Developing the Data Analytic Plan

  • H. Gerry Taylor


Preparing grant applications is a difficult and anxiety-laden process for everyone. The problems we face and the obstacles we must overcome for successful grantsmanship are similar, whatever our area of interest or theoretical bent. Although the primary aim of this chapter is to discuss components of the data analytic section of a grant proposal, my larger purpose is to review the grant-writing process more generally. It is impossible to write a competitive data analytic section without having first developed a sound rationale and appropriate study design. The data analytic section provides necessary details regarding data analytic plan, but this section will only make sense if the applicant has already set forth a clear and defensible rationale, formulated testable hypotheses, attended to potential methodological pitfalls, proposed an appropriate study design, and convinced the reviewer that the study is both novel and feasible.


Multivariate Statistics Grant Application Grant Proposal Data Analytic Plan Sound Rationale 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Additional Reading

  1. Bock, R. D. 1975. Multivariate Statistics for the Behavioral Sciences. New York: McGraw-Hill.Google Scholar
  2. Cohen, J. 1977. Statistical Power Analyses for the Behavioral Sciences. New York: Academic Press.Google Scholar
  3. Cohen, J., und Cohen, P. 1983. Multiple Regression/Correlational Analyses for the Behavioral Sciences Hillsdale, NJ: Erlbaum.Google Scholar
  4. Feinstein, A. R. 1988. Scientific standards in epidemiologic studies of the menace of daily life. Science 242 1257–1263.Google Scholar
  5. Huberty, C. J., und Morris, J. D. 1989. Multivariate analysis versus multiple univariate analysis. Psychological Bulletin 105 (2): 302-308.Google Scholar
  6. Kleinbaum, D. G., Kupper, L. L., und Muller, K. E. 1988. Applied Regression Analysis and Other Multivariate Meihods ( 2nd ed. ). Boston: P.W.S. Kent.Google Scholar
  7. O’Brien, R. G., und Kaiser, M. K. 1985. MANOVA method for analyzing repeated measure designs: An extensive primer. Psychological Bulletin 97: 316–333.PubMedCrossRefGoogle Scholar
  8. Schlesselman, J. J. 1982. Case-Control Studies: Design, Conduct, Analysis. New York: Oxford.Google Scholar
  9. Tabachnick, B. G., und Fedeli, L. S. 1983. Using Multivariate Statistics. New York: Harper und Row.Google Scholar

Copyright information

© Springer Science+Business Media New York 1995

Authors and Affiliations

  • H. Gerry Taylor

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