Original Article

Academic Psychiatry

, Volume 33, Issue 3, pp 221-228

Integrating Statistical and Clinical Research Elements in Intervention-Related Grant Applications: Summary From an NIMH Workshop

  • Joel T. SherrillAffiliated withDivision of Services and Intervention Research (DSIR), NIMH
  • , David I. SommersAffiliated withDivision of Extramural Activities, NIMH Email author 
  • , Andrew A. NierenbergAffiliated withDepartment of Psychiatry at MGH
  • , Andrew C. LeonAffiliated withDepartment of Psychiatry, Weill Medical College of Cornell University
  • , Stephan ArndtAffiliated withIowa Consortium for Substance Abuse Research, University of Iowa Hospitals and Clinics
  • , Karen Bandeen-RocheAffiliated withDepartment of Biostatistics, Johns Hopkins Bloomberg School of Public Health
  • , Joel GreenhouseAffiliated withDepartment of Statistics, Carnegie Mellon
  • , Donald GuthrieAffiliated withUCLA
  • , Sharon-Lise NormandAffiliated withHarvard Medical School
    • , Katharine A. PhillipsAffiliated withDivision of Services and Intervention Research (DSIR), NIMHDepartment of Psychiatry & Human Behavior, Brown University
    • , M. Katherine ShearAffiliated withDivision of Services and Intervention Research (DSIR), NIMHSchool of Social Work, Columbia University
    • , Robert WoolsonAffiliated withDivision of Services and Intervention Research (DSIR), NIMHDepartment of Psychiatry/Biostatistics, Medical University of South Carolina

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The authors summarize points for consideration generated in a National Institute of Mental Health (NIMH) workshop convened to provide an opportunity for reviewers from different disciplines—specifically clinical researchers and statisticians—to discuss how their differing and complementary expertise can be well integrated in the review of intervention-related grant applications.


A 1-day workshop was convened in October, 2004. The workshop featured panel presentations on key topics followed by interactive discussion. This article summarizes the workshop and subsequent discussions, which centered on topics including weighting the statistics/data analysis elements of an application in the assessment of the application’s overall merit; the level of statistical sophistication appropriate to different stages of research and for different funding mechanisms; some key considerations in the design and analysis portions of applications; appropriate statistical methods for addressing essential questions posed by an application; and the role of the statistician in the application’s development, study conduct, and interpretation and dissemination of results.


A number of key elements crucial to the construction and review of grant applications were identified. It was acknowledged that intervention-related studies unavoidably involve trade-offs. Reviewers are helped when applications acknowledge such trade-offs and provide good rationale for their choices. Clear linkage among the design, aims, hypotheses, and data analysis plan and avoidance of disconnections among these elements also strengthens applications.


The authors identify multiple points to consider when constructing intervention-related grant applications. The points are presented here as questions and do not reflect institute policy or comprise a list of best practices, but rather represent points for consideration.