The ISSR offers free consultation and workshops on social science methods and statistical analysis for students, faculty, and other members of the UMass-Amherst research community. For other consultation resources on campus please see here.
Our consulting service is staffed by a team of advanced graduate students funded by the Graduate School who provide walk-in consultation in the ISSR Training Lab and by appointment. The lab is also open to researchers who do not need assistance, but require access to computers with specialized analytical software or just a quiet place to work. The expertise of our staff covers a range of popular analytical computer platforms and methods. This team is coordinated by ISSR Methodologist Henry Renski, who will address more complex consultation issues and forward cases to a network of faculty affiliates within specialized methodological areas. The team also offers short courses in specific methods and data program packages.
As a free service to the UMASS research community, our 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. While we pride ourselves on our flexibility, we can’t be expected to be experts in every possible method within every social science discipline. ISSR also offers a customized consultation program specific to a PI's research activity. PI's and project personnel can consult with graduate student advisors at $25/hour and faculty advisors at $100/hour.
Areas of expertise
- Research design
- Data management, coding, and processing
- Questionnaire design and survey implementation
- Public secondary data sources (Census, Economic Statistics, etc.)
- Access & Excel
- Descriptive analysis and simple hypothesis testing
- Multivariate linear regression
- Logistic regression, including multi-nomial, ordered, and count-based approaches
- Longitudinal data analysis (fixed and random effects)
- Hierarchical linear/multi-level modeling
- Factor, cluster, and principle components analysis
- Structural equations modeling
- Event history/survival analysis
- Propensity score
- Measurement error
- Multiple imputation and missing data
- Data visualization and graphics
- Network analysis and ERG 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
Our walk-in consulting service and training workshops are held in a fully-equipped computing and training lab, located in W37E Machmer, 3rd Floor, West Wing. The lab is equipped with a number of laptop computers that have been pre-loaded with a variety of popular software platforms, including: STATA, NVivo, R, SAS, SPSS, Adobe Professional, and MS Office. We also have high-speed internet connections and workspace for those working on their own laptops. Come visit us if you need to access to computing software, have research questions, or are just looking for a place to work on your research studies.
The lab is typically open to the general public from 1:00 to 4:00 during the regular semester, unless it has been reserved for training. Please check the calendar for our schedule of workshops and general lab availability. The table below lists the staffing of our walk-in service for the fall semester 2012. Nearly all of our consultants are capable of answering general and basic questions pertaining to data management and statistical analysis, although some have particular expertise working in a specific software platform or with a particular mode of analysis. So if you have questions specific to a particular program or analytical method, follow the links from the table to our staff bios.
The ISSR training lab will resume daily hours in the fall.
Statistical Consulting Staff Bios and Areas of Expertise
Henry Renski – ISSR Methodologist Dr. Renski is an Assistant Professor in the Department of Landscape Architecture and Regional Planning. His research interests include the study of spatial variations in regional development patterns, specifically entrepreneurship, industrial concentration, and human capital. He is also interested in applied methods of demographic and economic analysis, such as population forecasting, measuring inequality and polarization, economic impact analysis, spatial patterns of development and quantitative approaches to measuring the impact of state and local economic development policies.
Software: SAS, ArcGIS, GeoDa, STATA (proficient), SPSS (proficient)
Methods: Research design, descriptive analysis, multivariate regression, logistic regression, event history analysis, hierarchical/multi-level modeling, survey-weighted data, spatial analysis, applied demography, program impact evaluation.
Jessica Looze is a doctoral candidate in Sociology. Her research focuses on the intersection of women's paid work in the labor market and their unpaid carework at home. Her dissertation examines the effects of children, job changes and employment interruptions on women's career earnings trajectories.
Software: STATA (proficient)
Methods: Multivariate regression, logistic regression, multinomial logistic regression, longitudinal data analysis, fixed effects regression, event history analysis, survey-weighted data, scale construction and measurement, multiple imputation for missing data.
Jackie Stein is a graduate student in the Sociology Department. Her research interests include the impacts of worktime control on worker well-being, public understandings of stratification and inequality, narrative analysis of public opinion, and social policy. She has done both qualitative and quantitative work with survey, interview, and textual data.
Software: SPSS (basic), Zotero(Basic), STATA (intermediate), NVivo (Advanced), MS Office (Advanced)
Methods: coding and analysis of qualitative data, database creation and management, multivariate regression, categorical data analysis.
Chris Burns is a fourth year Ph. D. candidate in Resource Economics. His research interests include the studying the effects of measurement error in a panel data model setting and the implications of measurement error in resource economic modeling.
Software: SAS, R, STATA
Methods: Applied econometrics, multivariate regression, measurement error, panel data and time series modeling
Chris Smith is a doctoral student in sociology working on her dissertation research. Her research interests include crime and inequality, feminist criminology, organized crime, social network analysis, and social policy. She has research expertise in mixed methods approaches integrating social network analysis and historical narrative based on archival research.
Software: STATA, MS Office, R
Methods: database creation and management, social network analysis, multivariate regression, categorical data analysis, coding of newspapers and archival documents
Owen Thompson is a PhD candidate in Economics. His research is primarily focused on labor economics, health economics and economic demography, and typically involves the manipulation and analysis of large nationally representative imicro-data sets such as the Census or ACS, the NLSY, the CPS, the NHIS, or Add Health, as well as data from administrative sources. Topics of particular interest include the determinants of wages and labor market success, racial disparities in health and employment outcomes, the lasting impact of early childhood experiences on economic outcomes, and US inequality trends.
Software: Stata, but also has some familiarity with SPSS, R and SAS.
Methods: Multiple regression and related techniques such as panel data methods, fixed effects, limited dependent variable models, quantile regression, non-parametrics, cluster and heteroskedasticity robust inference, and bootstrapping. Causal-effect methodologies such as instrumental variables, regression discontinuity designs, and difference-in-differences. Owen is also a reasonably good at Stata programing techniques, such using local and global macros, writing various kinds of loops, and performing simulations.