Customer Reviews

The Workflow of Data Analysis Using Stata

5 star:		(9)
4 star:		(1)
3 star:		(0)
2 star:		(0)
1 star:		(0)

 

 

The book covers basic material in data management and organizing your work in STATA. Most of the material will prove beneficial to the novice STATA user or to someone who is about to start doing serious statistical analysis with STATA and wants to know a bit about organization and documentation of the work ahead. However, the material is also beneficial to the intermediate and advanced STATA user because it serves as a reminder of the right way of doing things when it comes to data and work organization that could potentially save tons of time in the future when looking for errors and trying to explain why things didnt turn out the way they should. On the down side, there is a lot of stuff in the book that can be found in other books and especially in the STATA Documentation series. Long tries hard to clarify each concept with many examples but in some places the examples go on forever. Also in some parts of the book the same material is covered more than once. Now this can be ok for the novice user but not for the expert. some of the material (for example why files get lost) could have stayed out of the book. I think that the same material could have been covered in 200 pages and not 350. Overall though, the book is a great resource for the novice researcher and can offer useful hints and tips about work organization to the more seasoned researchers.

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.

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.

I like this book and will definitely share with my collegues. In my consulting and training, questions relating to research flows (analytical workflows) come out all times, but no books are available. This book may be the first to fully address this issue in details. The principles and guidlines presented in this book are not only useful to Stata users, but also to the users of SPSS and R.

The book focuses more on data preparation than on data analysis (model building) that more books in this area are needed.

[...]

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.

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.

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.

J. Scott Long's "The Workflow of Data Analysis Using Stata" is well-written, logically organized, and a great resource. I'm an experienced Stata user and have encountered the issues he explicitly outlines but, alas, I always dealt with those items with ad hoc and less-than-ideal solutions. I feel like my approach to organization of my analyses, data cleansing, and outputting of results has evolved to a higher level after reading this book. The section on setting up analysis directories was especially educational, as was the template he provided for the setup and organization of a .do file. Almost all Stata users -- even those with considerable expertise -- are likely to find something useful in this book. Highly recommended to statisticians, data analysts, programmers, and researchers!

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.

Time and again I order Stata Press books because they are easy to read, clear, explicit, and written for data users at all levels. This book is no exception. I'm a doctoral student working on my dissertation, and the largest hurdle I've had so far is managing my data since I use very large datasets. I found myself time and again getting lost in the details of prepping the data and then having to go back and rerun things when I realized I had omitted crucial first steps (if I could even find the do files I had written). Since data management is not something that is taught in my program (and likely not in others), this book is crucial to doing efficient, replicable work. It's a gem-glad I found out about it. Another five-star rating for a Stata Press book, and kudos to J.Scott Long.