We investigated threats to the accuracy of analyses by subjecting all variables to graphical and statistical analyses. For each self-report variable in the analysis, fewer than 5% of cases had missing data. Peer data were available for slightly more than 40% (n=258 for IPIP-N and Big 5, and n=253 for the BIS) of the participants. We assumed that data in these analyses were missing at random. We used Mplus (Muthén & Muthén, 1998-2007) for data analysis, which provides maximum likelihood estimates for parameters when data are missing at random. We followed recommendations by Winship and Radbill (1994) and did not weight cases in most of our analyses. However, weighted analyses yielded almost identical results to unweighted analyses.
