valids_test: Test for Invalid Elements in Data
In quest: Prepare Questionnaire Data for Analysis

Description Usage Arguments Value See Also Examples

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.

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

`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.

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].

valid_test revalids revalid

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