Who Can You Count On? Understanding The Determinants of Reliability

Using reinterview data from the PATH Reliability and Validity (PATH-RV) study, we examine the characteristics of questions and respondents that predict the reliability of the answers. In the PATH-RV study, 524 respondents completed an interview twice, five to twenty-four days apart. We coded a number of question characteristics and used them to predict the gross discrepancy rates (GDRs) and kappas for each question. We also investigated respondent characteristics associated with reliability. Finally, we fitted cross-classified models that simultaneously examined a range of respondent and question characteristics. Although the different models yielded somewhat different conclusions, in general factual questions (especially demographic questions), shorter questions, questions that did not use scales, those with fewer response options, and those that asked about a noncentral topic produced more reliable answers than attitudinal questions, longer questions, questions using ordinal scales, those with more response options, and those asking about a central topic. One surprising finding was that items raising potential social desirability concerns yielded more reliable answers than items that did not raise such concerns. The respondent-level models and cross-classified models indicated that five adult respondent characteristics were associated with giving the same answer in both interviews-education, the Big Five trait of conscientiousness, tobacco use, sex, and income. Hispanic youths and non-Hispanic black youths were less likely to give the same answer in both interviews. The cross-classified model also found that more words were associated with less reliable answers. The results are mostly consistent with earlier findings but are nonetheless important because they are much less model-dependent than the earlier work. In addition, this study is the first to incorporate such personality traits as needed for cognition and the Big Five personality factors and to examine the relationships among reliability, item nonresponse, and response latency.