2. The SPSS outputs below are from two logistic regression models fitted to data on all SARS cases in Taiwan with status =1 meaning the patient died and =0 survived, agemid = midpoint of the age group to which the patient belonged, gender =0 for females and 1 for males. Variables in the Equation Variables in the Equation (a) From the simple logistic regression (first table), with status as the outcome variable and gender as the predictor variable (female as baseline), is there a statistically significant difference in mortality between males and females? What is the odds ratio (males: females) for mortality? (b) From the multiple logistic regression with both gender (female as baseline) and agemid as predictors (second table), what is the adjusted odds ratio (males:females) for mortality? Is the difference in mortality between males and females statistically significant adjusted for other variables in the model? How would you explain the change in the coefficient of gender between the two models? 2. The SPSS outputs below are from two logistic regression models fitted to data on all SARS cases in Taiwan with status =1 meaning the patient died and =0 survived, agemid = midpoint of the age group to which the patient belonged, gender =0 for females and 1 for males. Variables in the Equation Variables in the Equation (a) From the simple logistic regression (first table), with status as the outcome variable and gender as the predictor variable (female as baseline), is there a statistically significant difference in mortality between males and females? What is the odds ratio (males: females) for mortality? (b) From the multiple logistic regression with both gender (female as baseline) and agemid as predictors (second table), what is the adjusted odds ratio (males:females) for mortality? Is the difference in mortality between males and females statistically significant adjusted for other variables in the model? How would you explain the change in the coefficient of gender between the two models