Oversampling and cluster sampling must be addressed when analyzing complex sample data. This study: (a) compares parameter estimates when applying weights versus not applying weights; (b) examines subset selection issues; (c) compares results when using standard statistical software (SPSS) versus specialized software (AM); and (d) offers recommendations for analyzing complex sample data. Underestimated standard errors and overestimated test statistics were produced when both the oversampled and cluster sample characteristics of the data were ignored. Regarding subset analysis, marked differences were not evident in SPSS results, but the standard errors of the weighted versus unweighted models became more similar as smaller subsets of the data were extracted using AM. Recommendations to researchers are provided including accommodating both oversampling and cluster sampling.