Have a question you’d like to run by someone before you speak to your advisor? Getting an error message when you run a regression model in STATA or R? Have a bunch of addresses you’d like to map? Trying to develop a qualitative research plan? These are all questions D-Lab’s consulting services can assist you with.

D-Lab’s consulting services are designed to provide guidance at all stages of your research. Our diverse roster of consultants have expertise in all facets of the research process. The majority of our consultations take place in D-Lab, in our consulting room (356A Barrows Hall) and last 30 to 60 minutes. The consultation is an informal meeting where consultant and consultee(s) discuss the problem and walk through possible solutions. Many times consultants will map our potential answers on a whiteboard or open the statistical program you’re working in and walk you through coding. Our consultations are comfortable meetings where no questions are off limits. Our motto at D-Lab is IOKN2K, “It’s OK not to know”, and our consultants follow this.

 A typical quantitative coding consultation request may look like:

I’m trying to compute some statistics in STATA, mostly means comparisons, and I keep getting an error message...


During the meeting, the consultant asked the test to be rerun to see the actual text of the error message, which was “no observations”. This indicated that there were either no observations associated with the given variable or no readable observations. It turned out to be the latter -- that the set of information associated with the measure of interest were not numeric, rather alpha. In other words, the variable did not contain numbers or ordered information and instead contained an alpha list of levels of education (elementary, middle, high school, college, etc.). We call this a string variable. Most statistical programs, STATA included, cannot run quantitative analysis on non-numeric or ordered data. In this instance we can actually convert the data into something STATA can read because levels of education do have a natural order to them (i.e. college is greater or higher than high school, etc.). This can be done through destringing or encoding processes -- both of which require one line of code. Destringing converts the actual variable so you don’t add any new information to your dataset. Encoding generates a new variable based on the original strong measure, adding a new variable to your dataset.

Our consultant roster is comprised of graduate students, postdocs, faculty, and staff at all levels of expertise, from departments and schools across campus. If you’d like to request a consultation, please visit D-Lab’s consulting page for details. Please include a description of your project, data and what stage you are at in the research process. You can either send a request directly to a consultant if you know their expertise matches your needs or a general request which goes out to all of our consultants. If you are under a time constraint or don’t have a lot of free time for a meeting, we recommend sending a general request since many of our consultants have busy schedules of their own. We look forward to working with you!

Oh, and yes, D-Lab provides consulting services during the summer break, although we have a smaller staff on hand to serve you.  Our summer hours are Monday - Thursday, 10am - 3pm, and run from May 14 to August 10, 2018.


Nora Broege

Nora Broege is a doctoral candidate in the Department of Sociology at the University of California, Berkeley. Her dissertation, Race and the Subjective Experience of Schooling: Micro-Sociological Explanations of Adolescents’ Everyday Lives, employs mixed methods to examine perception and effect(s) of stereotype threat, overall subjective well-being, and goal formation. Her main methodology, a time diary technique (The Experience Sampling Method) substantiates a theory of adolescent achievement grounded in subjective experience.