# 332 and the confidence interval is 0210 0524 however

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0.332 and the confidence interval is (0.210, 0.524). However, after adding age and BMI to the model the odds ratio for sex reduced to 0.274 (from 0.332). The confidence interval (0.166, 0.450) also become slightly wider. 4. Assess the statistical significance of the individual risk factors and explain the practical implication of your finding. (5 points) Sex, age, and BMI are statistically significant in the model. This means each of these variable can (to a statistically significant level) affect the odds of having coronary heart disease. The odds ratio for sex shows that males have (1/0.274 = ) 3.65 times higher odds of having coronary heart disease compared to the females. In other words, females have 3.65 times lower odds of having coronary heart disease compared to the males. If all other factors remain constant, for every unit increase in age there is 1.052 units increase in the odds of having coronary heart disease. In a similar way, given that all other

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factors remain constant, for every unit increase in BMI there is 1.133 units increase in the odds of having coronary heart disease.
IV. Cox Proportional Hazard (25 points) The Final Exam – Linear and Logistic (SPSS document) dataset , used in problems III and IV, also includes follow-up time (in days) from the beginning of the study to either onset of coronary heart disease or end of the study. This allows you to also look at the relationship of sex to CHD using survival analysis techniques. 1. Complete a Kaplan-Meier Survival Analysis using Followup as the Time variable, Chdfate as the status variable and Sex as the factor. Produce a plot of the survival function. Discuss whether the survival time appears related to whether the person is male or female based on the survival plot. (8 points)

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CORRECT ANALYTIC GRAPH for part 1
(-4) The survival function shows that sex has effect on the survival time. Overall, males have lower survival time compared to the females. This is evident from the rapid downward slope of the male’s cumulative survival compared to the female’s cumulative survival curve. In other words, males are more likely to develop coronary heart disease early/within the follow-up period. 2. Use Kaplan-Meier in SPSS to test the assumption of proportionality. Create a Hazard plot with time = followed, status=Chdfate, and factor = sex. Interpret the results. (6 points)

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The assumption of proportionality of hazards is met. This is because the ratio of the hazards in men to the hazards in women appears to be relatively constant through the follow-up period. This means that the hazards are proportional.
3. Conduct a Cox Proportional Hazard regression to compare the time to coronary heart disease event between men and women. Include a Plot of the Hazards function stratified by sex in the output. Interpret the results. (8 points) Variables in the Equation B SE Wald df Sig. Exp(B) 95.0% CI for Exp(B) Lower Upper sex -.861 .199 18.709 1 .000 .423 .286 .624

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The Cox proportional hazards model shows that sex have statistically significant (p < 0.05) effect on the hazards of developing coronary heart disease. The hazards ratio for sex shows that males have (1/0.423 =) 2.36 times higher hazards of developing coronary heart disease
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