A Gentle Introduction to Stata, Fifth Edition

The Labour Ward Handbook, second edition, is a succinct manual that provides detailed clinical practice guidelines for the care of women in labour. Dealing more with the practice than the theory of labour ward management, this book is designed to be a ready guide for use in the delivery suite by the busy clinician.The format has been specifically designed to make retrieval of information quick and simple. Relevant pages can be reproduced and filed in the patient's case-notes thus serving not only as an aide memoire and checklist, but also as a supplementary record of the care provided.The Labour Ward Handbook is essential reading for practising obstetricians of all grades, midwives, labour ward managers, and all other medical professionals who are interested in the conduct of labour and risk management in the delivery suite.Key FeaturesChecklists and bullet points for quick and straightforward guidence'Further reading' at the end of each sectionCompliant with RCOG and NICE guidelinesBuilds on a very popular first editionIf you work on the labour ward, this is the book to have with you at all times.Alan C. Acock's A Gentle Introduction to Stata, Fifth Edition,is aimed at new Stata users who want to become proficient in Stata.After reading this introductory text, new users will be able not onlyto use Stata well but also to learn new aspects of Stata.Acock assumes that the user is not familiar with any statisticalsoftware. This assumption of a blank slate is central to the structureand contents of the book. Acock starts with the basics; for example,the portion of the book that deals with data management begins with acareful and detailed example of turning survey data on paper into aStata-ready dataset on the computer. When explaining how to go aboutbasic exploratory statistical procedures, Acock includes notes thatwill help the reader develop good work habits. This mixture ofexplaining good Stata habits and good statistical habits continuesthroughout the book.Acock is quite careful to teach the reader all aspects of using Stata.He covers data management, good work habits (including the use ofbasic do-files), basic exploratory statistics (including graphicaldisplays), and analyses using the standard array of basic statisticaltools (correlation, linear and logistic regression, and parametric andnonparametric tests of location and dispersion). He also successfullyintroduces some more advanced topics such as multiple imputation andstructural equation modeling in a very approachable manner. Acockteaches Stata commands by using the menus and dialog boxes while stillstressing the value of do-files. In this way, he ensures that alltypes of users can build good work habits. Each chapter has exercisesthat the motivated reader can use to reinforce the material.The tone of the book is friendly and conversational without ever beingglib or condescending. Important asides and notes about terminologyare set off in boxes, which makes the text easy to read without anyconvoluted twists or forward-referencing. Rather than splitting topicsby their Stata implementation, Acock arranges the topics as they wouldappear in a basic statistics textbook; graphics and postestimation arewoven into the material in a natural fashion. Real datasets, such asthe General Social Surveys from 2002 and 2006, are usedthroughout the book.The focus of the book is especially helpful for those in thebehavioral and social sciences because the presentation of basicstatistical modeling is supplemented with discussions of effect sizesand standardized coefficients. Various selection criteria, such assemipartial correlations, are discussed for model selection. Acockalso covers a variety of commands available for evaluating reliabilityand validity of measurements.The fifth edition of the book includes two new chapters that covermultilevel modeling and item response theory (IRT) models. Themultilevel modeling chapter demonstrates how to fit linear multilevelmodels using the mixed command. Acock discusses models withboth random intercepts and random coefficients, and he provides avariety of examples that apply these models to longitudinal data. TheIRT chapter introduces the use of IRT models for evaluating a set ofitems designed to measure a specific trait such as an attitude, value,or a belief. Acock shows how to use the irt suite of commands,which are new in Stata 14, to fit IRT models and to graph the results.In addition, he presents a measure of reliability that can be computedwhen using IRT.