A Gentle Introduction to Stata, Fifth Edition

A Gentle Introduction to Stata, Fifth Edition

<P>Alan C. Acock's <STRONG>A Gentle Introduction to Stata, Fifth Edition</STRONG>,<BR>is aimed at new Stata users who want to become proficient in Stata.<BR>After reading this introductory text, new users will be able not only<BR>to use Stata well but also to learn new aspects of Stata.<BR><BR>Acock assumes that the user is not familiar with any statistical<BR>software. This assumption of a blank slate is central to the structure<BR>and contents of the book. Acock starts with the basics; for example,<BR>the portion of the book that deals with data management begins with a<BR>careful and detailed example of turning survey data on paper into a<BR>Stata-ready dataset on the computer. When explaining how to go about<BR>basic exploratory statistical procedures, Acock includes notes that<BR>will help the reader develop good work habits. This mixture of<BR>explaining good Stata habits and good statistical habits continues<BR>throughout the book.<BR><BR>Acock is quite careful to teach the reader all aspects of using Stata.<BR>He covers data management, good work habits (including the use of<BR>basic do-files), basic exploratory statistics (including graphical<BR>displays), and analyses using the standard array of basic statistical<BR>tools (correlation, linear and logistic regression, and parametric and<BR>nonparametric tests of location and dispersion). He also successfully<BR>introduces some more advanced topics such as multiple imputation and<BR>structural equation modeling in a very approachable manner. Acock<BR>teaches Stata commands by using the menus and dialog boxes while still<BR>stressing the value of do-files. In this way, he ensures that all<BR>types of users can build good work habits. Each chapter has exercises<BR>that the motivated reader can use to reinforce the material.<BR><BR>The tone of the book is friendly and conversational without ever being<BR>glib or condescending. Important asides and notes about terminology<BR>are set off in boxes, which makes the text easy to read without any<BR>convoluted twists or forward-referencing. Rather than splitting topics<BR>by their Stata implementation, Acock arranges the topics as they would<BR>appear in a basic statistics textbook; graphics and postestimation are<BR>woven into the material in a natural fashion. Real datasets, such as<BR>the <EM>General Social Surveys</EM> from 2002 and 2006, are used<BR>throughout the book.<BR><BR>The focus of the book is especially helpful for those in the<BR>behavioral and social sciences because the presentation of basic<BR>statistical modeling is supplemented with discussions of effect sizes<BR>and standardized coefficients. Various selection criteria, such as<BR>semipartial correlations, are discussed for model selection. Acock<BR>also covers a variety of commands available for evaluating reliability<BR>and validity of measurements.<BR><BR>The fifth edition of the book includes two new chapters that cover<BR>multilevel modeling and item response theory (IRT) models. The<BR>multilevel modeling chapter demonstrates how to fit linear multilevel<BR>models using the <STRONG>mixed</STRONG> command. Acock discusses models with<BR>both random intercepts and random coefficients, and he provides a<BR>variety of examples that apply these models to longitudinal data. The<BR>IRT chapter introduces the use of IRT models for evaluating a set of<BR>items designed to measure a specific trait such as an attitude, value,<BR>or a belief. Acock shows how to use the <b>irt</b> suite of commands,<BR>which are new in Stata 14, to fit IRT models and to graph the results.<BR>In addition, he presents a measure of reliability that can be computed<BR>when using IRT.<BR></P>