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1. IRB approval: If you do not have IRB approval, go here and read carefully. "Under Federal regulations and University policy, all researchers who conduct research that involves human subjects or materials of human origin must submit an application to the IRB. Approval of the research protocol must be in place BEFORE the research begins." If you are using secondary data, please verify with the Office of Research Administration (see link above) on whether you need approval. If you need it but do not obtain it, you cannot use the results of your research.17Apr2011
2. Using Stata: If you do not have experience with Stata or would like a refresher, I suggest that you work through the "Getting Started Using Stata" before the course begins.
3. Accounts before class begins: Get an MDSS (same as SDA) account for mass storage. Details are here. Please apply immediately since delays in getting an account might occur.
4. Books: Click here for ordering books.
5. External drive: I encourage everyone to have an external drive to use for backup and testing methods for preserving data. You can buy these on sale for as little as $50. I recommend a drive that does NOT require external power but rather gets power for the USB for Firewire port. Depending on the size of your dataset, a flash drive might work.
6. Setting up your computer: Before class begins, I encourage you to: a) Install Dropbox;
   b) Link to MDSS from your computer; c) Install a file manager and text editor (suggestions are here); d) Use IUware to install Acrobat XI; to find it, Google "IUware Windows" or "IUware Mac"; e) Having Stata installed on your computer is helpful but not required; f) Make sure your computer will connect to the IU wireless system.
7. Dropbox: We will use Dropbox to exchange materials. Feel free to start using it now.
8. CLASSPAK: This should be available late April 2013. If the bookstore doesn't have copies of the ClassPak, go to the textbook register at the IU Bookstore and purchase a voucher. They will have a copy of the ClassPak by 3PM the next day. If you have problems, talk to Kathy Parker cparker@indiana.edu.

Schedule

• To be completed...

Detailed description of class

This intensive workshop helps you develop a workflow for conducting complex statistical research. Workflow in data analysis is a framework for the entire research process: planning, organizing, and documenting your work; importing data; naming, labeling, documenting, creating, and verifying variables; conducting and presenting statistical and graphical analyses; and preserving your work. Each step is guided by the demands of producing replicable and accurate results while working as quickly and efficiently as possible. While traditional classes in statistics deal with estimating and interpreting models, in "real world" research statistical analyses often involve less than ten percent of the total work. This class focuses on the other ninety percent. Developing an efficient workflow saves time, improves accuracy, and leads to replicable results. This two-week workshop explores the following topics.

1, General principles that guide your research: replicability, accuracy, and efficiency.

2. Efficient methods for planning, organizing, documenting, executing, and preserving your work.

3. Tools that enhance and simplify your work: software, programming methods, organizational structure, and cyberinfrastructure.

4. Real world examples of what works and what does not in each stage of the process.

• Planning and organizing research
• Preparing data for analysis: importing data; developing consistent names and labels; documenting the sample and variables; and cleaning the data.
• Conducting sophisticated data analysis that is replicable and efficient.
• Accurately and quickly incorporating complex statistical results into your writing and presentations while maintaining the provenance of each result.
• Methods to speed up the inevitable process of revising your work.
• How to prevent catastrophic loss of files during the project and to ensure long term preservation of your materials.

While many software tools are illustrated, Stata is the primary package for data management and analysis and the course will use Long (2009) The Workflow of Data Analysis Using Stata.. While the methods apply readily to other statistical packages, students must have some familiarity with Stata. If you are not familiar with Stata, you take the Stata netcourse NC101 or study an introduction to Stata (e.g., chapters 3 and 4 of my Workflow book).

Requirements: Each student is expected to develop her own workflow and apply it to a real research project. The class is too short to complete the project, but you can develop critical skills to help you complete future research more quickly and accurately while ensuring replicability and maintaining the provenance of results. Students must participate in class, complete exercises applying the lectures to their project, develop a mock file structure with backup procedures, maintain a research log, and present their "final" workflow to the class. While some lab time for independent work will be available during the day, students will also need to work on their project outside of class.

Books

1. ClassPak - be sure to bring this the first day of class. It includes lecture notes and reprints. Required.
2. Long, J.S. 2008, The Workflow of Data Analysis Using Stata. Stata Press.College Station, TX. The book is cheaper from Stata Corp than at amazon.com, but if you have free shipping, amazon.com might be cheaper. Some copies of this book will be at the book store.
3. Wong, Dona M. 2010. The Wall Street Journal Guide to Information Graphics: The Dos and Don'ts of Presenting Data, Facts, and Figures. Highly recommended for tables and graphs.

Computing

Windows

Notepad++: A highly recommended, freeware editor. Information on enhancing Notepad++ for work with Stata is here.

muCommander: A nice, freeware file manager.

AutoHotkey: A freeware macro program.

Mac OSX

TextWrangler: A highly recommended, freeware editor.

muCommander: A very nice, freeware file manager. Highly recommended.

Enrolling in Soc 751

Authorization is required for enrollment to make sure that each student has sufficient quantitative experience to benefit from the course and has a research project that they can use in class.

Getting ready

There are several things you can do to get ready for the class.

1. Spend time working with Stata.

2. Get the materials ready for your project, such as datasets and codebooks. Begin planning your project and try loading your data in Stata.

3. Think about how you want to organize your files.

4. Gather all of the materials that you used for a quantitative research project. Try to replicate the results from the project.