Journal of Data Science

Abstract: Background: Brass developed a procedure for converting proportions dead of children ever born reported by women in childbearing ages into estimates of the probability of dying before attaining certain exact childhood ages. The method has become very popular in less developed countries where direct mortality estimation is not possible due to incomplete death registration. However, the estimates of q(x), the probability of dying before age x, obtained by Trussell’s variant of Brass method are sometimes unrealistic, q(x) being not monotonically increasing for increasing x. Method: State level child mortality estimates obtained by Trussell’s variant of Brass method from 1991 and 2001 Indian census data were made monotonically increasing by logit smoothing. Using two of the smoothed child mortality estimates, infant mortality estimate is obtained by fitting a two parameter Weibull survival function. Results: It has been found that in many states and union territories infant mortality rates have increased between 1991 and 2001. Cross checking with the 1991 and 2001 census data on the increase/decrease of percentage of children died establishes the reliability of the estimates. Conclusion: We have reason to suspect the trend of declining infant mortality as shown by the different agencies and researchers.

In this paper an attempt has been made to analyze the child mortality by use of a hazard model in Bayesian environment, family effect through multiplicative random effect is also incorporated in the model. For fitting this model real data has taken from District Level Household and Facility Survey (DLHS)-3. The largest state (in population) of India i.e. Uttar Pradesh data is taken for analysis. Deviance information criteria are used for comparison of models. It found that the model with family frailty gives better fit. All the analysis is performed in winBUGS software, which is used Markov chain monte carlo simulation under gibbs sampling.