Are there tricky aspects of NAPP data to be particularly aware of?
It is important to examine the documentation for the variables you are using. The codes and labels for variable categories do not tell the whole story. In other words, the syntax labels are not enough. Read the variable comparability discussions for the samples you are interested in. Important comparability issues should be mentioned there. If a variable is of particular importance in your research (for example, it is your dependent variable), you are also well served to read the enumeration text associated with it. This text is linked directly to the variable, so it is quite easy to call it up.
By default, the extract system rectangularizes the data: it puts the household information on the person records and drops the separate household record. This can distort analyses at the household level. The number of observations will be inflated to the number of person records. You can either select the first person in each household (PERNUM) or select the “hierarchical” box in the extract system to get the proper number of household observations. The rectangularizing feature also drops any vacant households, which are otherwise available in some samples. Despite these complications, the great majority of researchers prefer the rectangularized format, which is why it is the default output of our system.