The Institute for Social Science Research offers free consultation and workshops on social science methods and statistical analysis for students, faculty, and other members of the UMass-Amherst research community. Our consulting service is staffed by a team of advanced graduate students who provide consultation during walk-in hours and by appointment. The team also offers short courses in specific methods and data program packages. Our graduate student consultants are funded by the Graduate School at UMass-Amherst .
Our free consultation services are limited to general advice on standard research methods or more advanced methods that fall within the range of expertise of our consultants.
Spring 2015 consultation hours are walk-in (Monday- Friday, 1:00-4:00 pm, unless lab is reserved) or by appointment.
Thursday-Rodrigo Dominguez Villegas*
*Support for the ISSR Methodology Consultants is generously provided by the UMass Graduate School 
Our walk-in consulting service and training workshops are held in a fully-equipped computing and training lab, located in 107 Bartlett Hall. The lab is equipped with computers pre-loaded with popular software platforms, including:
- Adobe Professional
- Microsoft Office
We also have workspace in the lab for those using their own laptops.
Please check the calendar for our schedule of workshops and general lab availability.
Make an appointment with someone from our consulting team.
ISSR also offers private, customized fee-based consultations specific to principal investigators’ research activities, at a rate of $150 an hour.
Areas of expertise
- Research design
- Data management, coding and processing
- Questionnaire design and survey implementation
- Public secondary data sources (Census, Bureau of Economic Analysis, etc.)
- Descriptive analysis and simple hypothesis testing
- Multivariate linear regression
- Logistic regression, including multinomial, ordered, and count-based approaches
- Longitudinal data analysis, including fixed and random effects
- Hierarchical linear/multi-level modeling
- Factor, cluster, and principal components analysis
- Structural equations modeling
- Event history and survival analysis
- Propensity score
- Measurement error
- Multiple imputation and missing data
- Data visualization and graphics
- Network analysis and exponential random graph modeling
- Survey-weighted statistical methods
- Spatial data analysis
- Structured interviewing methods and NVivo coding
- Archival research
- Content analysis, coding, and use of descriptive statistics in qualitative research
- Design of comparative and case study-based research