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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 FREE CHAPTER 2. Stata Programming and Data Management 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

Proportionality assumption


The Cox Hazard proportionality model has a very significant feature called proportionality assumption. There are numerous ways through which we can verify that a particular model fulfills the proportionality model. However, in this case, we will examine proportionality by incorporating time-dependent covariates, such as vcr and temp in the stocx command. Here, predictors as well as time are the interactions of time-dependent covariates. In the present case, interaction is used along with log because generally, this function is used more frequently, yet apart from this, one can use any other function. Note that if a time-dependent covariate is important, then it disobeys the proportionality assumption of that predictor. To summarize, we can say that all time-dependent variables support the proportionality assumption hazard:

Stcox age metfordrug j.med j.sests ccs.age j.sests nmohrr vmcr

(age metfordrug medicinet ssets) temp(lmlnn(_tnt))

failure _d:  censor
analysis...
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