Khalkhali H, Haji Nejad E, Mohammad K,
Volume 59, Issue 1 (7 2001)
Abstract
Difference aspects of multinomial statistical modelings and its classifications has been studied so far. In these type of problems Y is the qualitative random variable with T possible states which are considered as classifications. The goal is prediction of Y based on a random Vector X ? IR^m. Many methods for analyzing these problems were considered. One of the modern and general method of classification is Classification and Regression Trees (CART). Another method is recursive partitioning techniques which has a strange relationship with nonparametric regression. Classical discriminant analysis is a standard method for analyzing these type of data. Flexible discriminant analysis method which is a combination of nonparametric regression and discriminant analysis and classification using spline that includes least square regression and additive cubic splines. Neural network is an advanced statistical method for analyzing these types of data. In this paper properties of multinomial logistics regression were investigated and this method was used for modeling effective factors in selecting contraceptive methods in Ghom province for married women age 15-49. The response variable has a tetranomial distibution. The levels of this variable are: nothing, pills, traditional and a collection of other contraceptive methods. A collection of significant independent variables were: place, age of women, education, history of pregnancy and family size. Menstruation age and age at marriage were not statistically significant.
Rahnavard Z, Heidarnia A, Babaei Gh, Mahmoodi M, Khalkhali H,
Volume 59, Issue 5 (9 2001)
Abstract
Population growth has been one of the main anxieties of different countries planners so far. Background and purpose growth of population has always had various impacts on society in economical, social, health and even political fields and its cure is controlling population growth. In order to study the efficient factors upon unwanted children, 1527 married women in Tehran have been randomly selected and data from questionnaire was selected. In this study, effective factors such as couple's education level, couple's occupation, number of children, age of marriage, age of last pregnancy, having stillbirth, breast feeding period in last born and effect of sex of infant in family planning upon unwanted children have been studied. Results show that some factors like husband's age, number of children, age of first marriage, age of last pregnancy, husband occupation, having stillbirth, breast feeding period and effect of infant's sex in family planning increase the chance of unwanted children and some criteria like women age, woman's education, fist pregnancy age, woman occupation, decrease the chance of unwanted children. According to logistic regression model, women age is one of the most important effective factors and one year increment in woman's age increase the chance of unwanted child 0.89 more times. Other factors is the number of children that in return for increasing one child to family, the chance of un wanting become 116.8 more times. It seems families don't have enough knowledge about family planning measures and their usage. Breast feeding period in wives who have fed their last children for more than six months, is another important factor which increases the chance of unwanted child to 1.02 more times than woman who have fed their last children for less than six months.
