Run missingness check
library(DrugExposureDiagnostics)
library(dplyr)
library(DT)
# acetaminophen concept id is 1125315
acetaminophen <- 1125315
cdm <- mockDrugExposure()
acetaminophen_checks <- executeChecks(
cdm = cdm,
ingredients = acetaminophen,
checks = "missing"
)Overall missingness
This shows the missingness of the drug records summarised on ingredient level.
datatable(acetaminophen_checks$missingValuesOverall,
rownames = FALSE
)| Column | Description |
|---|---|
| ingredient_concept_id | Concept ID of ingredient. |
| ingredient | Name of drug ingredient. |
| variable | the variable for which missingness was assessed. |
| n_records | Number of records for ingredient concept. If n_records is the same as n_sample this means that there are more records but the number was cut at the pre-specified sample number for efficiency reasons. |
| n_sample | The pre-specified maximum sample. If n_records is smaller than the sample it means that sampling was ignored because the total number of records was already too small. |
| n_records_not_missing_value | The number of records for which there is no missingness in the variable of interest. |
| n_records_missing_value | The number of records with missing values for the variable of interest. |
| proportion_records_missing_value | The proportion of records with missing values for the variable of interest. |
| result_obscured | TRUE if count has been suppressed due to being below the minimum cell count, otherwise FALSE. |
Missingness by drug concept
This shows the missingness on drug concept level.
datatable(acetaminophen_checks$missingValuesByConcept,
rownames = FALSE
)| Column | Description |
|---|---|
| drug_concept_id | ID of the drug concept. |
| drug | Name of the drug concept. |
| ingredient_concept_id | Concept ID of ingredient. |
| ingredient | Name of drug ingredient. |
| variable | the variable for which missingness was assessed. |
| n_records | Number of records for drug concept. If n_records is the same as n_sample this means that there are more records but the number was cut at the pre-specified sample number for efficiency reasons. |
| n_sample | The pre-specified maximum sample. If n_records is smaller than the sample it means that sampling was ignored because the total number of records was already too small. |
| n_records_not_missing_value | The number of records for which there is no missingness in the variable of interest. |
| n_records_missing_value | The number of records with missing values for the variable of interest. |
| proportion_records_missing_value | The proportion of records with missing values for the variable of interest. |
| result_obscured | TRUE if count has been suppressed due to being below the minimum cell count, otherwise FALSE. |