# \donttest{
library(OmopSketch)
library(dplyr, warn.conflicts = FALSE)
library(omock)
cdm <- mockCdmFromDataset(datasetName = "GiBleed", source = "duckdb")
#> ℹ Reading GiBleed tables.
#> ℹ Adding drug_strength table.
#> ℹ Creating local <cdm_reference> object.
#> ℹ Inserting <cdm_reference> into duckdb.
result <- summarisePerson(cdm = cdm)
tablePerson(result = result)
Summary of person table
| Variable name |
Variable level |
Estimate name |
CDM name
|
|---|
| GiBleed |
|---|
| Number subjects |
– |
N |
2,694 |
| Number subjects not in observation |
– |
N (%) |
0 (0.00%) |
| Sex |
Female |
N (%) |
1,373 (50.97%) |
|
Male |
N (%) |
1,321 (49.03%) |
|
None |
N (%) |
0 (0.00%) |
| Sex source |
F |
N (%) |
1,373 (50.97%) |
|
M |
N (%) |
1,321 (49.03%) |
| Race |
No matching concept |
N (%) |
451 (16.74%) |
|
Missing |
N (%) |
2,243 (83.26%) |
| Race source |
asian |
N (%) |
212 (7.87%) |
|
black |
N (%) |
338 (12.55%) |
|
hispanic |
N (%) |
435 (16.15%) |
|
native |
N (%) |
14 (0.52%) |
|
other |
N (%) |
2 (0.07%) |
|
white |
N (%) |
1,693 (62.84%) |
| Ethnicity |
No matching concept |
N (%) |
2,259 (83.85%) |
|
Missing |
N (%) |
435 (16.15%) |
| Ethnicity source |
african |
N (%) |
119 (4.42%) |
|
american |
N (%) |
79 (2.93%) |
|
american_indian |
N (%) |
14 (0.52%) |
|
arab |
N (%) |
2 (0.07%) |
|
asian_indian |
N (%) |
81 (3.01%) |
|
central_american |
N (%) |
75 (2.78%) |
|
chinese |
N (%) |
131 (4.86%) |
|
dominican |
N (%) |
105 (3.90%) |
|
english |
N (%) |
218 (8.09%) |
|
french |
N (%) |
129 (4.79%) |
|
french_canadian |
N (%) |
74 (2.75%) |
|
german |
N (%) |
130 (4.83%) |
|
greek |
N (%) |
19 (0.71%) |
|
irish |
N (%) |
438 (16.26%) |
|
italian |
N (%) |
295 (10.95%) |
|
mexican |
N (%) |
42 (1.56%) |
|
polish |
N (%) |
107 (3.97%) |
|
portuguese |
N (%) |
93 (3.45%) |
|
puerto_rican |
N (%) |
258 (9.58%) |
|
russian |
N (%) |
34 (1.26%) |
|
scottish |
N (%) |
48 (1.78%) |
|
south_american |
N (%) |
60 (2.23%) |
|
swedish |
N (%) |
29 (1.08%) |
|
west_indian |
N (%) |
114 (4.23%) |
| Year of birth |
– |
Missing (%) |
0 (0.00%) |
|
|
Median [Q25 - Q75] |
1,961 [1,950 - 1,970] |
|
|
90% Range [Q05 to Q95] |
1,922 to 1,979 |
|
|
Range [min to max] |
1,908 to 1,986 |
| Month of birth |
– |
Missing (%) |
0 (0.00%) |
|
|
Median [Q25 - Q75] |
7 [4 - 10] |
|
|
90% Range [Q05 to Q95] |
1 to 12 |
|
|
Range [min to max] |
1 to 12 |
| Day of birth |
– |
Missing (%) |
0 (0.00%) |
|
|
Median [Q25 - Q75] |
16 [8 - 23] |
|
|
90% Range [Q05 to Q95] |
2 to 29 |
|
|
Range [min to max] |
1 to 31 |
| Location |
– |
Missing (%) |
2,694 (100.00%) |
|
|
Zero count (%) |
0 (0.00%) |
|
|
Distinct values |
1 |
| Provider |
– |
Missing (%) |
2,694 (100.00%) |
|
|
Zero count (%) |
0 (0.00%) |
|
|
Distinct values |
1 |
| Care site |
– |
Missing (%) |
2,694 (100.00%) |
|
|
Zero count (%) |
0 (0.00%) |
|
|
Distinct values |
1 |
