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@N-thony The partial label featyre you added is designed for situations where there are more (numerical) values than value labels.
The other way round, namely more labels than levels is quite common and is different and should not be included. That's when there are extra factor levels with zero frequency and we handle that differently.
I found this problem with IPUMS data, where they are from one country, but the labels gives all the possible countries. You must be doing a check somewhere for not equal, when ut should be that that there are more values in the data than in the labels.
The text was updated successfully, but these errors were encountered:
@N-thony The partial label featyre you added is designed for situations where there are more (numerical) values than value labels.
The other way round, namely more labels than levels is quite common and is different and should not be included. That's when there are extra factor levels with zero frequency and we handle that differently. I found this problem with IPUMS data, where they are from one country, but the labels gives all the possible countries. You must be doing a check somewhere for not equal, when ut should be that that there are more values in the data than in the labels.
@N-thony The partial label featyre you added is designed for situations where there are more (numerical) values than value labels.
The other way round, namely more labels than levels is quite common and is different and should not be included. That's when there are extra factor levels with zero frequency and we handle that differently.
I found this problem with IPUMS data, where they are from one country, but the labels gives all the possible countries. You must be doing a check somewhere for not equal, when ut should be that that there are more values in the data than in the labels.
The text was updated successfully, but these errors were encountered: