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“The Effects of Sociodemographic Factors on the Hazard of Dying Among Aged Chinese Males and Females” Dudley L. Poston, Jr. and Hosik Min Department of Sociology Texas A&M University College Station, Texas 77843 dudleyposton@yahoo.com. Introduction Prior Studies Data and Methods
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“The Effects of Sociodemographic Factors on the Hazard of Dying Among Aged Chinese Males and Females” Dudley L. Poston, Jr. and Hosik Min Department of Sociology Texas A&M University College Station, Texas 77843 dudleyposton@yahoo.com
Introduction Prior Studies Data and Methods Results Kaplan-Meier Survival Curves Cox Proportional Hazard Regression Adjusted Cox Survival Curves Conclusion
The Kaplan-Meier estimator of surviving beyond time t (i.e., not dying): S(t) =
Cox Proportional Hazard Regression: log h(t) = log h0(t) + b1x1 + ... + bkxk where: h0(t) is an unspecified function of time t, x1to xk are sociodemographic co-variates (independent variables), and b1to bk are the Cox parameters to be estimated.
Figure 1. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month: 8,131 Oldest Old Persons, China, 1998-2000
Figure 2. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Males and Females: 8,131 Oldest Old Persons, China, 1998-2000 Male Female Χ2 = 7.27, P = .007
Figure 3. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Han and non-Han: 8,131 Oldest Old Persons, China, 1998-2000 Non-Han Han Χ2 = 1.40, P= .237
Figure 4. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Rural and non-Rural Residents: 8,131 Oldest Old Persons, China, 1998-2000 Non-Rural Rural Χ2 = 35.96, P = .000
Figure 5. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Rural Birth and non-Rural Birth: 8,131 Oldest Old Persons, China, 1998-2000 Non-Rural Birth Rural Birth Χ2 = 37.89, P = .000
Figure 6. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month, Four Age Groups: 8,131 Oldest Old Persons, China, 1998-2000 77-79 80-89 90-99 100+ Χ2 = 896.00, P = .000
Table 1. Cox Proportional Hazard Model Estimates of the Effects of Sociodemographic Co-variates, on the Hazard of Dying: 8,131 Oldest Old Persons, China, 1998-2000 Hazard Hazard Semi-Standardized Variable Coefficient Ratio Hazard Ratio Female -0.27* 0.76 0.88 Han 0.13* 1.13 1.03 Rural Residence 0.04 1.04 1.02 Rural Birth 0.13* 1.14 1.05 Education (years) 0.00 1.00 1.00 Never Married 0.08 1.08 1.01 Separated/Divorced 0.20 1.22 1.03 Widowed 0.43* 1.53 1.18 Age group 0.60* 1.83 1.65 Final Log Likelihood = -28468.04 Likelihood Ratio 2 = 947.88, P = .000 *significant at p<0.05, one-tailed test
Cox proportional hazard model survival curve that adjusts for the co-variates in the Cox model: where the predicted survival function at time t is given by a baseline survival function raised to a power equal to the exponential of the sum of the predicted Cox parameters times the mean values of the co-variates.
Figure 7. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month: 8,131 Oldest Old Persons, China, 1998-2000
Figure 8. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Males and Females: 8,131 Oldest Old Persons, China, 1998-2000 Female Male
Figure 9. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Han and non-Han: 8,131 Oldest Old Persons, China, 1998-2000 Non-Han Han
Figure 10. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Rural and non-Rural Residents: 8,131 Oldest Old Persons, China, 1998-2000 Non-Rural Rural
Figure 11. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Rural Birth and non-Rural Birth: 8,131 Oldest Old Persons, China, 1998-2000 Non-Rural Birth Rural Birth
Figure 12. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month, Four Age Groups: 8,131 Oldest Old Persons, China, 1998-2000 77-79 80-89 90-99 100+