Cutoff designs for community-based intervention studies

Statistics in Medicine

Volumn 30, Issue 15, 2011, Pages 1865-1882

  Pennell, Michael L ^a   Hade, Erinn M ^a   Murray, David M ^a   Rhoda, Dale A ^a,b  

^a OHIO STATE UNIVERSITY   (United States)

^b BATTELLE MEMORIAL INSTITUTE   (United States)

Author keywords

Community based interventions; Group randomized trials; Intraclass correlation coefficient; Power analysis; Regression discontinuity design

Indexed keywords

ANALYTIC METHOD; ANALYTICAL PARAMETERS; ARTICLE; COHORT ANALYSIS; COMMUNITY ASSESSMENT; CONTROLLED STUDY; CROSS-SECTIONAL STUDY; CUT OFF DESIGN; GROUP RANDOMIZED TRIAL; HUMAN; INTERMETHOD COMPARISON; INTERVENTION STUDY; MATHEMATICAL COMPUTING; PUBLIC HEALTH; RANDOMIZED CONTROLLED TRIAL (TOPIC); REGRESSION ANALYSIS; REGRESSION DISCONTINUITY DESIGN; SAMPLE SIZE; STUDY DESIGN;

ADOLESCENT; ANALYSIS OF VARIANCE; CHILD NUTRITION SCIENCES; COMMUNITY-BASED PARTICIPATORY RESEARCH; CROSS-SECTIONAL STUDIES; DIET; EPIDEMIOLOGIC RESEARCH DESIGN; FEMALE; HEALTH PROMOTION; HUMANS; INTERVENTION STUDIES; MOTOR ACTIVITY; SAMPLE SIZE; SCHOOLS;

EID: 79958730573     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.4237     Document Type: Article

References (35)

1. Horrowitz H. The effectiveness of community water fluoridation in the United States. Journal of Public Health Dentistry 1996; 56:253-258.
2. Stevens J, Murray D, Catellier D, Hannan P, Lytele L, Elder J, Young D, Simons-Morton D, Webber L. Design of the trial of activity in adolescent girls (TAAG). Contemporary Clinical Trials 2005; 26:223-233.
3. Beresford S, Locke E, Bishop S, West B, McGregor B, Bruemmer B, Duncan G, Thompson B. Worksite study promoting activity and changes in eating (PACE): design and baseline results. Obesity 2007; 15:4S-15S.
4. Paskett E, Tatum C, D'Agostino R, Rushing J, Velez R, Michielutte R, Dignan M. Community-based interventions to improve breast and cervical cancer screening: results of the Forsyth County cancer screening (FoCaS) project. Cancer Epidemiology, Biomarkers and Prevention 1999; 8:453-459.
5. Atienza A, King A. Community-based health intervention studies: an overiew of methodologic issues. Epidemiologic Reviews 2002; 24:72-79.
6. Hohmann A, Shear M. Community-based intervention research: coping with the 'noise' of real life in study design. American Journal of Psychiatry 2002; 159:201-207.
7. Murray D. Design and Analysis of Group-randomized Trials. Oxford University Press: New York, 1998.
8. Donner A, Klar N. Design and Analysis of Cluster Randomization Trials in Health Research. Arnold: London, 2000.
9. Katz D, Nawaz H, Jennings G, Chan W, Ballard J, Comerford B, Spargo K, Walsh J. Community health promotion and the randomized controlled trial: approaches to finding common ground. Journal of Public Health Management Practice 2001; 7:33-40.
10. Murray D. Design and analysis of community trials: lessons from the Minnesota Heart Health Program. American Journal of Epidemiology 1995; 15:569-575.
11. Shadish W, Cook T, Campbell D. Experimental and Quasi-experimental Designs for Generalized Causal Inference. Houghton Mifflin Company: Boston, 2002.
12. Trochim W, Cappelleri J. Cutoff assignment strategies for enhancing randomized clinical trials. Controlled Clinical Trials 1992; 13:190-212.
13. Rubin D. Assignment to treatment group on the basis of a covariate. Journal of Educational Statistics 1977; 2:1-26.
14. Cappelleri J, Trochim W, Stanley T, Reichardt C. Random measurement error does not bias the treatment effect estimate in the regression discontinuity design: I. The case of no interaction. Evaluation Review 1991; 15:395-419.
15. Imbens G, Lemieux T. Regression discontinuity designs: a guide to practice. Journal of Econometrics 2008; 142:615-635.
16. Schochet P. Statistical power for regression discontinuity designs in education evaluations. Journal of Educational and Behavioral Statistics 2009; 34:238-266.
17. Lytle L, Murray D, Perry C, Story M, Birnbaum A, Kubik M, Varnell S. School-based approaches to affect adolescents' diets: results from the TEENS study. Health Education and Behavior 2004; 31:270-287.
18. Murray D, Van Horn M, Hawkins J, Arthur M. Analysis strategies for a community trial to reduce adolescent ATOD use: a comparison of random coefficient and ANOVA/ANCOVA models. Contemporary Clinical Trials 2006; 27:188-206.
19. Algina J, Olejnik S. Conducting power analyses for ANOVA and ANCOVA in between-subjects designs. Evaluation and the Health Professions 2003; 26:288-313.
20. Janega J, Murray D, Varnell S, Blistein J, Birnbaum A, Lytle L. Assessing intervention effects in a school-based nutrition intervention trial: which analytic model is most powerful? Health Education and Behavior 2004; 31:756-774.
21. Cook T. 'Waiting for life to arrive': a history of the regression-discontinuity design in psychology, statistics and economics. Journal of Econometrics 2008; 142:636-654.
22. Decker S. Medicare and the health of women with breast cancer. Journal of Human Resources 2005; 40:948-968.
23. Cappelleri J. Cutoff-based designs in comparison and combination with randomized clinical trials. Ph.D. Dissertation, Cornell University, Ithaca, New York, 1991.
24. Goldberger A. Selection bias in evaluating treatment effects: some formal illustrations. Technical Report 123, Institute for Research on Poverty, University of Wisconsin-Madison, Madison, WI, 1972.
25. Cappelleri J, Trochim W. An illustrative statistical analysis of cutoff-based randomized clinical trials. Journal of Clinical Epidemiology 1994; 47:261-270.
26. Goldberger A. Selection bias in evaluating treatment effects: the case of interaction. Technical Report 129, Institute for Research on Poverty, University of Wisconsin-Madison, Madison, WI, 1972.
27. Angrist J, Pischke J. Mostly Harmless Economics: An Empiricist's Companion. Princeton University Press: Princeton, NJ, 2009.
28. Cappelleri J, Darlington R, Trochim W. Power analysis of cutoff-based randomized clinical trials. Evaluation Review 1994; 18:141-152.
29. Gail M, Mark S, Carroll R, Green S, Pee D. On design considerations and randomization-based inference for community intervention trials. Statistics in Medicine 1996; 15:1069-1092.
30. Cohen P, Cohen JSGW, Aiken L. Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences (3rd edn). Lawrence Erblaum: Mahwah, NJ, 2002.
31. Cappelleri J, Trochim W. Cutoff designs. In Encyclopedia of Biopharmaceutical Statistics: 3rd Edition, Revised and Expanded, Chow S (ed.). Informa Healthcare: New York.
32. Murray D, Hannan P, Wolfinger R, Baker W, Dwyer J. Analysis of data from group-randomized trials with repeat observations on the same groups. Statistics in Medicine 1998; 17:1581-1600.
33. Cappelleri J, Trochim W. Ethical and scientific features of cutoff-based designs of clinical trials. Medical Decision Making 1995; 15:387-394.
34. Trochim W, Cappelleri J, Reichardt C. Random measurement error does not bias the treatment effect estimate in the regression-discontinuity design: II. When an interaction is present. Evaluation Review 1992; 15:571-604.
35. Mandell M. Having one's cake and eating it, too: combining true experiments with regression discontinuity designs. Evaluation Review 2008; 32:415-434.