Statistics and Methods Clinic
The Department of Psychology currently has two faculty members (Ryne Estabrook & Alexander Demos) and one graduate TA (Andrea Frankenstein) who have dedicated time to assist in research design, statistical consulting, and help with the interpretation of results. Our services are available to all members of the UIC Psychology department, those collaborating with members of our department, and any graduate students who have taken Psychology methods courses. Our goal is to help you do research!
We now have three avenues for help (see below for details).
- Zoom Statistics & Methods lab meetings in BSB 1076 (Tuesday,12:00pm – 12:50am). For Zoom office hours use: Lab Meetings
- Walk-in office hours for help with the TA in BSB 10281 (Wednesday, 12:30 – 1:30pm). For Zoom office hours use: Walk-in office hours
- Private consultation with clinic faculty.
How to get Help:
To help direct you to the appropriate avenue for help, we ask if you want to schedule lab meeting or consult with clinic faculty to first fill out a short Qualtrics form (Note: walk-in TA do not require the form). The clinic TA will review this form, and they will get back to you regarding the next steps. Our goal of this form is to make it easy to keep track of who and when we are assisting so we can spend less time documenting and more time helping you.
Walk-in hour with TA:
Faculty and Grad students can come with questions related to implementation or standard questions about ANOVA/Regression. This is the time to say, “help my code won’t work” or “which contrast is the right one for this ANOVA”.
Details about the Lab Meeting:
Faculty and Grad students can come and ask your design, programming, analysis questions, and all in the room can hear our discussion. All are welcome to attend each week and can just show up. For those who want to work on their data/project or suggest a specific topic, we ask you to fill out the Qualtrics form at least one week in advance to secure a spot (30 or 60 mins).
- Grad students: For example, time to work out an MA/Ph.D. design/analysis plan.
- Lab Directors: Bring your whole lab to discuss anything related to methods you might want a tutorial on.
- If no one signs up that week, we will still hold the meeting for walk-in questions (no sign up necessary) and feel free to bring friends to hear the discussion.
Details about Private Consultations:
Assist in the design of new studies, consult on analysis plans of studies already completed, help with the response to reviewer methods/analysis comments, power analysis related questions, and other methods issues. These meetings will be up to 1 hour long, and if we go over, you will be asked to book the next available meeting time.
- Analysis help: Have the design ready (with all details and if you could visualize it before you arrive that would help).
- Interpretation/Code help: Have datasets loaded and code run (or marked where stuck) and ready to view.
- Design Help: To quote Fisher, “To consult the statistician after an experiment is finished is often merely to ask him to conduct a post mortem examination. He can perhaps say what the experiment died of.” We want to save you grief, so come before you collect data.
- Analysis Help: Guidance in which techniques answer which questions.
- Milestones: We will help you assess the methods you need for your questions. We can often direct you the resources you will need to learn, and the time it will take for your discussions with your committee.
- Code Help: Between us, we can help with R, OpenMx, Matlab, SPSS, and SAS. We will not code it for you, but we can help.
Other Useful Links:
- OpenMx designed in part by our own Dr. Ryne Estabrook
- JAMOVI Open Source GUI R-based program that has ANOVA, regression, mixed models, factor analysis, mediation, meta-analysis, power analysis, and other modules. It’s all “clickity-clickity”, but you might learn R by mistake.
- JASP Open Source GUI stats program which lets you compare frequentist and Bayesian methods.
- UIC Graduate level ANOVA, Regression and mixed models course lectures on the web
- UIC Graduate regression, SEM and mixed models course lectures on the web
- Grad student-written R-webbook