A Comprehensive Guide to Coding and Programming in Stata PDF Download

Author: Rafael Gafoor
Publisher: CRC Press
ISBN: 104008950X
Category : Mathematics
Languages : en
Pages : 204

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Book Description
This book is an introductory guide to programming and coding in Stata. Commonly encountered code in the field of medical statistics as well as the analyses of observational data are presented. For those who are involved in the analyses of observational studies, the need to sometimes assemble large datasets will necessitate a detailed understanding of loops and macros. This book covers these materials early on and then describes other commonly required coding commands. For those who program in a controlled environment (.e.g. medical statisticians who perform analyses for regulatory bodies), the production of log files, a suggested folder structure and analysis pathway are covered. This book also includes a wide range of tabulation commands and other methods of producing tables of descriptive statistics. The text also then provides a clear explanation of how to perform some inferential analyses (including how to extract and format the coefficients for use in subsequent reports). The focus on coding allows beginners to grasp the basics of coding and programming, as well as allowing established researchers to hone their skills and become more advanced programmers. Key Features: Covers the fundamental of using and understanding Stata. Able to be used by anyone looking to learn the basics of coding. Introduces and explains difficult concepts such as macros from the outset.

Author: Christopher F. Baum
Publisher: Stata Press
ISBN: 9781597181501
Category : Social sciences
Languages : en
Pages : 0

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Book Description
"The second edition of this book contains several new recipes illustrating how do-files, ado-files, and Mata functions can be used to solve programming problems. Several recipes have also been updated to reflect new features in Stata added between versions 10 and 14. The discussion of maximum-likelihood function evaluators has been significantly expanded in this edition. The new topics covered in this edition include factor variables and operatores; use of margins, marginsplot, and suest; Mata-based likelihood function evaluators; and associative arrays."--Preface.

Author: Kristoffer Bjärkefur
Publisher: World Bank Publications
ISBN: 1464816956
Category : Business & Economics
Languages : en
Pages : 388

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Book Description
Development Research in Practice leads the reader through a complete empirical research project, providing links to continuously updated resources on the DIME Wiki as well as illustrative examples from the Demand for Safe Spaces study. The handbook is intended to train users of development data how to handle data effectively, efficiently, and ethically. “In the DIME Analytics Data Handbook, the DIME team has produced an extraordinary public good: a detailed, comprehensive, yet easy-to-read manual for how to manage a data-oriented research project from beginning to end. It offers everything from big-picture guidance on the determinants of high-quality empirical research, to specific practical guidance on how to implement specific workflows—and includes computer code! I think it will prove durably useful to a broad range of researchers in international development and beyond, and I learned new practices that I plan on adopting in my own research group.†? —Marshall Burke, Associate Professor, Department of Earth System Science, and Deputy Director, Center on Food Security and the Environment, Stanford University “Data are the essential ingredient in any research or evaluation project, yet there has been too little attention to standardized practices to ensure high-quality data collection, handling, documentation, and exchange. Development Research in Practice: The DIME Analytics Data Handbook seeks to fill that gap with practical guidance and tools, grounded in ethics and efficiency, for data management at every stage in a research project. This excellent resource sets a new standard for the field and is an essential reference for all empirical researchers.†? —Ruth E. Levine, PhD, CEO, IDinsight “Development Research in Practice: The DIME Analytics Data Handbook is an important resource and a must-read for all development economists, empirical social scientists, and public policy analysts. Based on decades of pioneering work at the World Bank on data collection, measurement, and analysis, the handbook provides valuable tools to allow research teams to more efficiently and transparently manage their work flows—yielding more credible analytical conclusions as a result.†? —Edward Miguel, Oxfam Professor in Environmental and Resource Economics and Faculty Director of the Center for Effective Global Action, University of California, Berkeley “The DIME Analytics Data Handbook is a must-read for any data-driven researcher looking to create credible research outcomes and policy advice. By meticulously describing detailed steps, from project planning via ethical and responsible code and data practices to the publication of research papers and associated replication packages, the DIME handbook makes the complexities of transparent and credible research easier.†? —Lars Vilhuber, Data Editor, American Economic Association, and Executive Director, Labor Dynamics Institute, Cornell University

Author: Rafael Gafoor
Publisher:
ISBN: 9781003483779
Category : Medical
Languages : en
Pages : 0

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Book Description
"This book is an introductory guide to programming and coding in Stata. Commonly encountered code in the field of medical statistics as well as the analyses of observational data are presented. For those who are involved in the analyses of observational studies, the need to sometimes assemble large datasets will necessitate a detailed understanding of loops and macros. This book covers these materials early on and then describes other commonly required coding commands. For those who program in a controlled environment (e.g. medical statisticians who perform analyses for regulatory bodies), the production of log files, a suggested folder structure and analysis pathway are covered. This book also includes a wide range of tabulation commands and other methods of producing tables of descriptive statistics. The text also then provides a clear explanation of how to perform some inferential analyses (including how to extract and format the coefficients for use in subsequent reports). The focus on coding allows beginners to grasp the basics of coding and programming, as well as allowing established researchers to hone their skills and become more advanced programmers"--

Author: Robert A. Muenchen
Publisher: Springer Science & Business Media
ISBN: 1441913181
Category : Computers
Languages : en
Pages : 549

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Book Description
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.

Author: Michael N Mitchell
Publisher: Stata Press
ISBN: 9781597183185
Category :
Languages : en
Pages : 512

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Book Description
This second edition of Data Management Using Stata focuses on tasks that bridge the gap between raw data and statistical analysis. It has been updated throughout to reflect new data management features that have been added over the last 10 years. Such features include the ability to read and write a wide variety of file formats, the ability to write highly customized Excel files, the ability to have multiple Stata datasets open at once, and the ability to store and manipulate string variables stored as Unicode. Further, this new edition includes a new chapter illustrating how to write Stata programs for solving data management tasks. As in the original edition, the chapters are organized by data management areas: reading and writing datasets, cleaning data, labeling datasets, creating variables, combining datasets, processing observations across subgroups, changing the shape of datasets, and programming for data management. Within each chapter, each section is a self-contained lesson illustrating a particular data management task (for instance, creating date variables or automating error checking) via examples. This modular design allows you to quickly identify and implement the most common data management tasks without having to read background information first. In addition to the "nuts and bolts" examples, author Michael Mitchell alerts users to common pitfalls (and how to avoid them) and provides strategic data management advice. This book can be used as a quick reference for solving problems as they arise or can be read as a means for learning comprehensive data management skills. New users will appreciate this book as a valuable way to learn data management, while experienced users will find this information to be handy and time saving--there is a good chance that even the experienced user will learn some new tricks.

Author: Tilman M. Davies
Publisher: No Starch Press
ISBN: 1593276516
Category : Computers
Languages : en
Pages : 833

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Book Description
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.

Author: Gábor Békés
Publisher: Cambridge University Press
ISBN: 1108483011
Category : Business & Economics
Languages : en
Pages : 741

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Book Description
A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

Author: Nikhil Abraham
Publisher: John Wiley & Sons
ISBN: 1119050944
Category : Computers
Languages : en
Pages : 288

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Book Description
Your friendly guide to getting a job in coding Getting a Coding Job For Dummies explains how a coder works in (or out of) an organization, the key skills any job requires, the basics of the technologies a coding pro will encounter, and how to find formal or informal ways to build your skills. Plus, it paints a picture of the world a coder lives in, outlines how to build a resume to land a coding job, and so much more. Coding is one of the most in-demand skills in today's job market, yet there seems to be an ongoing deficit of candidates qualified to take these jobs. Getting a Coding Job For Dummies provides a road map for students, post-grads, career switchers, and anyone else interested in starting a career in coding. Inside this friendly guide, you'll find the steps needed to learn the hard and soft skills of coding—and the world of programming at large. Along the way, you'll set a clear career path based on your goals and discover the resources that can best help you build your coding skills to make you a suitable job candidate. Covers the breadth of job opportunities as a coder Includes tips on educational resources for coders and ways to build a positive reputation Shows you how to research potential employers and impress interviewers Offers access to online video, articles, and sample resume templates If you're interested in pursuing a job in coding, but don't know the best way to get there, Getting a Coding Job For Dummies is your compass!

Author: Andrie de Vries
Publisher: John Wiley & Sons
ISBN: 1119963133
Category : Computers
Languages : en
Pages : 470

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Book Description
Master the programming language of choice among statisticians and data analysts worldwide Coming to grips with R can be tough, even for seasoned statisticians and data analysts. Enter R For Dummies, the quick, easy way to master all the R you'll ever need. Requiring no prior programming experience and packed with practical examples, easy, step-by-step exercises, and sample code, this extremely accessible guide is the ideal introduction to R for complete beginners. It also covers many concepts that intermediate-level programmers will find extremely useful. Master your R ABCs ? get up to speed in no time with the basics, from installing and configuring R to writing simple scripts and performing simultaneous calculations on many variables Put data in its place ? get to know your way around lists, data frames, and other R data structures while learning to interact with other programs, such as Microsoft Excel Make data dance to your tune ? learn how to reshape and manipulate data, merge data sets, split and combine data, perform calculations on vectors and arrays, and much more Visualize it ? learn to use R's powerful data visualization features to create beautiful and informative graphical presentations of your data Get statistical ? find out how to do simple statistical analysis, summarize your variables, and conduct classic statistical tests, such as t-tests Expand and customize R ? get the lowdown on how to find, install, and make the most of add-on packages created by the global R community for a wide variety of purposes Open the book and find: Help downloading, installing, and configuring R Tips for getting data in and out of R Ways to use data frames and lists to organize data How to manipulate and process data Advice on fitting regression models and ANOVA Helpful hints for working with graphics How to code in R What R mailing lists and forums can do for you