Statistical Consulting

Statistical Consulting

 

The psychology department offers statistics and research consulting to psychology graduate students, psychology postdoctoral fellows, and psychology faculty members. This service is not available to psychology undergraduates or members of other departments. The department’s consultants are available to assist with the research process from the point of design and preregistration through the selection, implementation, and troubleshooting of analytical techniques. To facilitate the consultation process, please email a description of your problem to the consultant with whom you will meet at least 5 days prior to your scheduled appointment. This will give your consultant time to prepare for the consultation and the opportunity to contact you if clarification is needed. Generally speaking, your email should include information on the following:

  1. Research question
  2. Hypothesis
  3. Summary of preliminary analyses performed
  4. Output of analyses you have already performed, if appropriate
  5. Summary of analytical techniques you are considering

 

Meet the Consultants:

 

Dr. Daniel Russell

Office: 2352 Palmer Building

Email (drussell@iastate.edu) to schedule an appointment with Dr. Russell

 

 

 

 

  • Dr. Russell has taught courses on topics such as multivariate statistics and structural equation modeling analysis for nearly 40 years, first at the University of Iowa and since 1992 at ISU. This includes courses for the psychology department and human development and family studies. Particular areas of focus include measurement (both classic and IRT approaches), regression analysis (including multilevel regression), factor analysis, missing data, and power analysis, along with a variety of topics related to SEM analysis. Dr. Russell has taught several one credit classes for the psychology department on these topics. He employs software such as SPSS, SAS, HLM, and Mplus in teaching these courses, along with some specific R programs related to measurement and SEM.

 

Dr. Andrew Smith

Office: 204 Lagomarcino Hall

Login to Google Docs (https://docs.google.com/spreadsheets/u/0/) using the consulting account username and password (see note below) to schedule an appointment with Dr. Smith.

 

 

 

  • Dr. Smith performs experimental research on memory and decision-making primarily in the context of eyewitness identification procedures. This research focus has led him to develop expertise in categorical data analysis, signal detection theory, and receiver operating characteristic (ROC) analysis. He has taught graduate courses covering these techniques and has also taught graduate courses on Advanced ANOVA and experimental design. In addition, he has considerable experience in fitting regression models and some experience in fitting hierarchical linear models (mostly in the context of repeated-measures experiments). Two years ago, Dr. Smith started pre-registering his experiments and has developed some expertise with this process, and he welcomes the opportunity to assist those who are navigating (or are thinking about navigating) this process for the first time. Finally, he has recently taken an interest in Bayesian approaches to data analysis and is currently honing his expertise in this area. In terms of statistical software, he typically uses Excel, SPSS, and R. In the past, he has also used MATLAB and LISREL.

 

Michael Tynan, M.S.

Office: W159 Lagomarcino Hall

Login to Google Docs (https://docs.google.com/spreadsheets/u/0/) using the consulting account username and password (see note below) to schedule an appointment with Michael Tynan.

 

 

 

  • Michael’s research focuses on examining the construct validity of predictors of academic success. Through this research, he has become familiar with regression-based analyses, factor analyses, and meta-analysis. He completed the graduate certificate in quantitative psychology in 2017. He has recently been exploring the benefits of using necessary condition analysis as a supplement to traditional regression-based analyses. The majority of his data collection has been through Qualtrics, and he has used Inquisit in the past. He is most familiar with statistical analyses and data management in Excel, R, SPSS, and Mplus. Michael is excited to work with faculty and graduate students, especially those currently enrolled in quantitative courses or learning a new statistical technique.

 

Additional statistical consulting is available through the department of statistics.

 


NOTE: The consulting account username and password were distributed via email. If you do not have this information, email Dr. Smith.