DMT01 Table 1 (Default) Demographics and Baseline Characteristics Table 1.

For each variable, summary statistics are by default based on the number of patients in the corresponding n row.

Usage

dmt01_1_main(
  adam_db,
  armvar = .study$planarm,
  summaryvars = .study$demo_vars,
  summaryvars_lbls = .study$demo_vars_lbls,
  lbl_overall = .study$lbl_overall,
  prune_0 = TRUE,
  deco = std_deco("DMT01"),
  .study = list(planarm = "ARM", demo_vars = c("AGE", "SEX", "COUNTRY", "RACE"),
    demo_vars_lbls = NULL, lbl_overall = "All Patients")
)

dmt01_1_lyt(
  armvar = .study$planarm,
  summaryvars = .study$demo_vars,
  summaryvars_lbls = .study$demo_vars_lbl,
  lbl_overall = .study$lbl_overall,
  deco = std_deco("DMT01"),
  .study = list(planarm = "ARM", demo_vars = c("AAGE", "AGEGR1", "SEX", "ETHNIC",
    "RACE"), demo_vars_lbl = c("Age (yr)", "Pooled Age Group 1 (yr)", "SEX", "ETHNIC",
    "RACE"), lbl_overall = "All Patients")
)

dmt01_1_pre(adam_db, ...)

dmt01_1

Format

An object of class chevron_tlg of length 1.

Arguments

adam_db: (dm) object containing the ADaM datasets
armvar: (character) variable used for column splitting
summaryvars: (vector of character) variables summarized in demographic table. Usually a vector containing the following one or more of the following: AAGE, AGEGR1, SEX, ETHNIC, RACE and by default all of them.
summaryvars_lbls: (vector of character) labels corresponding to the analyzed variables.
lbl_overall: (character) label used for overall column, if set to NULL the overall column is omitted
prune_0: (logical) remove 0 count rows
deco: (character) decoration with title, subtitles and main_footer content
.study: (list) with default values for the arguments of the function
...: not used.
demo_vars: (vector of strings) variables summarized in demographic table.
demo_vars_lbls: (vector of strings) labels corresponding to the analyzed variables.

Details

Information from ADSUB are generally included into ADSL before analysis.
Default demographic and characteristics table
If not specified otherwise, numbers represent absolute numbers of patients and fraction of N
Remove zero-count rows
Split columns by arm (planned or actual / code or description)
Include a total column by default

Functions

dmt01_1_main(): Main TLG function
dmt01_1_lyt(): Layout
dmt01_1_pre(): Preprocessing

Examples

library(dm)
library(magrittr)

db <- syn_test_data() %>%
  dmt01_1_pre()

dmt01_1_main(db, summaryvars = c("AGE", "RACE", "SEX"), lbl_overall = NULL)
#>                                                A: Drug X    B: Placebo    C: Combination
#>                                                 (N=134)       (N=134)        (N=132)    
#> ————————————————————————————————————————————————————————————————————————————————————————
#> Age                                                                                     
#>   n                                               134           134            132      
#>   Mean (SD)                                   33.8 (6.6)    35.4 (7.9)      35.4 (7.7)  
#>   Median                                         33.0          35.0            35.0     
#>   Min - Max                                   21.0 - 50.0   21.0 - 62.0    20.0 - 69.0  
#> Race                                                                                    
#>   n                                               134           134            132      
#>   ASIAN                                       68 (50.7%)     67 (50%)       73 (55.3%)  
#>   BLACK OR AFRICAN AMERICAN                   31 (23.1%)    28 (20.9%)      32 (24.2%)  
#>   WHITE                                       27 (20.1%)    26 (19.4%)      21 (15.9%)  
#>   AMERICAN INDIAN OR ALASKA NATIVE              8 (6%)       11 (8.2%)       6 (4.5%)   
#>   MULTIPLE                                         0         1 (0.7%)           0       
#>   NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER        0         1 (0.7%)           0       
#> Sex                                                                                     
#>   n                                               134           134            132      
#>   Female                                       79 (59%)     82 (61.2%)       70 (53%)   
#>   Male                                         55 (41%)     52 (38.8%)       62 (47%)   
dmt01_1_main(db,
  summaryvars = c("AGE", "RACE", "SEX"),
  summaryvars_lbls = c("Age (yr)", "Race", "Sex")
)
#>                                                A: Drug X    B: Placebo    C: Combination   All Patients
#>                                                 (N=134)       (N=134)        (N=132)         (N=400)   
#> ———————————————————————————————————————————————————————————————————————————————————————————————————————
#> Age (yr)                                                                                               
#>   n                                               134           134            132             400     
#>   Mean (SD)                                   33.8 (6.6)    35.4 (7.9)      35.4 (7.7)      34.9 (7.4) 
#>   Median                                         33.0          35.0            35.0            34.0    
#>   Min - Max                                   21.0 - 50.0   21.0 - 62.0    20.0 - 69.0     20.0 - 69.0 
#> Race                                                                                                   
#>   n                                               134           134            132             400     
#>   ASIAN                                       68 (50.7%)     67 (50%)       73 (55.3%)      208 (52%)  
#>   BLACK OR AFRICAN AMERICAN                   31 (23.1%)    28 (20.9%)      32 (24.2%)      91 (22.8%) 
#>   WHITE                                       27 (20.1%)    26 (19.4%)      21 (15.9%)      74 (18.5%) 
#>   AMERICAN INDIAN OR ALASKA NATIVE              8 (6%)       11 (8.2%)       6 (4.5%)       25 (6.2%)  
#>   MULTIPLE                                         0         1 (0.7%)           0            1 (0.2%)  
#>   NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER        0         1 (0.7%)           0            1 (0.2%)  
#> Sex                                                                                                    
#>   n                                               134           134            132             400     
#>   Female                                       79 (59%)     82 (61.2%)       70 (53%)      231 (57.8%) 
#>   Male                                         55 (41%)     52 (38.8%)       62 (47%)      169 (42.2%) 
dmt01_1_lyt(armvar = "ACTARM")
#> A Pre-data Table Layout
#> 
#> Column-Split Structure:
#> ACTARM (lvls) 
#>  (all obs) 
#> 
#> Row-Split Structure:
#> DOMAIN (lvls) -> AAGE:AGEGR1:SEX:ETHNIC:RACE (** multivar analysis **) 
#> 
dmt01_1_pre(syn_test_data())
#> ── Metadata ────────────────────────────────────────────────────────────────────
#> Tables: `adsl`, `adae`, `adaette`, `adcm`, `addv`, … (15 total)
#> Columns: 847
#> Primary keys: 2
#> Foreign keys: 1