William Gould, Jeffrey Pitblado, and Brian Poi
Maximum Likelihood Estimation with Stata, Fourth Edition, is the essential reference and guide for researchers in all disciplines who wish to write maximum likelihood (ML) estimators in Stata. Beyond providing comprehensive coverage of Stata’s ml command for writing ML estimators, the book presents an overview of the underpinnings of maximum likelihood and how to think about ML estimation.
Whether you want to fit a special ML estimator for your own research or wish to write a general-purpose ML estimator for others to use, you need this book.
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Tom M. Palmer and Jonathan A. C. Sterne (editors)
Meta-analysis allows researchers to combine results of several studies into a unified analysis that provides an overall estimate of the effect of interest and to quantify the uncertainty of that estimate. Stata has some of the best statistical tools available for doing meta-analysis. The unusual thing about these tools is that none of them are part of official Stata. They are all created by and documented by experts in the broader research community who also happen to be proficient Stata developers. The new edition adds 11 articles to the original collection of 16 articles. The articles cover topics ranging from standard and cumulative meta-analysis and forest plots to contour-enhanced funnel plots and nonparametric analysis of publication bias. In their articles, the authors present conceptual overviews of the techniques, thorough explanations, and detailed descriptions and syntax of new commands. They also provide examples using real- world data. In short, this collection is a complete introduction and reference for performing meta-analyses in Stata.
A. Colin Cameron and Pravin K.Trivedi
Microeconometrics Using Stata, Revised Edition, by A. Colin Cameron and Pravin K.Trivedi, is an outstanding introduction to microeconometrics and how to do microeconometric research using Stata. Aimed at students and researchers, this book covers topics left out of microeconometrics textbooks and omitted from basic introductions to Stata. Cameron and Trivedi provide the most complete and up-to-date survey of microeconometric methods available in Stata.
The unique combination of topics, intuitive introductions to methods, and detailed illustrations of Stata examples make Microeconometrics Using Stata an invaluable, hands-on addition to the library of anyone who uses microeconometric methods.
Sophia Rabe-Hesketh and Anders Skrondal
Multilevel and Longitudinal Modeling Using Stata, Third Edition, by Sophia Rabe-Hesketh and Anders Skrondal, looks specifically at Stata’s treatment of generalized linear mixed models, also known as multilevel or hierarchical models. These models are “mixed” because they allow fixed and random effects, and they are “generalized” because they are appropriate for continuous Gaussian responses as well as binary, count, and other types of limited dependent variables.
The material in the third edition consists of two volumes, a result of the substantial expansion of material from the second edition, and has much to offer readers of the earlier editions. The text has almost doubled in length from the second edition and almost quadrupled in length from the original version, to almost 1,000 pages across the two volumes. Fully updated for Stata 12, the book has 5 new chapters, and many new exercises and datasets.
Stata Press now offers electronic edition of this title.
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Nicholas J. Cox and H. Joseph Newton (editors)
One Hundred Nineteen Stata Tips provides concise and insightful notes about commands, features, and tricks that will help you obtain a deeper understanding of Stata. The book comprises the contributions of the Stata community that have appeared in theStata Journal since 2003.
J. Scott Long and Jeremy Freese
Regression Models for Categorical Dependent Variables Using Stata, Third Edition, by J. Scott Long and Jeremy Freese, shows how to use Stata to fit and interpret regression models for categorical data. The third edition is a complete rewrite of the book. Factor variables and the margins command changed how the effects of variables can be estimated and interpreted. In addition, the authors' views on interpretation have evolved. The changes to Stata and to the authors' views inspired the authors to completely rewrite their popular SPost commands to take advantage of the power of the margins command and the flexibility of factor-variable notation. The new edition will interest readers of a previous edition as well as new readers.
Nicholas J. Cox
Speaking StataGraphics 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.
Michael N. Mitchell
Stata for the Behavioral Sciences, by Michael Mitchell, is the ideal reference for researchers using Stata to fit ANOVA models and other models commonly applied to behavioral science data. Drawing on his education in psychology and his experience in consulting, Mitchell uses terminology and examples familiar to the reader as he demonstrates how to fit a variety of models, how to interpret results, how to understand simple and interaction effects, and how to explore results graphically.
Although this book is not designed as an introduction to Stata, it is appealing even to Stata novices. Throughout the text, Mitchell thoughtfully addresses any features of Stata that are important to understand for the analysis at hand. He also is careful to point out additional resources such as related videos from Stata's YouTube channel.
Survey Weights: A Step-by-Step Guide
to Calculation, by Richard Valliant and Jill Dever, is an excellent reference for
survey data analysts and researchers. This book details the reasons for
weighting and shows how to perform different weight-adjustment methods in
Topics covered include nonresponse, weight
adjustment and calibration, linearized and replication-based variance
estimation, multiple weights, two-phase sampling, composite estimation, and
quality control when computing your own survey weights.
The authors assume familiarity with Stata and some
applied sampling experience and knowledge of "lite" theory, such as
the concepts of with-replacement versus without-replacement sampling and
single- versus multistage designs.
* Briefly introduces survey data analysis using Stata
* Details methods for weight adjustment newly added in Stata 15
* Provides examples that give analysts tools for computing weights in
* Those wanting to learn how survey weights are calculated
* Those wanting to learn how survey weights are adjusted to account for
sampling bias due to the sampling design or non-response
* Those wanting to learn about the standard variance estimation methods
employed when working with survey data
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J. Scott Long
The Workflow of Data Analysis Using Stata, by J. Scott Long, is an essential productivity tool for data analysts. Aimed at anyone who analyzes data, this book presents an effective strategy for designing and doing data-analytic projects.
In this book, Long presents lessons gained from his experience with numerous academic publications, as a coauthorof the immensely popular Regression Models for Categorical Dependent Variables Using Stata, and as a coauthor of the SPOST routines, which are downloaded over 20,000 times a year.
This volume is a sometimes serious and sometimes whimsical retrospective of Stata, its development, and its use over the last 30 years. The view from the inside opens with an essay by Bill Gould,Stata's president and cofounder, that discusses the challenges and concepts that guided the design and implementation of Stata. This is followed by an interview of Bill by Joe Newton that discusses Bill's early interest in computing, his early work on a program for matching prom dates in the days when you had to purchase time on computers, and further exploration of the guiding principles behind Stata. Finally, Sean Becketti, Stata's first employee, delves into the not-to-be-missed culture of Stata in its infancy.
The view from the outside comprises 14 essays by prominent researchers and members of the Stata community. Most discuss Stata's use and evolution in disciplines such as behavioral sciences, business, economics, epidemiology, time series, political science, public health, public policy, veterinary epidemiology, and statistics. Some take a sweeping overview. Others are more intimate personal recollections. Mostly, we simply wanted to celebrate the relationship between Stata users and Stata software. We hope that this volume holds something interesting for everyone.