Jorjani Biomedicine Journal

---

Background and Objective: Discriminant analysis and logistic regression are classical methods for classifying data in several studies. However, these models do not lead in valid results due to not meeting all necessary assumptions. The purpose of this study was to classify the number of Children Ever Born (CEB) using decision tree model in order to present an efficient method to classify demographic data.

Methods: In the present study, CART tree model with Gini splitting rule was fitted to classify the number of CEB in fertility behavior of at least once married 15-49 year-old women, in Semnan-2012. 405 women aged 15-49 years old comprised the survey sample.

Results: Women in first and second birth cohorts who had married at an early age had 3 CEB while women who had married at an older age had 2 CEB. Women in third birth cohort who had married at an early age and were employed, had 2 CEB while unemployed women in this cohort whose type of marriages were familial and non-familial had 0 and 1 CEB respectively. Women in the third birth cohort who were married in older age had 1 CEB.

Conclusion: Among important advantages of CART model are the simplicity in interpretation, using distribution-free measures, considering missing data and outliers for construction trees which has increased the usage of this method. Therefore, this method is a suitable way for classifying demographic data in comparison to other classical modeling methods in the conditions that necessary assumptions are not met.

---

---

Background and objectives: Birth spacing is an important variable for identification of fertility acceleration, total fertility rate, and maternal and fetal health. Therefore, special attention has been paid to this issue by researchers in the fields of medical sciences, health, and population. In addition, proper analysis of this concept is of foremost importance. Application of classical analytical techniques with no attention to their assumptions (e.g., independence of events) is associated with inefficient results. As such, this study aimed to present frailty models as effective models for this analysis.
Methods: Frailty models consider the dependence between unobserved intervals and dispersions by exerting a random impact on the model. Different types of these models include shared, conditional, correlated and time-dependent frailty, each of which along with their applications were presented in the current research using two examples. Results: In practice, the shared frailty model is highly applied due to its simplicity. Nevertheless, since most of the unknown factors affecting the birth spacing are not common between different births, the shared frailty models must be used with caution.
Conclusion: Use of classical statistical methods, such as the Cox proportional hazards model, the important assumption of which is the dependence of events occurred, is not appropriate for the accurate analysis of birth spacing. On the other hand, frailty models consider the correlation between the intervals and are an effective method for analysis of birth spacing, use of which is recommended to researchers in fields of medicine and population.

---

---

Background: Divorce, as an important social harm, is associated with anxiety, fear, and feelings of helplessness and loneliness, leading to changes in behavior, financial status, and lifestyle, has always been the focus of investigators and policymakers. Since women are more affected by divorce than men, and children also play a decisive role in divorce decisions, the purpose of this article was to study the marital durability of women with children based on selected covariates.
Methods: The current study is a secondary analysis of the divorce survey data conducted by the National Organization for Civil Registration in 2016-2017. Information was collected through questionnaires from 756 women who had filed for divorce at divorce registration offices. An unshared frailty survival model was applied for analyzing this data using SAS software.
Results: In this study, 29.5%, 52.9%, and 11.8% of women had 1, 2, and 3 or more children, and the first marriage longevity (FML) medians among these women were 150.45, 221.13, and 343.20 months, respectively. An unshared Gamma frailty Weibull model was selected as the final model for analyzing the data. The variables of the human development index (AF=0.312), women’s and their spouses’ marriage age (AF=0.985, 0.992), the first child’s age (AF=0.938), educational years (AF=1.121), number of children (AF=1.03), number of spouse's siblings (AF=1.018), father's survival status (AF=0.963), and child’s custody status (AF=1.093) were found to significantly affect the FML of these women.
Conclusion: Based on the results, children can play positive or negative roles in women’s divorce; as the number of children increased, women’s FML also increased. On the other hand, as the age of women’s first child increased, the divorce risk also increased.