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Check a GADSdat for large labeled whole-number values.

Source: R/checkIntOverflow.R
checkIntOverflow.Rd

Check a GADSdat object for any occurrences of labeled whole-number values that would be too large for R to handle if they were coerced as.integer().

Usage

checkIntOverflow(GADSdat)

Arguments

GADSdat

A GADSdat object.

Value

Returns a data.frame, listing the affected varNames, the large whole-number values, their respective missings tags, and whether they actually occur in the data (empty). The rownums of the affected rows in GADSdat$labels are also provided in a separate column as a fail safe.

Details

According to its documentation, R can only handle integer values of up to (roughly) \(\pm 2 \times 10^9\) (2,147,483,647 to be exact; c.f. .Machine$integer.max). This restriction is relevant when exporting a GADSdat to .dta and only when any value exceeding the limit is also labeled (or tagged as missing). This is because Stata only accepts labeled integer (not labeled floating-point; c.f. checkLabeledFractionals() in this package) values. haven's write_dta function will therefore try to coerce any labeled values as.integer(). Unlabeled values, however, will stay generic numeric values that have a higher limit.

See also

Other dataset compliance checks: checkLabeledFractionals(), getProgramLimit()

Examples

# Introduce a fractional value into meta data
pisa2 <- changeMissings(GADSdat = pisa,
                        varName = "schtype",
                        value = 9999999999,
                        missings = "miss")
checkIntOverflow(pisa2)
#>   varName value missings empty rownum
#> 1 schtype 1e+10     miss  TRUE      7