Stata Technical Bulletin Reprints
Author | : StataCorp LP |
Publisher | : Stata Press |
Total Pages | : 254 |
Release | : 1994-05 |
Genre | : Mathematics |
ISBN | : 9781881228127 |
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Author | : StataCorp LP |
Publisher | : Stata Press |
Total Pages | : 254 |
Release | : 1994-05 |
Genre | : Mathematics |
ISBN | : 9781881228127 |
Author | : Jonathan Sterne |
Publisher | : Stata Press |
Total Pages | : 0 |
Release | : 2009-03-18 |
Genre | : Mathematics |
ISBN | : 9781597180498 |
This collection provides detailed descriptions of both standard and advanced meta-analytic methods and their implementation in Stata. Readers will gain access to the statistical methods behind the rapid increase in the number of meta-analyses reported in the social science and medical literature. The book shows how to conduct and interpret meta-analyses as well as produce highly flexible graphical displays. Using meta-regression, it examines reasons for between-study variability in effect estimates. The book also employs advanced methods for the meta-analysis of diagnostic test accuracy studies, dose-response meta-analysis, meta-analysis with missing data, and multivariate meta-analysis.
Author | : William Gould |
Publisher | : Stata Press |
Total Pages | : 352 |
Release | : 2010-10-27 |
Genre | : Mathematics |
ISBN | : 9781597180788 |
Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.
Author | : Nicholas J. Cox |
Publisher | : Stata Press |
Total Pages | : 0 |
Release | : 2014-04-28 |
Genre | : Mathematics |
ISBN | : 9781597181440 |
Speaking Stata Graphics is ideal for researchers who want to produce effective, publication-quality graphs. A compilation of articles from the popular Speaking Stata column by Nicholas J. Cox, this book provides valuable insights about Stata's built-in and user-written statistical-graphics commands.
Author | : Christopher F. Baum |
Publisher | : Stata Press |
Total Pages | : 362 |
Release | : 2006-08-17 |
Genre | : Business & Economics |
ISBN | : 1597180130 |
Integrating a contemporary approach to econometrics with the powerful computational tools offered by Stata, this introduction illustrates how to apply econometric theories used in modern empirical research using Stata. The author emphasizes the role of method-of-moments estimators, hypothesis testing, and specification analysis and provides practical examples that show how to apply the theories to real data sets. The book first builds familiarity with the basic skills needed to work with econometric data in Stata before delving into the core topics, which range from the multiple linear regression model to instrumental-variables estimation.
Author | : MICHAEL N. MITCHELL |
Publisher | : Stata Press |
Total Pages | : 610 |
Release | : 2020-12-18 |
Genre | : |
ISBN | : 9781597183215 |
Interpreting and Visualizing Regression Models Using Stata, Second Edition provides clear and simple examples illustrating how to interpret and visualize a wide variety of regression models. Including over 200 figures, the book illustrates linear models with continuous predictors (modeled linearly, using polynomials, and piecewise), interactions of continuous predictors, categorical predictors, interactions of categorical predictors, and interactions of continuous and categorical predictors. The book also illustrates how to interpret and visualize results from multilevel models, models where time is a continuous predictor, models with time as a categorical predictor, nonlinear models (such as logistic or ordinal logistic regression), and models involving complex survey data. The examples illustrate the use of the margins, marginsplot, contrast, and pwcompare commands. This new edition reflects new and enhanced features added to Stata, most importantly the ability to label statistical output using value labels associated with factor variables. As a result, output regarding marital status is labeled using intuitive labels like Married and Unmarried instead of using numeric values such as 1 and 2. All the statistical output in this new edition capitalizes on this new feature, emphasizing the interpretation of results based on variables labeled using intuitive value labels. Additionally, this second edition illustrates other new features, such as using transparency in graphics to more clearly visualize overlapping confidence intervals and using small sample-size estimation with mixed models. If you ever find yourself wishing for simple and straightforward advice about how to interpret and visualize regression models using Stata, this book is for you.
Author | : Stata Corporation |
Publisher | : |
Total Pages | : 498 |
Release | : 2003 |
Genre | : Analysis of variance |
ISBN | : |
Author | : Robert A. Muenchen |
Publisher | : Springer Science & Business Media |
Total Pages | : 549 |
Release | : 2010-04-26 |
Genre | : Computers |
ISBN | : 1441913181 |
Stata is the most flexible and extensible data analysis package available from a commercial vendor. R is a similarly flexible free and open source package for data analysis, with over 3,000 add-on packages available. This book shows you how to extend the power of Stata through the use of R. It introduces R using Stata terminology with which you are already familiar. It steps through more than 30 programs written in both languages, comparing and contrasting the two packages' different approaches. When finished, you will be able to use R in conjunction with Stata, or separately, to import data, manage and transform it, create publication quality graphics, and perform basic statistical analyses. A glossary defines over 50 R terms using Stata jargon and again using more formal R terminology. The table of contents and index allow you to find equivalent R functions by looking up Stata commands and vice versa. The example programs and practice datasets for both R and Stata are available for download.