The use of a multinomial logistic regression model in analyzing the characteristics of married women using family planning methods in Iraq 2018 * - Suhair Jameel Mushrif Al-Neyazy, (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
Family planning allows for the spacing of births, which has a positive impact in reducing such cases. We find that about (43.5%) of currently married women in Iraq use family planning methods in 2000 and that percentage rose to (52.8%) in (2018), an increase of about (22%), on the other hand, unmet need rose from (8%) in (2000) to (14.3%) in (2018), (World Bank, 2020). The study aims to identify the determinants of using family planning methods among currently married Iraqi women in the age group (15-49) years, for a sample of (18,306) women through the Multiple Indicator Cluster Survey of (2018) in Iraq. The dependent variable in this study is the use of family planning methods, which has three levels (1 = do not use, 2 = use a traditional method, 3 = use a modern method). Therefore, the Multiple Multinomial Logistic Regression Model was used to find the best prediction of a model describing the relationship between the dependent variable and the independent variables in this study using family planning methods based on independent variables. Where the model parameters were estimated by resorting to the maximum likelihood method, which is the most appropriate method for all linear and nonlinear models, through which two equations parameters were best estimated: the model (using traditional family planning methods versus non-use), and the model (using traditional family planning methods versus non-use). Modern family planning versus no use) of the transactions through which the data were interpreted. * This paper is derived from a master's thesis entitled "Using a multifaceted logistic regression model in analyzing the determinants of the use of family planning methods in Iraq" by Suhair Jameel Mushrif Al-Neyazy / University of Baghdad. Under the supervision of P.Dr. Zuhdi Muhammad Nofal and Dr. Wafaa Abdel Aziz Hussein.