Prepare data for Subgroup Analysis for Baseline Characteristic
format_base_char_subgroup.RdPrepare data for Subgroup Analysis for Baseline Characteristic
Arguments
- outdata
A metadata object created by
prepare_base_char_subgroup().- display
Column wants to display on the table. The term could be selected from
c("n", "prop", "total").- display_stat
A vector of statistics term name. The term name could be selected from
c("mean", "sd", "se", "median", "q1 to q3", "range", "q1", "q3", "min", "max").
Examples
meta <- meta_sl_example()
outdata <- prepare_base_char_subgroup(
meta,
population = "apat",
parameter = "age",
subgroup_var = "TRTA",
subgroup_header = c("SEX", "TRTA"),
display_subgroup_total = TRUE
)
outdata |> format_base_char_subgroup()
#> $group
#> [1] "Female" "Male"
#>
#> $subgroup
#> [1] "Placebo" "Low Dose" "High Dose"
#>
#> $display_subgroup_total
#> [1] TRUE
#>
#> $meta
#> ADaM metadata:
#> .$data_population Population data with 254 subjects
#> .$data_observation Observation data with 254 records
#> .$plan Analysis plan with 4 plans
#>
#>
#> Analysis population type:
#> name id group var subset label
#> 1 'apat' 'USUBJID' 'TRTA' SAFFL == 'Y' 'All Participants as Treated'
#>
#>
#> Analysis observation type:
#> name id group var subset label
#> 1 'apat' 'USUBJID' 'TRTA' 'All Participants as Treated'
#>
#>
#> Analysis parameter type:
#> name label subset
#> 1 'age' 'Age (years)'
#> 2 'gender' 'Gender'
#> 3 'race' 'Race'
#> 4 'disposition' 'Trial Disposition'
#> 5 'medical-disposition' 'Participant Study Medication Disposition'
#> 6 'comp8' 'Compliance (Week 8)'
#> 7 'comp16' 'Compliance (Week 16)'
#> 8 'comp24' 'Compliance (Week 24)'
#>
#>
#> Analysis function:
#> name label
#> 1 'base_char' 'baseline characteristic table'
#> 2 'trt_compliance' 'treatment compliance table'
#> 3 'disp' 'disposition table'
#> 4 'base_char_subgroup' 'baseline characteristic sub group table'
#>
#>
#> $population
#> [1] "apat"
#>
#> $observation
#> [1] "apat"
#>
#> $parameter
#> [1] "age"
#>
#> $out_all
#> $out_all$Placebo
#> List of 14
#> $ meta :List of 7
#> $ population : chr "apat"
#> $ observation : chr "apat"
#> $ parameter : chr "age"
#> $ n :'data.frame': 1 obs. of 5 variables:
#> $ order : NULL
#> $ group : chr "SEX"
#> $ reference_group: NULL
#> $ char_n :List of 1
#> $ char_var : chr "AGE"
#> $ char_prop :List of 1
#> $ var_type :List of 1
#> $ group_label : Factor w/ 2 levels "Female","Male": 1 2
#> $ analysis : chr "base_char_subgroup"
#>
#> $out_all$`Low Dose`
#> List of 14
#> $ meta :List of 7
#> $ population : chr "apat"
#> $ observation : chr "apat"
#> $ parameter : chr "age"
#> $ n :'data.frame': 1 obs. of 5 variables:
#> $ order : NULL
#> $ group : chr "SEX"
#> $ reference_group: NULL
#> $ char_n :List of 1
#> $ char_var : chr "AGE"
#> $ char_prop :List of 1
#> $ var_type :List of 1
#> $ group_label : Factor w/ 2 levels "Female","Male": 2 1
#> $ analysis : chr "base_char_subgroup"
#>
#> $out_all$`High Dose`
#> List of 14
#> $ meta :List of 7
#> $ population : chr "apat"
#> $ observation : chr "apat"
#> $ parameter : chr "age"
#> $ n :'data.frame': 1 obs. of 5 variables:
#> $ order : NULL
#> $ group : chr "SEX"
#> $ reference_group: NULL
#> $ char_n :List of 1
#> $ char_var : chr "AGE"
#> $ char_prop :List of 1
#> $ var_type :List of 1
#> $ group_label : Factor w/ 2 levels "Female","Male": 2 1
#> $ analysis : chr "base_char_subgroup"
#>
#> $out_all$Total
#> List of 14
#> $ meta :List of 7
#> $ population : chr "apat"
#> $ observation : chr "apat"
#> $ parameter : chr "age"
#> $ n :'data.frame': 1 obs. of 5 variables:
#> $ order : NULL
#> $ group : chr "SEX"
#> $ reference_group: NULL
#> $ char_n :List of 1
#> $ char_var : chr "AGE"
#> $ char_prop :List of 1
#> $ var_type :List of 1
#> $ group_label : Factor w/ 2 levels "Female","Male": 1 2
#> $ analysis : chr "base_char_subgroup"
#>
#>
#> $tbl
#> name var_label order Placebon_1 Placebop_1 Placebon_2
#> 7 Participants in population ----- 1 53 <NA> 33
#> 1 65-80 Age (years) 2 22 (41.5) 20
#> 2 <65 Age (years) 3 9 (17.0) 5
#> 3 >80 Age (years) 4 22 (41.5) 8
#> 6 <NA> Age (years) 5 <NA> <NA> <NA>
#> 4 Mean Age (years) 6 76.4 <NA> 73.4
#> 9 SD Age (years) 7 8.7 <NA> 8.1
#> 5 Median Age (years) 8 78.0 <NA> 74.0
#> 8 Range Age (years) 9 59 to 89 <NA> 52 to 85
#> Placebop_2 Placebon_9999 Placebop_9999 Low Dosen_1 Low Dosep_1 Low Dosen_2
#> 7 <NA> 86 <NA> 50 <NA> 34
#> 1 (60.6) 42 (48.8) 28 (56.0) 19
#> 2 (15.2) 14 (16.3) 5 (10.0) 3
#> 3 (24.2) 30 (34.9) 17 (34.0) 12
#> 6 <NA> <NA> <NA> <NA> <NA> <NA>
#> 4 <NA> 75.2 <NA> 75.7 <NA> 75.6
#> 9 <NA> 8.6 <NA> 8.1 <NA> 8.7
#> 5 <NA> 76.0 <NA> 77.5 <NA> 77.5
#> 8 <NA> 52 to 89 <NA> 54 to 87 <NA> 51 to 88
#> Low Dosep_2 Low Dosen_9999 Low Dosep_9999 High Dosen_1 High Dosep_1
#> 7 <NA> 84 <NA> 40 <NA>
#> 1 (55.9) 47 (56.0) 28 (70.0)
#> 2 (8.8) 8 (9.5) 5 (12.5)
#> 3 (35.3) 29 (34.5) 7 (17.5)
#> 6 <NA> <NA> <NA> <NA> <NA>
#> 4 <NA> 75.7 <NA> 74.7 <NA>
#> 9 <NA> 8.3 <NA> 7.7 <NA>
#> 5 <NA> 77.5 <NA> 76.0 <NA>
#> 8 <NA> 51 to 88 <NA> 56 to 88 <NA>
#> High Dosen_2 High Dosep_2 High Dosen_9999 High Dosep_9999
#> 7 44 <NA> 84 <NA>
#> 1 27 (61.4) 55 (65.5)
#> 2 6 (13.6) 11 (13.1)
#> 3 11 (25.0) 18 (21.4)
#> 6 <NA> <NA> <NA> <NA>
#> 4 74.1 <NA> 74.4 <NA>
#> 9 8.2 <NA> 7.9 <NA>
#> 5 77.0 <NA> 76.0 <NA>
#> 8 56 to 86 <NA> 56 to 88 <NA>
#>
#> $display
#> [1] "n" "prop" "total"
#>
#> $display_stat
#> [1] "mean" "sd" "median" "range"
#>