# Solution

**Topics:**Regression analysis, Logistic regression, Blood pressure

**Pages:**2 (638 words)

**Published:**May 20, 2015

Coding

0=Death

1=Alive

The two post-operative status of the patients are death and alive coded by 0 and 1 respectively to use in binary logistic regression. Hosmer and Lemshow goodness of fit test sig value=0.896

The analysis is fitted that means the analysis is compatible with the data and the logit model is expected to predict the post-operative status of the patient Block 0

Accuracy =29%

This shows the fluke accuracy about the post-operative status of the patient if none of the indicators are used as predictors. Variables not in equation with sig. values

Pulse Rate0.004

Systolic BP0.000

Sugar Level0.001

HB0.450

The table shows that if Pulse rate, systolic BP and Sugar level are used for prediction it will help to predict the post-operative status of the patient more accurately while HB does not matter Block 1

Omnibus sig0.0000

Neglekark R square0.548Cox & Snell R-square0.458

The omnibus test is showing that the logit model is expected to have enough better accuracy then fluke while Neglekarke R square is showing that about 55% increase in accuracy is expected if we use logit model to predict post-operative status of the patient

Variables in equation with B coefficients, Sig. value and Exp (B) Pulse Rate1.2450.0041.45

Systolic BP4.6580.0001.104

Sugar Level-0.5680.0010.846

HB0.1680.4501.000

Accuracy=78%

Therefor the logit model is

Link function = 1.245 (PR) + 4.658 (SBP) – 0.568 (SL)

Where, Link function = post-operative status of the patient The accuracy of above model is 78%

The Exp (B) shows that :

The chance of life increase by 45% if the Pulse rate of...

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