SSRC Eurasia Quantitative Methods Webinar Grantwriting for Quantitative Research

1. SSRC Eurasia Quantitative Methods WebinarGrantwriting for Quantitative Research Professor Jane Zavisca University of Arizona January 25, 2013 janez@u.arizona.edu

2. Developing a Quantitative Research Agenda • Possible but limited without funding • Why do you need funding? • To buy data: new fieldwork or secondary data • To buy equipment: hardware/software • To buy time: research assistance, course releases • To get/keep a job that values external grants

3. Start small and build up • Be realistic: big grants go to people with proven track records • Be ambitious: apply for leveraging grants to support a longer-term agenda

4. My trajectory • Grants as graduate student • Fulbright-Hays to support qualitative/historical research ($15,000) • NSF dissertation improvement grant (plus internal supplement) to support modest survey in one city ($20,000) • Grants as assistant professor • SSRC postdoctoral fellowship to support pilot qualitative research for new study ($20,000) • NCEEER grant to pay for qualitative data collection and to purchase quantitative data ($32,000)

5. Grants as associate professor. Co-PI with Ted Gerber, full professor at University of Wisconsin • NSF grant to support a large retrospective survey in Russia, to test hypotheses drived from my NCEEER/SSRC-supported research ($250k) • Mystery grant to support four-country, longitudinal survey, building on the NSF work ($3.5 million). [Funder has not yet announced award publicly]

6. Types of quantitative research that warrant external funding • Collect original survey data • Costly, time-consuming risky • Tailor design to your research agenda • Piggyback on existing surveys • Cheaper, logistically simpler • Constrained in length and content • New uses for existing data • Combine existing sources in new ways • Use old data to answer new questions

7. Types of funders • Area studies • NCEEER, SSRC • International/comparative studies • Fulbright. Some fellowships suffice for small scale surveys • Defense/Homeland Security. Minerva Research Initiative, DRTA, DARPA • Basic social science • NSF • NIH • Topic-based funding • Spencer Foundation (education) • Macarthur Foundation (various topics)

8. General advice on proposal writing • SSRC: The art of writing proposals • http://www.ssrc.org/publications/view/7A9CB4F4-815F-DE11-BD80-001CC477EC70/ • Great general advice • NIH: Writing a great grant application • http://www.niaid.nih.gov/researchfunding/qa/Pages/writing.aspx#hypo • Geared toward quantitative proposals • Other resources • Ask successful grant-writers for copies of their proposals • If you are at an R1 university, take advantage of internal resources for proposal development (workshops, editing, leveraging funds)

9. Do your homework • Review existing data and literature: to generate hypotheses, and demonstrate novelty of your proposal • Start writing very early – at least 3 months before deadline (your institution’s deadline may differ from sponsor). • Line up collaborators and solicit letters of support

10. Research the funder: • What is the purpose of a given grant, and are you eligible? • What are the selection criteria? • Look for instructions given to reviewers in addition to instructions for applicants. • Structure your proposal around the criteria • Who are the reviewers, and how are they selected? • What are the funder’s broader priorities? • Who are the funder’s own funders? What are their priorities?

11. Pitching quantitative research to Eurasian studies audiences • Appeal to funder’s priorities • NCEEER is funded by US State Department, which has recently called for more quantitative work on the region. • Appeal to novelty/systematicity. • Majority of field research in the region is qualitative • Build on qualitative area expertise to develop quantitative hypotheses

12. Pitching quantitative research to Eurasian studies audiences • Demonstrate your regional knowledge and commitment • Don’t frame only as a theoretical case • Signal commitment to further study in the region • Regional languages: if you don’t know them, explain why you don’t need them for this particular project. • Don’t assume any knowledge of statistics • Use flow charts to depict models • Signal your sophistication to those who do with parenthetical citations, footnotes, appendices

13. Pitching Eurasian context to non-disciplinary audiences • Why should the funder care about your research if they don’t care about your region? • Theoretical advantages • Quasi-natural experiment due to rapid social change • Cross-national variation within comparable contexts • Logistical advantages • Relatively low cost compared to Western contexts • More stable/accessible than other semi-authoritarian regions of the world • OR: …convince them to care about the region • Security issues • Humanitarian concerns • Resources/environment

14. Questions any effective proposal should answer • What is the core question? • Why is it worth answering? • How do you plan to answer it? • What is new about your approach? • What exactly will you do with the time and money provided? • What will you produce? • Why should you be the one to do this research? • Why should the funder pay for it?

15. Writing an effective quantitative proposal • Effective quantitative proposals are more a function of research design than statistics • There should be a tight fit between research questions, concepts, measures, hypotheses, and models

16. At least half of proposal should details the nuts and bolts of what you will do: • what data you will collect (if applicable), how you will ensure its quality, and how you will analyze it. • Justify your specific design choices with reference back to your research questions, theory, and hypotheses

17. Specifics about survey design • Instrument design • Proposed measures—and what concepts they will measure • Survey medium (e.g. face-to-face, computer-assisted, web) • Plans for pretests and pilot tests • Sampling: • Generalizability: how is sample related to population of interest? • Sample size (actual and effective) • Sampling strategy

18. Specifics about survey design • Data collection • Personnel • Field procedures • Quality control • Analytical techniques • Class of statistical models • Examples of models to be tested • Data management plan • Confidentiality, quality, archiving, sharing • Making your data public gives value-added for funder

19. Be careful what you wish for • Is the budget realistic? • Is the timeline realistic? • Do you have adequate institutional support beyond what the grant can provide? • Do you really want to do the proposed research?