Background for Survival Analysis The UIS data Exploring the data: Univariate Analyses Model Building Interactions Proportionality Assumption Graphing Survival Functions from stcox command Goodness of Fit of the Final Model The Stata program on which the seminar is based. The UIS_small data file for the seminar. Background for Survival Analysis The goal of this seminar…
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Survey Data Analysis in Stata The purpose of this seminar is to explore how to analyze survey data collected under different sampling plans using Stata.  Other examples, including those using other survey data analysis packages, can be found at Choosing the Correct Analysis for Various Survey Designs.  Before we begin looking at examples in Stata,…
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Simple random sample in Stata In this example, we are taking a simple random sampling of schools. After loading the data set into Stata, we will use the count command to see how many cases we have in the data file.  Next, we will set the seed so that the results are replicable. If you…
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by Xiao Chen, Phil Ender, Michael Mitchell & Christine Wells (in alphabetical order) The aim of these materials is to help you increase your skills in using logistic regression analysis with Stata.  This web book does not teach logistic regression, per se, but focuses on how to perform logistic regression using Stata.  It is assumed…
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We will begin our discussion of binomial logistic regression by comparing it to regular ordinary least squares (OLS) regression. Perhaps the most obvious difference between the two is that in OLS regression the dependent variable is continuous and in binomial logistic regression, it is binary and coded as 0 and 1. Because the dependent variable…
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2.0 Introduction 2.1 One Categorical predictor 2.2 Two Categorical predictors       2.2.1 A 2 by 2 Layout with Only Main Effects       2.2.2 A 2 by 2 Layout with Main Effects and Interaction       2.2.3 A 2 by 3 Layout with Only Main Effects       2.2.4 A 2 by 3 Layout with Main Effects and…
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NOTE:  This page is under construction!! So far in this course we have analyzed data in which the response variable has had exactly two levels, but what about the situation in which there are more than two levels? In this chapter of the Logistic Regression with Stata, we cover the various commands used for multinomial…
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NOTE:  This page is under construction!! Intro paragraph needed!!!!! 5.1 Conditional Logistic Regression There are two alternative approaches to maximum likelihood estimation in logistic regression, the unconditional estimation approach and the conditional estimation approach. In the previous chapters we have made use of the unconditional estimation approach. Unconditional estimation works best when the number of…
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by Xiao Chen, Philip B. Ender, Michael Mitchell and Christine Wells (in alphabetical order)   The aim of these materials is to help you increase your skills in using regression analysis with Stata.  This web book does not teach regression, per se, but focuses on how to perform regression analyses using Stata.  It is assumed…
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Chapter Outline  1.0 Introduction 1.1 A First Regression Analysis 1.2 Examining Data 1.3 Simple linear regression 1.4 Multiple regression 1.5 Transforming variables 1.6 Summary 1.7 Self assessment 1.8 For more information 1.0 Introduction This book is composed of four chapters covering a variety of topics about using Stata for regression. We should emphasize that this…
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