The impact of confounder selection criteria on effect estimation

American Journal of Epidemiology

Volumn 129, Issue 1, 1989, Pages 125-137

  Mickey, Ruth M ^a   Greenland, Sander ^b  

^a UNIVERSITY OF VERMONT   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Epidemiologic methods

Indexed keywords

CASE CONTROL STUDY; CONFIDENCE INTERVAL; CONTROLLED STUDY; EPIDEMIOLOGY; HUMAN; METHODOLOGY; PRIORITY JOURNAL; SHORT SURVEY; STATISTICS; SYSTEM ANALYSIS; THEORETICAL STUDY;

EPIDEMIOLOGIC METHODS; MATHEMATICS; RESEARCH DESIGN; SUPPORT, U.S. GOV'T, P.H.S.;

EID: 0024592074     PISSN: 00029262     EISSN: None     Source Type: Journal    
DOI: 10.1093/oxfordjournals.aje.a115101     Document Type: Article

References (21)

1. Fleiss JL. Signficance tests have a role in epidemiologic research: reactions to A. M. Walker. Am J Public Health 1986;76:559-60.
2. Miettinen OS. Stratification by a multivariate confounder score. Am J Epidemiol 1976;104:609-20.
3. Dales LG, Ury HK. An improper use of statistical significance testing in studying covariables. Int J Epidemiol 1978;4:373-5.
4. Greenland S, Neutra RR. Control of confounding in the assessment of medical technology. Int J Epidemiol 1980;9:361-7.
5. Breslow NE, Day NE. Statistical methods in cancer research. Vol 1. The analysis of case-control studies. (IARC scientific publication no. 32). Lyon: International Agency for Research on Cancer, 1980.
6. Schlesselman JJ. Case-control studies: design, conduct, analysis. New York: Oxford University Press, 1982.
7. Kleinbaum DG, Kupper LL, Morgenstern H. Epidemiologic research: principles and quantitative methods. Belmont, CA: Lifetime Learning Publications, 1982.
8. Rothman KJ. Modem epidemology. Boston: Little, Brown, 1986.
9. Whittemore AS. Collapsibility of multidimensional contingency tables. J R Stat Soc B 1978; 40:328-40.
10. Duchanne GR, Lepage Y. Testing collapsibility in contingency tables. J R Stat Soc B 1986;48:197-206.
11. Greenland S, Mickey RM. Closed-form and dually consistent methods for inference on collapsibility in 2 x 2 x K and 2 x J x K tables. Appl Stat 1988;37:336-43.
12. Mantel N, Haenszel W. Statistical aspects of the analysis of data from retrospective studies of disease. JNCI 1959;22:719-48.
13. Robins JM, Breslow NE, Greenland S. Estimators of the Mantel-Haenszel variance consistent in both sparse data and large strata limiting models. Biometrics 1986;42:311-23.
14. Robins JM, Greenland S. The role of model selection in causal inference from nonexperimental data. Am J Epidemiol 1986; 123:392-402.
15. Robins JM. The statistical foundations of confounding in epidemiology. (Technical report no. 2, Occupational Health Program). Boston: Harvard School of Public Health, 1983.
16. Bunker JP. The national halothane study. Bethesda: National Institute of General Medical Sciences, 1969; chap. IV-5.
17. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studes for causal effects. Biometrika 1983;70:41-55.
18. Pike MC, Anderson J, Day N. Some insights into Miettinen's multivariate confounder score approach to case-control study analysis. J Epidemiol Community Health 1979;33:104-6.
19. Rosenbaum PR, Rubin DB. Reducing bias in observational studies using subclassiQcation on the propensity score. J Am Stat Assoc 1984;79:916-24.
20. Cochran WG. The effectiveness of adjustment by subclassification in removing bias in observational studies. Biometrics 1968;24:295-313.
21. Griffiths WE, Hill RC, Pope PJ. Small sample properties of probit model estimators. J Am Stat Assoc 1987, 82:929-37.