DMT01
Table 1 (Default) Demographics and Baseline Characteristics Table 1.
dmt01_1.Rd
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,
arm_var = "ARM",
summaryvars = list(`Age (yr)` = "AAGE", `Age group (yr)` = "AGEGR1", Sex = "SEX",
Ethnicity = "ETHNIC", Race = "RACE"),
lbl_overall = "All Patients",
deco = std_deco("DMT01"),
...
)
dmt01_1_lyt(arm_var, summaryvars, summaryvars_lbls, lbl_overall, deco)
dmt01_1_pre(adam_db, ...)
dmt01_1_post(tlg, prune_0 = TRUE, ...)
dmt01_1
Arguments
- adam_db
(
dm
) object containing theADaM
datasets- arm_var
(
string
) variable used for column splitting- summaryvars
(
list
) variables summarized in demographic table. Names are used as subtitles. For values where no name is provided, the label attribute of the corresponding column inadsl
table ofadam_db
is used.- lbl_overall
(
string
) label used for overall column, if set toNULL
the overall column is omitted- deco
(
character
) decoration withtitle
,subtitles
andmain_footer
content- ...
not used.
- summaryvars_lbls
(
character
) labels corresponding to the analyzed variables.- tlg
(
TableTree
,Listing
orggplot
) object typically produced by amain
function.- prune_0
(
flag
) remove 0 count rows
Details
Information from
ADSUB
are generally included intoADSL
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 functiondmt01_1_lyt()
: Layoutdmt01_1_pre()
: Preprocessingdmt01_1_post()
: Postprocessing
Examples
library(dm)
library(magrittr)
db <- syn_data %>%
dmt01_1_pre()
dmt01_1_main(db, lbl_overall = NULL)
#> A: Drug X B: Placebo C: Combination
#> (N=134) (N=134) (N=132)
#> ————————————————————————————————————————————————————————————————————————————————————————
#> Age (yr)
#> 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
#> Age group (yr)
#> n 134 134 132
#> <65 134 (100%) 134 (100%) 131 (99.2%)
#> >=65 0 0 1 (0.8%)
#> Sex
#> n 134 134 132
#> F 79 (59.0%) 82 (61.2%) 70 (53.0%)
#> M 55 (41.0%) 52 (38.8%) 62 (47.0%)
#> Ethnicity
#> n 134 134 132
#> NOT REPORTED 6 (4.5%) 10 (7.5%) 11 (8.3%)
#> HISPANIC OR LATINO 15 (11.2%) 18 (13.4%) 15 (11.4%)
#> NOT HISPANIC OR LATINO 104 (77.6%) 103 (76.9%) 101 (76.5%)
#> UNKNOWN 9 (6.7%) 3 (2.2%) 5 (3.8%)
#> Race
#> n 134 134 132
#> ASIAN 68 (50.7%) 67 (50.0%) 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 (6.0%) 11 (8.2%) 6 (4.5%)
#> MULTIPLE 0 1 (0.7%) 0
#> NATIVE HAWAIIAN OR OTHER PACIFIC ISLANDER 0 1 (0.7%) 0
#> OTHER 0 0 0
#> UNKNOWN 0 0 0
dmt01_1_main(db, summaryvars = c("Age" = "AGE", "Race" = "RACE", "Gender" = "SEX"))
#> A: Drug X B: Placebo C: Combination All Patients
#> (N=134) (N=134) (N=132) (N=400)
#> ———————————————————————————————————————————————————————————————————————————————————————————————————————
#> Age
#> 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 (50.0%) 73 (55.3%) 208 (52.0%)
#> 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 (6.0%) 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%)
#> OTHER 0 0 0 0
#> UNKNOWN 0 0 0 0
#> Gender
#> n 134 134 132 400
#> F 79 (59.0%) 82 (61.2%) 70 (53.0%) 231 (57.8%)
#> M 55 (41.0%) 52 (38.8%) 62 (47.0%) 169 (42.2%)
dmt01_1_pre(syn_data)
#> ── Metadata ────────────────────────────────────────────────────────────────────
#> Tables: `adsl`, `adab`, `adae`, `adaette`, `adcm`, … (19 total)
#> Columns: 1400
#> Primary keys: 1
#> Foreign keys: 18
run(dmt01_1, syn_data)
#> 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
#> Age group (yr)
#> n 134 134 132 400
#> <65 134 (100%) 134 (100%) 131 (99.2%) 399 (99.8%)
#> >=65 0 0 1 (0.8%) 1 (0.2%)
#> Sex
#> n 134 134 132 400
#> F 79 (59.0%) 82 (61.2%) 70 (53.0%) 231 (57.8%)
#> M 55 (41.0%) 52 (38.8%) 62 (47.0%) 169 (42.2%)
#> Ethnicity
#> n 134 134 132 400
#> NOT REPORTED 6 (4.5%) 10 (7.5%) 11 (8.3%) 27 (6.8%)
#> HISPANIC OR LATINO 15 (11.2%) 18 (13.4%) 15 (11.4%) 48 (12.0%)
#> NOT HISPANIC OR LATINO 104 (77.6%) 103 (76.9%) 101 (76.5%) 308 (77.0%)
#> UNKNOWN 9 (6.7%) 3 (2.2%) 5 (3.8%) 17 (4.2%)
#> Race
#> n 134 134 132 400
#> ASIAN 68 (50.7%) 67 (50.0%) 73 (55.3%) 208 (52.0%)
#> 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 (6.0%) 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%)