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1 “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
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2 Introduction Prior Studies Data and Methods Results Kaplan-Meier Survival Curves Cox Proportional Hazard Regression Adjusted Cox Survival Curves Conclusion
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S(t) = The Kaplan-Meier estimator of surviving beyond time t (i.e., not dying):
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4 Cox Proportional Hazard Regression: log h(t) = log h 0 (t) + b 1 x 1 +... + b k x k where: h 0 (t) is an unspecified function of time t, x 1 to x k are sociodemographic co-variates (independent variables), and b 1 to b k are the Cox parameters to be estimated.
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5 Figure 1. Kaplan-Meier Survival Curve of the Probability of Surviving Death by Month: 8,131 Oldest Old Persons, China, 1998-2000
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6 Χ 2 = 7.27, P =.007 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
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7 Χ 2 = 1.40, P=.237 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
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8 Χ 2 = 35.96, P =.000 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
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9 Χ 2 = 37.89, 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
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10 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 Χ 2 = 896.00, P =.000 77-79 90-99 80-89 100+
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11 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 VariableCoefficient 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
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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.
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13 Figure 7. Adjusted Cox Proportional Hazard Survival Curve of the Probability of Surviving Death by Month: 8,131 Oldest Old Persons, China, 1998-2000
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14 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
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15 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
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16 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
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17 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
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18 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+
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19 End of Presentation
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