scholarly journals Proportional Hazards Models for Current Status Data: Application to the Study of Differentials in Age at Weaning in Pakistan

Demography ◽  
1986 ◽  
Vol 23 (4) ◽  
pp. 607 ◽  
Author(s):  
Ian D. Diamond ◽  
John W. McDonald ◽  
Iqbal H. Shah
Keyword(s):  
Proportional Hazards ◽  
Current Status Data ◽  
Current Status ◽  
Proportional Hazards Models ◽  
Data Application ◽  
Status Data

Social and economic factors related to breast-feeding durations in Tanzania

1996 ◽  
Vol 28 (3) ◽  
pp. 347-354 ◽  
Author(s):  
P. R. Andrew Hinde ◽  
Akim J. Mturi
Keyword(s):  
Urban Area ◽  
Breast Feeding ◽  
Proportional Hazards ◽  
Current Status Data ◽  
Current Status ◽  
Economic Factors ◽  
Region Of Residence ◽  
Mother And Child ◽  
Proportional Odds Models ◽  
Status Data

SummarySome social and economic factors related to breast-feeding durations in Tanzania are analysed using current status data taken from the 1991–92 Tanzanian Demographic and Health Survey. Proportional hazards and proportional odds models are estimated. The results show that breast-feeding durations vary according to the region of residence of the mother and child (and whether they are living in a rural or an urban area), the age of the mother at the time of the birth, the order of the birth, and the mother's religion.

PENALIZED LOG-LIKELIHOOD ESTIMATION FOR COX-FRAILTY MODEL WITH NONINFORMATIVE BIVARIATE CURRENT STATUS DATA

2021 ◽  
pp. 16-27
Author(s):  
Alhassan Faisal
Keyword(s):  
Variance Estimation ◽  
Proportional Hazards ◽  
Likelihood Estimation ◽  
Frailty Model ◽  
Cox Proportional Hazards ◽  
Current Status Data ◽  
Current Status ◽  
Hazard Functions ◽  
Failure Times ◽  
Status Data

A Penalized Maximum Likelihood Estimation (PMLE) procedure is proposed for Cox proportional hazards frailty model with noninformative bivariate current status data. An integrated splines (I-splines) was used to approximate the two unknown baseline cumulative hazard functions of the failure times. The one-parameter gamma frailty distribution was used to model the correlation between the two failure times. An easy to implement computational algorithm is proposed to estimate the regression and splines parameters. Bayesian technique as proposed by Wahba (1983) was employed for the variance estimation. The statistical properties of the estimated parameters were studied through extensive simulation and it was observed that the PMLEs were consistent, asymptotically normal and efcient. In addition, the estimators were robust to the choice of knots, censoring rates and type of frailty distribution used. The proposed methodology is further demonstrated through the analysis of the tumorigenicity experiment data by Lindsey and Ryan (1994).

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