Filter the final result of the object lab

# S3 method for lab
choose_test(obj, test = "mis", group_id = T)

Arguments

obj	An object. Class lab.
test	A character scalar. Parameters, which use to filter the final dataset, default: "mis": "ok" - analysis, which has a correct estimate of the result, "mis" - analysis, which has an incorrect estimate of the result, "skip" - analysis, which has an empty value of the estimate, "null" - analysis, which has an empty result and value of the estimate.
group_id	A logical scalar, default is TRUE.True is grouped by id, otherwise, it isn't grouped.

Value

The filtered dataset by a value of test.

Examples

ID <- c("01", "02", "03")
SITE <- c("site 01", "site 02", "site 03")
AGE <- c("19", "20", "22")
SEX <- c("f", "m", "f")
GLUC_V1 <- c(5.5, 4.1, 9.7)
GLUC_IND_V1 <- c("norm", "no", "cl")
AST_V2 <- c("30", "48", "31")
AST_IND_V2 <- c(NA, "norm", "norm")

df <- data.frame(
  ID, SITE, AGE, SEX,
  GLUC_V1, GLUC_IND_V1,
  AST_V2, AST_IND_V2,
  stringsAsFactors = FALSE
)

refs <- system.file("labs_refer.xlsx", package = "dmtools")
obj_lab <- lab(refs, ID, AGE, SEX, "norm", "no")

obj_lab <- check(obj_lab, df)
choose_test(obj_lab, "mis")
#>   ID AGE SEX                 LBTEST LBTESTCD VISIT LBORNRLO LBORNRHI LBORRES
#> 1 02  20   m                Glucose     GLUC   _V1      3.9      5.9     4.1
#> 2 02  20   m Aspartate transaminase      AST   _V2      0.0     42.0      48
#> 3 03  22   f                Glucose     GLUC   _V1      3.9      5.9     9.7
#>   LBNRIND RES_TYPE_NUM IND_EXPECTED
#> 1      no          4.1         norm
#> 2    norm         48.0           no
#> 3      cl          9.7           no