In many situations in demography and the social sciences. however, we have a dependent variable, Y, that is dichotomous Lecture 10 rather than continuous, e.g., whether or not a woman has had a second birth whether nd birth is a male or a female baby, whether or not a woman uses any contraceptive method, whether or not a person Logistic regression has migrated in the last 5 years, whether or the People's University staff uses public transportation coming to work, whether or not an under-graduate student completed study last year in the Demography Department in People's University was awarded BA degree Why use logistic regression? In all these situations the outcome ofy In linear regression alue 1 represents yes, or a"success, and the value o no or a failure the +bX1+b2x2+…+bxn+e mean of this dichotomous(also referred to binary) dependent variable, designated the dependent variable, Y, is conti p, is the proportion of times that it takes and unbounded and we want to value 1 set of explanatory(independent, or X) variables that will assist us in predicting its mean value while explaining its observe variability1 1 Lecture 10 Logistic Regression 2 Why use logistic regression? In linear regression: Y =b0 + b1X1 + b2X2 + .... + bnXn + e the dependent variable, Y, is continuous and unbounded, and we want to identify a set of explanatory (independent, or X) variables that will assist us in predicting its mean value while explaining its observed variability 2 3 In many situations in demography and the social sciences, however, we have a dependent variable, Y, that is dichotomous, rather than continuous, e.g., whether or not a woman has had a second birth, whether the second birth is a male or a female baby, whether or not a woman uses any contraceptive method, whether or not a person has migrated in the last 5 years, whether or not the People’s University staff uses public transportation coming to work, whether or not an under-graduate student completed study last year in the Demography Department in People’s University was awarded BA degree, etc. 4 In all these situations, the outcome of Y only assumes two forms; usually, the value 1 represents yes, or a “success,” and the value 0, no, or a “failure.” The mean of this dichotomous (also referred to as binary) dependent variable, designated p, is the proportion of times that it takes the value 1