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Data Analysis with STATA

You're reading from   Data Analysis with STATA Explore the big data field and learn how to perform data analytics and predictive modelling in STATA

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Product type Paperback
Published in Oct 2015
Publisher Packt
ISBN-13 9781782173175
Length 176 pages
Edition 1st Edition
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Toc

Table of Contents (11) Chapters Close

Preface 1. Introduction to Stata and Data Analytics 2. Stata Programming and Data Management FREE CHAPTER 3. Data Visualization 4. Important Statistical Tests in Stata 5. Linear Regression in Stata 6. Logistic Regression in Stata 7. Survey Analysis in Stata 8. Time Series Analysis in Stata 9. Survival Analysis in Stata Index

Building a model


In order to build a model, we will incorporate all regular predictors as well as predictors that have a lesser value of p (0.3-0.35). As methodux consists of three steps, the preceding predictor will be incorporated along with a dummy variable as well as methodux1 as a reference. A dummy variable can be formed through the xi command with Toxiq:

Toxiq age metfordrug j.sets 1.metho, Lsssdzc

Fail_c: patient response
Analysis_tm: time

Iteration 0: log Likelihood = - 38645.678, Iteration 1: log Likelihood = -38546.876
Iteration 2: log Likelihood = -38546.956, Iteration 3: log Likelihood = -38546.567

Refined estimate: Iteration 0: Log Likelihood  = -38456,567

Cox regression -- Breslow method
Total subjects- 520
Total observations – 520
Failures – 294
Risk time – 13259
Log likelihood - -38456.567        LRRRchiiirl(3) – 36.90
                                   Prob> chiiiir(3) = 0

t_time

Coefficient

Standard Error

y

P> !y!

[ 93% Conff interval]

age

-0.12456

...
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