quest (version 0.2.0)

valids_test: Test for Invalid Elements in Data

Description

Valid.test tests whether data has any invalid elements. Valid values are specified by valid. Each variable is tested independently. If the variable in data[vrb.nm] has any values other than valid, then FALSE is returned for that variable; If the variable in data[vrb.nm] only has values in valid, then TRUE is returned for that variable.

Usage

valids_test(data, vrb.nm, valid, na.rm = TRUE)

Value

logical vector with length = length(vrb.nm) and names =

vrb.nm specifying whether all elements in each variable of

data[vrb.nm] are valid. If FALSE, then (at least one) invalid values are present in that variable of data[vrb.nm].

Arguments

data

data.frame of data.

vrb.nm

character vector of colnames from data specifying the variables

valid

atomic vector or list vector of valid values.

na.rm

logical vector of length 1 specifying whether NA should be ignored from the validity test. If TRUE (default), then any NAs are treated as valid.

See Also

valid_test revalids revalid

Examples

valids_test(data = psych::bfi, vrb.nm = names(psych::bfi)[1:25],
   valid = 1:6) # return TRUE
valids_test(data = psych::bfi, vrb.nm = names(psych::bfi)[1:25],
   valid = 0:5) # 6 is not present in `valid`
valids_test(data = psych::bfi, vrb.nm = names(psych::bfi)[1:25],
   valid = 1:6, na.rm = FALSE) # NA is not present in `valid`
valids_test(data = ToothGrowth, vrb.nm = c("supp","dose"),
   valid = list("VC", "OJ", 0.5, 1.0, 2.0)) # list vector as `valid` to allow for
   # elements of different typeof