A study (data from Efron B, et al 2004) was conducted to determine the predictors of whether participants had a low or high risk of diabetes (we'll call this variable "Y"), Data was collected on 442 diabetes patients. A multivariable logistic regression model was constructed for the outcome Y that included the predictor variables age, gender, BMI, blood pressure, total cholesterol, LDL cholesterol, triglycerides and glucose level. The odds ratios omputed from the model parameter estimates can be seen here:
A study (data from Efron B, et al 2004) was conducted to determine the predictors of whether participants had a low or high risk of diabetes (we'll call this variable "Y"), Data was collected on 442 diabetes patients. A multivariable logistic regression model was constructed for the outcome Y that included the predictor variables age, gender, BMI, blood pressure, total cholesterol, LDL cholesterol, triglycerides and glucose level. The odds ratios omputed from the model parameter estimates can be seen here:
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question
4
Transcribed Image Text:4 Odds Ratios for Gender
Level1 /Level2 Odds Ratio Prob> Chisq Lower 95% Upper 95%
2.
1.8525808
0.0569
0.9821721
3.4943523
1
0.5397875
0.0569
0.2861761
1.0181515
Note gender is coded as Gender=2 for female and Gender=1 for male and low risk of diabetes is
coded as 0, high risk of diabetes is coded as 1 and the model seeks to predict the high risk of
diabetes.
Do males or females have greater odds of a high risk of diabetes? Cite evidence to support your
answer and interpret the relevant results in terms of the problem at hand.
Transcribed Image Text:A study (data from Efron B, et al 2004) was conducted to detemine the predictors of whether
participants had a low or high risk of diabetes (we'll call this variable "Y"). Data was collected on
442 diabetes patients.
A multivariable logistic regression model was constructed for the outcome Y that included the
predictor variables age, gender, BMI, blood pressure, total cholesterol, LDL cholesterol,
triglycerides and glucose level. The odds ratios gomputed from the model parameter estimates can
be seen here:
4 Unit Odds Ratios
Per unit change in regressor
Term
Odds Ratio Lower 95% Upper 95%
Age
0.996106
0.972001
1.135468
1.028259
1.020597
BMI
1.225728
1.052517
1.330495
Blood Pressure
1.078545
Total Cholesterol
0.959058
0.931957
0.985535
1.069977
67.57455
LDL
Triglycerides
Glucose
1.039002
22.84237
1.000038
1.010135
8.430059
0.971109
1.029997
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