex_adsl)
#> <tlf_table> 7 row(s) x 5 column(s)
#>  Category                Drug 10 mg (N=20) Drug 20 mg (N=20) Placebo (N=20)
#>  Randomized              20 (100.0%)       20 (100.0%)       20 (100.0%)   
#>  Safety population       20 (100.0%)       20 (100.0%)       20 (100.0%)   
#>  Completed study         19 (95.0%)        17 (85.0%)        17 (85.0%)    
#>  Discontinued study      1 (5.0%)          3 (15.0%)         3 (15.0%)     
#>    ADVERSE EVENT         1 (5.0%)          1 (5.0%)          1 (5.0%)      
#>    LOST TO FOLLOW-UP     0                 2 (10.0%)         1 (5.0%)      
#>    WITHDRAWAL BY SUBJECT 0                 0                 1 (5.0%)      
#>  Total (N=60)
#>  60 (100.0%) 
#>  60 (100.0%) 
#>  53 (88.3%)  
#>  7 (11.7%)   
#>  3 (5.0%)    
#>  3 (5.0%)    
#>  1 (1.7%)