Maybe Small Is Too Small a Term: Introduction to Advancing Small Sample Prevention Science

Prevention Science

Volumn 16, Issue 7, 2015, Pages 943-949

  Fok, Carlotta Ching Ting ^a   Henry, David ^b   Allen, James ^c  

^a UNIVERSITY OF ALASKA FAIRBANKS   (United States)

^b UNIVERSITY OF ILLINOIS AT CHICAGO   (United States)

^c UNIVERSITY OF MINNESOTA MEDICAL SCHOOL   (United States)

Author keywords

Ethnic minority research; Health disparities; Research methods; Small samples; Statistical methods

Indexed keywords

HEALTH SERVICES RESEARCH; ORGANIZATION AND MANAGEMENT; PREVENTIVE HEALTH SERVICE;

HEALTH SERVICES RESEARCH; PREVENTIVE HEALTH SERVICES;

EID: 84942505819     PISSN: 13894986     EISSN: None     Source Type: Journal    
DOI: 10.1007/s11121-015-0584-5     Document Type: Article

References (28)

1. Allen, M. J., & Yen, W. M. (2001). Introduction to measurement theory. Long Grove: Waveland Press Inc.
2. Anderson, J. (2005). Unraveling health disparities: Examining the dimensions of hypertension and diabetes through community engagement. Journal of Health Care for the Poor and Underserved, 16, 91–117. doi:10.1353/hpu.2005.0121.
3. Boomsma, A. (1983). On the robustness of LISREL (maximum likelihood estimation) against small sample size and nonnormality. Amsterdam: Sociometric Research Foundation.
4. Castro, F., & Coe, K. (2007). Traditions and alcohol use: A mixed-methods analysis. Cultural Diversity and Ethnic Minority Psychology, 13, 269–84. doi:10.1037/1099-9809.13.4.269.
5. Centers for Disease Control and Prevention (CDC). (2011). CDC Health Disparities and Inequalities Report – United States. MMWR 2011; 60 (Supplement): 1–114.
6. de Jong, R., & Spiess, M. (2015). Robust multiple imputation. In U. Engel, B. Jann, P. Lynn, A. Scherpenzeel, & P. Sturgis (Eds.), Improving survey methods: Lessons from recent research (pp. 397–411). New York: Routledge/Taylor & Francis Group.
7. Fok, C. C. T., & Henry, D. (2015). Increasing the sensitivity of measures to change. Prevention Science. doi:10.1007/s11121-015-0545-z.
8. Fok, C. C. T., Henry, D., & Allen, J. (2015). Research designs for intervention research with small samples II: Stepped wedge and interrupted time-series designs. Prevention Science. doi:10.1007/s11121-015-0572-9.
9. Forero, C., & Maydeu-Olivares, A. (2009). Estimation of IRT graded response models: Limited versus full information methods. Psychological Methods, 14, 275–299. doi:10.1037/a0015825.
10. Giger, J. N., & Davidhizar, R. (2007). Promoting culturally appropriate interventions among vulnerable populations. Annual Review of Nursing Research, 25, 293–316.
11. Hedeker, D. (2015). Methods for multilevel ordinal data in prevention research. Prevention Science. doi:10.1007/s11121-014-0495-x.
12. Henry, D., Tolan, P. H., & Gorman-Smith, D. (2005). Cluster analysis in family psychology research. Journal of Family Psychology, 19, 121–132. doi:10.1002/jclp.20464.
13. Henry, D., Pavuluri, M. N., Youngstrom, E., & Birmaher, B. (2008). Accuracy of brief and full forms of the Child Mania Rating Scale. Journal of Clinical Psychology, 64, 1–14. doi:10.1002/jclp.20464.
14. Henry, D., Dymnicki, A. B., Mohatt, N., Allen, J., & Kelly, J. G. (2015). Clustering methods with qualitative data: A mixed methods approach for prevention research with small samples. Prevention Science. doi:10.1007/s11121-015-0561-z.
15. Hopkin, C. R., Hoyle, R. H., & Gottfredson, N. C. (2015). Maximizing the yield of small samples in prevention research: A review of general strategies and best practices. Prevention Science. doi:10.1007/s11121-014-0542-7.
16. Hoyle, R. H. (1999). Statistical strategies for small sample research. London: Sage Publications.
17. Hoyle, R. H., & Gottfredson, N. C. (2015). Sample size considerations in prevention research applications of multilevel modeling and structural equation modeling. Prevention Science. doi:10.1007/s11121-014-0489-8.
18. Institute of Medicine (IOM). (2002). Unequal treatment: Confronting racial and ethnic disparities in health care. Washington: The National Academies Press.
19. Kadane, J. B. (2015). Bayesian methods for prevention research. Prevention Science. doi:10.1007/s11121-014-0531-x.
20. Kaplan, D. (2014). Bayesian statistics for the social sciences. New York: Guilford.
21. Kenny, D. A., Mannetti, L., Pierro, A., Livi, S., & Kashy, D. A. (2002). The statistical analysis of data from small groups. Journal of Personality and Social Psychology, 83, 126–37. doi:10.1037/gdn0000022.
22. Lord, F. M. (1980). Applications of item response theory to practical testing problems. Mahwah: Lawrence Erlbaum Associates.
23. Murray, C. J. L., Kulkarni, S. C., Michaud, C., Tomijima, N., Bulzacchelli, M. T., Iandiorio, T. J., & Ezzati, M. (2006). Eight Americas: Investigating mortality disparities across races, counties, and race-counties in the United States. PLoS Medicine, 3, e545. doi:10.1371/journal.pmed.0030545.
24. Prentice, D., & Miller, D. T. (1992). When small effects are impressive. Psychological Bulletin, 112, 160–164. doi:10.1037/0033-2909.112.1.160.
25. Samejima, F. (1996). Graded response model. In W. J. van der Linden & R. K. Hambleton (Eds.), Handbook of modern item response theory (pp. 85–100). New York: Springer Publishing Company.
26. Tanaka, J. S. (1987). ‘How big is big enough?’: Sample size and goodness of fit in structural equation models with latent variables. Child Development, 58, 134–46. doi:10.1111/j.1467-8624.1987.tb03495.x.
27. van Buuren, S. (2011). Multiple imputation of multilevel data. In J. Hox & J. K. Roberts (Eds.), Handbook for advanced multilevel analysis (pp. 173–196). New York: Routledge/Taylor & Francis Group.
28. Wyman, P. A., Henry, D., Knoblauch, S., & Brown, C. H. (2015). Designs for testing group-based interventions with limited number of social units: The dynamic wait-listed and regression point displacement designs. Prevention Science. doi:10.1007/s11121-014-0535-6.