Ebook The Workflow of Data Analysis Using Stata, by J. Scott Long
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The Workflow of Data Analysis Using Stata, by J. Scott Long
Ebook The Workflow of Data Analysis Using Stata, by J. Scott Long
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Product details
Paperback: 379 pages
Publisher: Stata Press; 1 edition (December 10, 2008)
Language: English
ISBN-10: 1597180475
ISBN-13: 978-1597180474
Product Dimensions:
7.2 x 1 x 9 inches
Shipping Weight: 1.8 pounds (View shipping rates and policies)
Average Customer Review:
4.2 out of 5 stars
22 customer reviews
Amazon Best Sellers Rank:
#422,026 in Books (See Top 100 in Books)
This book is great. I highly recommend it for anyone dealing with large-scale collaborative data projects.The author covers everything from saving and filing your data (good life skills even for those who don't use STATA) to documenting and cleaning datasets.The book reads fast and is interesting enough. Lots of general advice and then a few specific, detailed examples with full-fledged code that are easy to skip if they are not relevant (mercifully, he does not force you through the examples like some books do - they are fairly self-contained modules within the chapters). For each task, he tends to talk about the commands used (with relevant/most-helpful options), but then also about general rules for how to approach the task.The author's personal narrative dominates the book, but it is clear that he has a lot of experience and for the most part, it is helpful that the book is written that way. Some of the advice is shocking in its simplicity but its usefulness (i.e. "Never name a file 'Final'" lest you wind up with "Final - v1" "Final - v2" and "Final - really really final") - these are problems that are applicable to everyone. As such, although I have a reasonable amount of experience with STATA I felt that this book covered really useful basics in a way that was helpful but not tedious.Unsurprisingly for someone who writes about organization and workflow management, the book is also well-organized, and designed in such a way that you can read as you go, covering relevant chapters as you face the tasks within. I've been moving along at the pace of my project, highlighting commands as I read so that I can use it as a reference manual once I finish going through the first time. So far, the book has more than paid for itself in time and frustration saved.
I had heard about (and then attended) Scott Long's ICPSR workflow lecture before reading the book, but carefully reading through and thinking about Long's recommendations would be worthwhile even if Long extended his lecture to a semester-long course. His careful analysis, unforgiving standards, and clear writing all reinforce the central message of professional data analysis: replicability is everything. Replicability is as difficult to achieve in practice as it is to imagine in theory, but Long's tools will help anyone, from a beginning graduate student to a tenured faculty member, come much closer to that goal at far less cost than they might have imagined.
Whether you use Stata or not, if you work with data and do research in the area of empirical social science (Economics, Political Science, Policy Studies) then this book is a must for you. And on top of that if you use Stata for your research, then the question is why you do not have this book yet in your library?This is probably one of of the few books that I ever bought which taught me something new in each page. It has definitely helped me to learn how to organize my work effectively and efficiently. It has also taught me a lot of Stata programming skills.
Short on statistics, and long on practical techniques, this thoughtful, incredibly well-organized guide should be required reading for anybody using STATA to complete a large project. My best guess is that for every hour you spend reading this book you will save 10 hours in your first analysis. Excellent on-line resources as well. Thank you Dr. Long!
I think it's very useful book for researchers. First of all, the author gives helpful advice concerning the whole workflow of data analysis. Secondly, the author explains why you should or should do something based on his and his colleagues' experience.However, it would be very nice if the book had exercises after each chapter.
This is a great book for anyone working with analyzing large data sets in Stata. We all have a workflow when doing this, this book wil make you aware of this, and will help you to make your workflow better at documenting and planning your projects. It also has some really nice tricks to automating things in Stata making your workflow more effective.It suits most researchers, from PhD students just starting up their career to more experienced researchers. It also fits almost all levels of Stata proficiency. You need a bare minimum of knowledge, but then it will suit everyone up until almost expert level. There are something for everyone!Personally my documenting skills have improved and I now realize just how much I can do with Stata when using Macros, Loops and Matrices to a wide variety of tasks. The book does not teach you statistics or how to do specific analysis, but rather how to do generic tasks in cleaning and managing your data, as well as presenting data.
Simply put, this book will drastically reduce the amount of time it will take you to write a do file. In fact, based on the suggestions that long has in this book I was able to write a do file that will run OLS and all the typical diagnostics automatically. All I have to do is assign the variable macros at the beginning of the do file. My summer project is to do the same thing for my other basic statistical models.The workflow of data analysis using Stata should be required for any course on regression or applied statistics that uses Stata. Any applied researcher using this program needs to buy this book.
This book provide generalizable concept of good practice in data management. My project is a clinical research collecting data in Access and analyzing with STATA.I found in process of cleaning data- many files been created and became messy. The "Posting file" and "dual workflow (separate data management and statistical analysis" are really help me organize this project.
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