A mixture model with discrete variables for depression diagnosis in infertile couples

Infertility is a major psycho–social crisis as well as being a medical problem. The factors that predict psycho–social consequences of infertility may vary in different gender, education level, socio-economic status. The primary purpose of this study was to investigate the relation- ship between socio-demographic characteristics and levels of depression and anxiety in infertile couples by exploring the role of each partner and of the related perceived levels of depression and of quality of dyadic adjustment. The perception of depression and/or anxiety are typically evaluated through latent components. This paper analyses these components by means of a mixture model for ordinal rating responses, allowing for uncertainty in answering. In responding to rating questions, indeed, an individual may give answers either according to her/his feeling or to her/his level of indecision, typically motivated by a response style. Since ignoring the uncertainty may entail misleading re- sults, we define the distribution of the ordinal responses via a mixture model which weights both components in answering. The study allows also to model the actor/partner interdependence in case of categorical dyadic data by presenting an alternative approach with respect to the current used methods. The effectiveness of the model is attested through the analysis of a cross-sectional study of infertile couples. The research aims to test and to evaluate the effects that some aspects linked to the couple’s relationship in infertile dyads have on depressive experience for both partners. It points out the role played by marital adjustment perceived by the wives in the definition of depressive symptoms of husbands, and vice versa. Specifically, the study is designed to measure interdependence within interpersonal relationship, that is when one person’s emotion, cogni- tion, or behaviour affects the emotion, cognition, or behaviour of the partner. One of the consequences is that observations of the two individuals are linked or correlated such that knowledge of one person’s score provides information about the other individual’s score.