Tweedie Distribution in Statistical Modelling of Infant Survival Time
This article examines the relevance of some of the determinants of Infant survival time for all Indian states using data from NFHS- 3. It explores the socio-cultural, biological and demographic factors which may affect the IMR and it’s hoped that it can be explained in terms of residence, religion, gender, Mother’s age, birth order, birth weight of infant, age at first marriage – all these variables are highly associated with child mortality. So far research studies have used GLM based on log Gaussian and Gamma distribution (Mc Cullagh and Nelder (1989)) to identify the risk factors of child mortality. These models fail to capture the non-zero probability of zero occurrence of an event. Tweedie distribution (Tweedie (1984), Jorgensen (1997) has the potential to model both discrete and continuous processes. In this paper an attempt is made to demonstrate the efficiency of Tweedie modelling over other GLM’s. A detailed map of India highlighting the significant predictors identified by the Tweedie and Gamma models across all states is also presented.
Disclaimer/Regarding indexing issue:
We have provided the online access of all issues and papers to the indexing agencies (as given on journal web site). It’s depend on indexing agencies when, how and what manner they can index or not. Hence, we like to inform that on the basis of earlier indexing, we can’t predict the today or future indexing policy of third party (i.e. indexing agencies) as they have right to discontinue any journal at any time without prior information to the journal. So, please neither sends any question nor expects any answer from us on the behalf of third party i.e. indexing agencies.Hence, we will not issue any certificate or letter for indexing issue. Our role is just to provide the online access to them. So we do properly this and one can visit indexing agencies website to get the authentic information.