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

25 September 2019
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ASA Conference 2019 - Statistics for Health and Well-being
Conference of the Applied Statistics Association.

Infertility is a major psychosocial crisis as well as being a medical problem. The factors that predict psychosocial consequences of infertility may vary in different gender, education level, socio-economic status. The primary purpose of this study was to investigate the relationship between sociodemographic 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.

This paper analyses these components by means of a mixture model for ordinal rating responses, allowing for uncertainty in answering (Piccolo, 2003). In responding to rating questions as the latent components which lead the perception of depression and/or anxiety, an individual may give answers either according to his/her feeling or to his/her level of indecision, typically motivated by a response style. Since ignoring this uncertainty may lead to misleading results, 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 (see Kenny et al. (2006), among others).

The effectiveness of the model is attested through the analysis of a cross-sectional study of 206 infertile couples interviewed from 2014 to 2016. A gynecologist evaluated participants for demographic and medical data and then they were visited by a psychologist to perform questionnaire scales which were the Dyadic Adjustment Scale, the Edinburgh Depression Scale and the State-Trait Anxiety Inventory for the evaluation of the perceived levels of psychological disease (Zurlo et al, 2018, 2017).

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