Network analysis is becoming a popular interdisciplinary research area in computer science, statistics, sociology, political science, and psychology. To better analyze social network data for psychological research, we propose to combine psychometric models with social network techniques. In this talk, I will present three studies to show the advantages of such combinations. In the first study, we investigate the relationship between the personality factor space and a friendship network by combining a factor model and a latent space model. In the second study, we expand the traditional mediation model to study the mediation role of a friendship network in understanding sex differences in smoking. In the third study, we use a growth curve model to investigate the longitudinal change of friendship networks. I will end my talk by discussing a general psychometric modeling framework for social network data analysis.