load_mcm | R Documentation |
Loads match control tables into the R environment.
load_mcm(
file,
sep = ":",
id_length = "standard",
na = TRUE,
identical = TRUE,
nThread = parallel::detectCores() - 1
)
file |
string, full file path to Mcm.txt. |
sep |
string, divider between hospital ID and MRN. Defaults to :. |
id_length |
string, indicating whether to modify MRN length based-on required values id_length = standard, or to keep lengths as is id_length = asis. |
na |
boolean, whether to remove columns with only NA values. Defaults to TRUE. |
identical |
boolean, whether to remove columns with identical values. Defaults to TRUE. |
nThread |
integer, number of threads to use to load data. |
data table, with matching data.
string, Epic PMRN value for a patient in the index cohort, corresponds to Case_Patient_EPIC_PMRN in RPDR. Data is formatted using pretty_mrn().
string, EMPI value for a patient in the index cohort, corresponds to Case_Patient_EMPI in RPDR. Data is formatted using pretty_mrn().
string, Epic PMRN value for a patient matched to a case in the index cohort, corresponds to Control_Patient_EPIC_PMRN in RPDR. Data is formatted using pretty_mrn().
string, EMPI value for a control patient matched to a case in the index cohort, corresponds to Control_Patient_EMPI in RPDR. Data is formatted using pretty_mrn().
string, Number of similar data points between the index patient and the control patient. This number corresponds to the number of controls (Age, Gender, etc.) chosen during the match control query creation process, corresponds to Match_Strength in RPDR.
## Not run:
#Using defaults
d_mcm <- load_mcm(file = "test_Mcm.txt")
#Use sequential processing
d_mcm <- load_mcm(file = "test_Mcm.txt", nThread = 1)
#Use parallel processing and parse data in MRN_Type and MRN columns and keep all IDs
d_mcm <- load_mcm(file = "test_Mcm.txt", nThread = 20, mrn_type = TRUE, perc = 1)
## End(Not run)
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