A health researcher wants to be able to predict whether the "incidence of heart disease" can be

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A health researcher wants to be able to predict whether the "incidence of heart disease" can be predicted based on "age", "weight", "gender" and "VO2max" (i.e., where VO2max refers to maximal aerobic capacity, an indicator of fitness and health). To this end, the researcher recruited 100 participants to perform a maximum VO2max test as well as recording their age, weight and gender. The participants were also evaluated for the presence of heart disease. A binomial logistic regression was then run to determine whether the presence of heart disease could be predicted from their VO2max, age, weight and gender. A logistic regression is performed and the SPSS output are given below: Model Summary Step | -2 Log likelihood | Cox & Snell R Square | Nagelkerke R Square 1 | 102.088a | .240 | .330 a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001. Classification Tablea Observed | Predicted heart_disease | Percentage Correct No | Yes Step 1 heart_disease No | 55 | 10 | 84.6 Yes | 19 | 16 | 45.7 Overall Percentage | | | 71.0 a. The cut value is .500 Variables in the Equation B | S.E. | Wald | df | Sig. | Exp(B) | 95% C.I. for EXP(B) Lower | Upper Step 1a age | .085 | .028 | 9.132 | 1 | .003 | 1.089 | 1.030 | 1.151 weight | .006 | .022 | .065 | 1 | .799 | 1.006 | .962 | 1.051 gender(1) | 1.950 | .842 | 5.356 | 1 | .021 | 7.026 | 1.348 | 36.625 VO2max | -.099 | .048 | 4.266 | 1 | .039 | .906 | .824 | .995 Constant | -1.676 | 3.336 | .253 | 1 | .615 | .187 a. Variable(s) entered on step 1: age, weight, gender, VO2max. Interpret and analyse the output and present the apt model to predict the heart disease in terms of age, weight, gender and VO2max. Write a brief report on the analysis. Calculate the necessary probabilities.

          A health researcher wants to be able to predict whether the "incidence of heart disease" can be predicted based on "age", "weight", "gender" and "VO2max" (i.e., where VO2max refers to maximal aerobic capacity, an indicator of fitness and health). To this end, the researcher recruited 100 participants to perform a maximum VO2max test as well as recording their age, weight and gender. The participants were also evaluated for the presence of heart disease. A binomial logistic regression was then run to determine whether the presence of heart disease could be predicted from their VO2max, age, weight and gender. A logistic regression is performed and the SPSS output are given below:

Model Summary
Step | -2 Log likelihood | Cox & Snell R Square | Nagelkerke R Square
1 | 102.088a | .240 | .330
a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.

Classification Tablea
Observed | Predicted heart_disease | Percentage Correct
No | Yes
Step 1 heart_disease No | 55 | 10 | 84.6
Yes | 19 | 16 | 45.7
Overall Percentage | | | 71.0
a. The cut value is .500

Variables in the Equation
B | S.E. | Wald | df | Sig. | Exp(B) | 95% C.I. for EXP(B) Lower | Upper
Step 1a age | .085 | .028 | 9.132 | 1 | .003 | 1.089 | 1.030 | 1.151
weight | .006 | .022 | .065 | 1 | .799 | 1.006 | .962 | 1.051
gender(1) | 1.950 | .842 | 5.356 | 1 | .021 | 7.026 | 1.348 | 36.625
VO2max | -.099 | .048 | 4.266 | 1 | .039 | .906 | .824 | .995
Constant | -1.676 | 3.336 | .253 | 1 | .615 | .187
a. Variable(s) entered on step 1: age, weight, gender, VO2max.

Interpret and analyse the output and present the apt model to predict the heart disease in terms of age, weight, gender and VO2max. Write a brief report on the analysis. Calculate the necessary probabilities.

A health researcher wants to be able to predict whether the "incidence of heart disease" can be predicted based on "age", "weight", "gender" and "VO2max" (i.e., where VO2max refers to maximal aerobic capacity, an indicator of fitness and health). To this end, the researcher recruited 100 participants to perform a maximum VO2max test as well as recording their age, weight and gender. The participants were also evaluated for the presence of heart disease. A binomial logistic regression was then run to determine whether the presence of heart disease could be predicted from their VO2max, age, weight and gender. A logistic regression is performed and the SPSS output are given below:

Model Summary
Step | -2 Log likelihood | Cox Snell R Square | Nagelkerke R Square
1 | 102.088a | .240 | .330
a. Estimation terminated at iteration number 5 because parameter estimates changed by less than .001.

Classification Tablea
Observed | Predicted heartdisease | Percentage Correct
No | Yes
Step 1 heartdisease No | 55 | 10 | 84.6
Yes | 19 | 16 | 45.7
Overall Percentage | | | 71.0
a. The cut value is .500

Variables in the Equation
B | S.E. | Wald | df | Sig. | Exp(B) | 95% C.I. for EXP(B) Lower | Upper
Step 1a age | .085 | .028 | 9.132 | 1 | .003 | 1.089 | 1.030 | 1.151
weight | .006 | .022 | .065 | 1 | .799 | 1.006 | .962 | 1.051
gender(1) | 1.950 | .842 | 5.356 | 1 | .021 | 7.026 | 1.348 | 36.625
VO2max | -.099 | .048 | 4.266 | 1 | .039 | .906 | .824 | .995
Constant | -1.676 | 3.336 | .253 | 1 | .615 | .187
a. Variable(s) entered on step 1: age, weight, gender, VO2max.

Interpret and analyse the output and present the apt model to predict the heart disease in terms of age, weight, gender and VO2max. Write a brief report on the analysis. Calculate the necessary probabilities.

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