A. In the following correlation matrix, if DVAR were regressed on VARA, VARB, and VARC, what is the lowest possible value of R2? VARA 1.00 .62 .77 .54 VARA VARB VARC DVAR VARB VARC DVAR 1.00 .68 .36 1.00 .48 1.00 B. In the following correlation matrix, if DVAR is regressed on VARA, VARB, and VARC simultaneously, is there a problem? What problem? VARA 1.00 .39 .86 .54 VARA VARB VARC DVAR VARB VARC DVAR 1.00 .40 .36 1.00 .48 1.00 C. For these exercises, you will be using the SPSS dataset Polit2SetC to do multiple regression analyses to predict level of depression in the sample of low-income urban women. The DV is cesd (#35 variable). The IVs are age (#2), sf12phys (#44) and sf12ment (#45). Before you perform a multiple regression, first perform bivariate correlation to examine the correlation matrix. Select Analyze Correlate Bivariate, then select the four variables and move them to the variables list. Then ok. a. Summarize your correlation in a matrix similar to TABLE 10.2. CES-D score Age SFphy SFment CES-D score 1.00 0.061 -0.264 -0.651 Age 0.061 1 -0.166 -0.39 SFphy -0.264 -0.166 1 0.168 SFment -0.651 -0.39 0.168 1 b. Which predictor has the highest correlation with cesd? c. Attach your SPSS printout. Correlations Age at first birth Age at first birth Pearson Correlation CES-D Score 1 Sig. (2-tailed) N CES-D Score 929 SF12: Physical SF12: Mental Health Health Component Component Score, Score, standardized standardized .045 -.033 -.020 .182 .339 .558 897 834 834 1 ** -.651** .000 .000 Pearson Correlation .045 -.264 Sig. (2-tailed) .182 N 897 962 884 884 -.033 -.264** 1 .168** SF12: Physical Health Pearson Correlation Component Score, Sig. (2-tailed) .339 .000 standardized N 834 884 893 893 SF12: Mental Health Pearson Correlation -.020 -.651** .168** 1 Component Score, Sig. (2-tailed) .558 .000 .000 standardized N 834 884 893 .000 893 **. Correlation is significant at the 0.01 level (2-tailed). D. E. In this exercise, you will run a simultaneous multiple regression analysis to predict the women's level of depression (scores on the CESD depression scale, cesd) based on age (#2), sf12phys (#44) and sf12ment (#45). Select Analyze Regression Linear. Insert the variable cesd in the box labeled Dependent. Insert the 3 predictor variables into the box for Independent(s). Make sure that Methods is set to \"Enter,\" the command for entering all predictors simultaneously. Then OK to run the analysis. Answer the following questions: a. How large is the sample on which the regression analysis was run? b. What is the value of R2 and what does it mean? c. What is the value of adjusted R2? d. What is the F value and p level? Will you reject the null hypothesis? e. What is the df for regression? f. What predictors are significant and at what p level? g. Write a paragraph summarizing the multiple regression results. h. Attach the SPSS printouts. Chapter 12: Logistic Regression A. What is the logistic regression equation for predicting the probability of having a tubal ligation, based on information shown in Figure 12.6 (page 322)? B. Based on either your clinical knowledge or on a brief literature search, what variable would you recommend adding to improve the prediction of a woman's decision to have a tubal ligation? How would you measure or construct that variable? The following questions are based on table 1. Table 1. Meta-analysis of the Association between diabetes and asthma Cardwell, C.R., Shields, M.D., Carson, D.J., & Patterson, C.C. (2003). A meta-Analysis of the Association Between Childhood Type 1 Diabetes and Atopic Disease. Diabetes Care, 26, 2568-2574. Note: There is a typo in the table for the last article (Rosenbauer); the CI should be 0.59 to 1.96 (not 0.96) which is non-significant. C. From table 1, which articles reported significant results? List the name of the author as appeared in table 1, the OR, 95% CI, and the direction indicating lower risk or higher risk of asthma among patients with diabetes. D. For the study by Douek, how many of the sample had diabetes? How many did not have diabetes (control)? What is the total N? E. For the study by Douek: a. What was the prevalence of asthma among people with diabetes? b. What was the prevalence of asthma among the controls? c. What was the RR? (you need to calculate the RR) d. Interpret the results based on the reported percentages and OR F. Overall, how many subjects with diabetes were included in all of the 23 studies? Among them, how many had asthma? How many subjects without diabetes were included all the studies? Among them, how many had asthma? G. What were the overall OR and 95% CI? Was the result significant