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About Binary logistic regression Analysis [message #11738] 
Mon, 06 February 2017 00:40 
Mohammad Nazmul Hoq
Messages: 4 Registered: May 2016 Location: Chitagong

Member 


Hello
I am working on BDHS2011 data set. My topic is fertility analysis. For this I consider Number of living children as dependent variable. There are so many independent variables like as, respondents education, wealth index, husbands education, access to mass media etc. One of my analysis is binary logistic regression analysis. For this I prepare the data set in different parity (Parity one(1) indicates those respondents having one child, parity two(2) indicates those having two child's and so on). My question is whether the analysis is correct if I consider in binary logistic analysis (in parity 1) o for those having no child and 1 those having one child. Again in Parity 2, 0 for those having no child and 1 those having two child. Similarly for other parity.
Please reply my answer as quick as possible.
Thank you
Md. Nazmul Hoq



Re: About Binary logistic regression Analysis [message #11745 is a reply to message #11738] 
Mon, 06 February 2017 09:52 
LizDHS
Messages: 1333 Registered: February 2013

Senior Member 


A response from Dr. Tom Pullum,
Quote:
This is potentially a more difficult question than you may realize. There are several different possibilities. You could perhaps construct a set of binary variables Yk, for k=0,1,2,3,4..... as follows. Yk=0 for women with k children; Yk=1 for women with more than k children; Yk="." for women with fewer than k children. You would then be describing the probability of going from parity k to parity k+1. This would be better for number of children ever born than for number of living children. Logit regression is not well suited for an outcome that is a count. Another possibility would be to use poisson regression or negative binomial regression. There is not a general agreement on a single way to analyze this outcome.








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