xgx_check_data performs a series of checks on a PK or PKPD dataset
It was inspired by the dataset preparation table from
IntiQuan.
xgx_check_data(data, covariates = NULL)the dataset to check. Must contain the above columns
the column names of covariates, to explore
data.frame
The dataset must have the following columns
ID = unique subject identifier. USUBJID is another option if ID is not there
EVID = event ID: 1 for dose, 0 otherwise
AMT = value of the dose
TIME = time of the measurement
DV = dependent value (linear scale). will check if LIDV or LNDV are also there if DV is not
YTYPE = data measurement for LIDV. will check if CMT is there, if YTYPE is not
The dataset may also have additional columns
CENS = flag for censoring of the data because it's below the limit of quantification (BLOQ)
MDV = missing dependent variable - will be counted and then filtered out from the data check
covariates <- c("WEIGHTB", "SEX")
check <- xgx_check_data(mad_missing_duplicates, covariates)
#> Warning: Setting YTYPE column equal to CMT
#> Warning: Setting DV column equal to LIDV
#> removing points with MDV==1 & EVID==0 from dataset
#>
#> DATA SUMMARY
#>
#> ------------------------------------------------------------------------------------------------------------
#> Category Description YTYPE Statistic
#> ------------- ---------------------------------------------------- ------- ---------------------------------
#> Patients Number of Patients - 60
#>
#> MDV Number of patients with zero PK or PD observations all 0
#>
#> MDV Number of Missing Data Points (MDV==1 and EVID==0) 1 0
#>
#> MDV Number of Missing Data Points (MDV==1 and EVID==0) 2 99
#>
#> MDV Number of Missing Data Points (MDV==1 and EVID==0) 3 0
#>
#> MDV Number of Missing Data Points (MDV==1 and EVID==0) 4 0
#>
#> MDV Number of Missing Data Points (MDV==1 and EVID==0) 5 0
#>
#> MDV Number of Missing Data Points (MDV==1 and EVID==0) 6 0
#>
#> Dose Number of non-zero doses - 300
#>
#> Dose Number of zero doses (AMT==0) - 60
#>
#> Dose Number of patients that never received drug - 10
#>
#> DV Number of Data Points 1 360
#>
#> DV Number of Data Points 2 1309
#>
#> DV Number of Data Points 3 600
#>
#> DV Number of Data Points 4 600
#>
#> DV Number of Data Points 5 600
#>
#> DV Number of Data Points 6 600
#>
#> DV Number of Data Points per Individual 1 min = 6, median = 6, max = 6
#>
#> DV Number of Data Points per Individual 2 min = 26, median = 26, max = 27
#>
#> DV Number of Data Points per Individual 3 min = 10, median = 10, max = 10
#>
#> DV Number of Data Points per Individual 4 min = 10, median = 10, max = 10
#>
#> DV Number of Data Points per Individual 5 min = 10, median = 10, max = 10
#>
#> DV Number of Data Points per Individual 6 min = 10, median = 10, max = 10
#>
#> DV Number of Data Points with zero value (DV==0) 1 0
#>
#> DV Number of Data Points with zero value (DV==0) 2 0
#>
#> DV Number of Data Points with zero value (DV==0) 3 0
#>
#> DV Number of Data Points with zero value (DV==0) 4 75
#>
#> DV Number of Data Points with zero value (DV==0) 5 0
#>
#> DV Number of Data Points with zero value (DV==0) 6 423
#>
#> DV Number of Data Points with NA (is.na(DV)) 1 0
#>
#> DV Number of Data Points with NA (is.na(DV)) 2 8
#>
#> DV Number of Data Points with NA (is.na(DV)) 3 0
#>
#> DV Number of Data Points with NA (is.na(DV)) 4 0
#>
#> DV Number of Data Points with NA (is.na(DV)) 5 0
#>
#> DV Number of Data Points with NA (is.na(DV)) 6 0
#>
#> DV+TIME Multiple measurements at same time 1 0
#>
#> DV+TIME Multiple measurements at same time 2 32
#>
#> DV+TIME Multiple measurements at same time 3 0
#>
#> DV+TIME Multiple measurements at same time 4 0
#>
#> DV+TIME Multiple measurements at same time 5 0
#>
#> DV+TIME Multiple measurements at same time 6 0
#>
#> CENS Number of Censored Data Points 1 0 (0%)
#>
#> CENS Number of Censored Data Points 2 9 (1%)
#>
#> CENS Number of Censored Data Points 3 4 (1%)
#>
#> CENS Number of Censored Data Points 4 4 (1%)
#>
#> CENS Number of Censored Data Points 5 4 (1%)
#>
#> CENS Number of Censored Data Points 6 4 (1%)
#>
#> All Columns Negative Values (number) - DV:12
#>
#> All Columns Missing Values (number) - LIDV:368, DV:368
#> ------------------------------------------------------------------------------------------------------------
#>
#> CONTINUOUS COVARIATES
#>
#> -----------------------------------------------------------
#> Covariate Nmissing min 25th median 75th max
#> ----------- ---------- ------ ------ -------- ------- -----
#> WEIGHTB 0 52.8 69.2 78.9 89.85 109
#> -----------------------------------------------------------
#>
#> CATEGORICAL COVARIATES
#>
#> -----------------------------------------------------------
#> Covariate Nmissing Ndistinct Value (Count)
#> ----------- ---------- ----------- ------------------------
#> SEX 0 2 Female (30), Male (30)
#> -----------------------------------------------------------
#>
#> POSSIBLE DATA ISSUES - FIRST 6 RECORDS
#>
#> ----------------------------------------------------
#> Data_Check_Issue ID TIME DV CENS YTYPE
#> ------------------ ---- -------- ---- ------ -------
#> DV == 0 1 -0.005 0 0 6
#>
#> DV == 0 1 24.33 0 0 6
#>
#> DV == 0 1 48.37 0 0 6
#>
#> DV == 0 1 72.2 0 0 6
#>
#> DV == 0 1 96.26 0 0 6
#>
#> DV == 0 1 120.2 0 0 6
#> ----------------------------------------------------
#>
#> The following columns contained missing values
#> LIDV:368, DV:368