We fit the logistic regression model with the data. Use the R codes below to fit the logistic regression model andanswer the following question.Sex = c(rep ("Female", 2), rep("Male", 2))ECG = c("Low", "High", "Low", "High")Disease = c(4, 8, 9, 21)No.Disease = c(11, 10, 9, 6)data.frame (Sex, ECG, Disease, No.Disease)Report the upper limit of the 90% likelihood ratio confidence interval for the common odds ratio between ECGand disease status controlling for Sex.

We fit the regression model in R using the given R commands.

We fit the logistic regression model with the data. Use the R codes below to fit the logistic regression model and answer the following question. Sex - c(rep ("Female", 2), rep("Male", 2)) ECG = c("Low", "High", "Low", "High") Disease - c(4, 8, 9, 21) No.Disease = e(11, 10, 9, 6) data.frame (Sex, EcG, Disease, No.Disease) Report the upper limit of the 90% likelihood ratio confidence interval for the common odds ratio between ECG and disease status controlling for Sex.

We fit the logistic regression model with the data. Use the R codes below to fit the logistic regression model and answer the following question. Sex - c(rep ("Female", 2), rep("Male", 2)) ECG = c("Low", "High", "Low", "High") Disease - c(4, 8, 9, 21) No.Disease = e(11, 10, 9, 6) data.frame (Sex, EcG, Disease, No.Disease) Report the upper limit of the 90% likelihood ratio confidence interval for the common odds ratio between ECG and disease status controlling for Sex.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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