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Research Technology Consulting

Research Technology Consulting. Simo Goshev Alex Storer Steve Worthington Ista Zahn support@help.hmdc.harvard.edu http://rtc.iq.harvard.edu. Consulting Goals. Data analysis support and programming services

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Research Technology Consulting

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  1. Research Technology Consulting SimoGoshevAlex StorerSteve WorthingtonIsta Zahn support@help.hmdc.harvard.edu http://rtc.iq.harvard.edu

  2. Consulting Goals • Data analysis support and programming services • Research project planning and guidance selecting appropriate technology for research projects • Facilitating appropriate organization, storage and sharing of data • Training on the use of both established software packages and emerging tools

  3. Scope • Free! • Support the entire social science community • Consults measured in hours rather than weeks or months • Currently doing outreach to departments, student groups and centers • Drop-ins on Fridays at 1pm in the training lab, Appointments, Help Tickets and casual chats in K306

  4. Scope Who We Are Ista Zahn SimoGoshev Steven Worthington Alex Storer Psychology Economics BiologicalAnthropology Neuroscience

  5. Alex Storer • BS,BA - UC Berkeley Electrical Engineering & Computer Science, Cognitive Science • PhD – Boston University Cognitive & Neural Systems • Analysis: • Machine Learning • Signal Processing • Surface Based Techniques • Simulation • Optimization • Tools: • Matlab, R, Python • Emacs, LaTeX, Linux

  6. Steve Worthington • BA / MS – Durham, UK Anthropology & Archeology • PhD – NYU Biological Anthropology • Analysis: • Linear models (OLS, GLS, PLS, etc.) • Resampling (permutation, bootstrap) • Ordination (PCA, LDA, CVA, etc.) • Tools: • Mainly R • Some SAS, SPSS • Aquamacs

  7. Choropleth Maps Soda Coke Pop Other

  8. Map Workflow • Spatial data • Attribute data • Shapefiles, ArcGIS files,etc. • State, county, or zipcode level data on any topic. • Merge by spatial ID • e.g., state or county name. • Map

  9. ICPSR example workflow • USA Spatial data • ICPSR Attribute data • ICPSR county level data 2003-2005 • Unemployment rate, Crime rate, Federal spending etc. • Long data frame • CreateMapusing R

  10. Cleaning / Merging data • Spatial data • Attribute data • ICPSR county level data 2003-2005 • Unemployment rate, Crime rate, Federal spending etc. • Long data frame • CreateMap using R

  11. Cleaning / Merging data • Spatial data • Attribute data • ICPSR county level data 2003-2005 • Unemployment rate, Crime rate, Federal spending etc. • Long data frame • CreateMap using R

  12. Unemployment Rate 2005 (annual average estimate)

  13. Unemployment Rate 2005 (annual average estimate) 20.9% 1.9%

  14. Unemployment Rate 2005 (annual average estimate) 20.9% 1.9%

  15. Unemployment Rate 2005 (annual average estimate) 1.9% 20.9%

  16. Unemployment Rate 2005 (annual average estimate) 1.9% 20.9%

  17. Crime Rate 2004 (annual average per 100K people) 0 13700

  18. SimoGoshev • BA – Sofia, Bulgaria Applied Econometrics • MS – McMaster University Statistics • PhD – McMaster University Economics • Analysis: • Econometrics Applied Microeconometrics • Panel Data • Applied statistics • Tools: • Mainly Stata • Some R

  19. Help with econometrics and/or Stata • How do I bootstrap estimates from survey data? • Stata does not support weighting for the type of graph I want to create. Can you help? • I want to study the factors underpinning scholar migration. What identification strategies would you suggest? • I have two datasets and I want to merge them. However, there are not unique case ID’s in either. What would you recommend? • I have a large and highly sensitive dataset stored in a SQL database. Can you help me access the database directly from within Stata?

  20. Help with computation/estimation • I am trying to estimate a model but for some reason the routine fails. Could you have a look at my script ? • I am working with a large dataset and my machine is giving up on me. Do you have any suggestions? • Which estimation method is best for…?

  21. Re-normalized Multinomial Logit • Common normalization in multinomial logit

  22. But what if different normalization is needed?

  23. Ista Zahn • BS – University of Oregon Psychology • PhD (ABD) – University of Rochester Social Psychology • Analysis: • Regression • Mixed Models • Scale Development • Tools: • R, Stata, SAS, SPSS • Emacs, LaTeX, Linux

  24. Workshops(schedule at http://rtc.iq.harvard.edu)

  25. Other Workshops

  26. IQSS Services THE INSTITUTE FOR Quantitative Social Science at Harvard University Research Computing Environment

  27. Contact Us! support@help.hmdc.harvard.edu http://rtc.iq.harvard.edu/ CGIS-Knafel, Room K306 Fridays afternoons, K018 Twitter: @iqssrtc

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