Ignorability and stability assumptions in neighborhood effects research

Statistics in Medicine

Volumn 27, Issue 11, 2008, Pages 1934-1943

  VanderWeele, Tyler J ^a  

^a UNIVERSITY OF CHICAGO   (United States)

Author keywords

Causal inference; Ignorability; Multilevel models; Neighborhood effects; Potential outcomes

Indexed keywords

AGE DISTRIBUTION; ANALYTICAL ERROR; ARTICLE; COMMUNITY ASSESSMENT; CONTROLLED STUDY; CORRELATION ANALYSIS; FEASIBILITY STUDY; HEALTH STATUS; HOSPITAL BUILDING; HUMAN; INDIVIDUALIZATION; MATHEMATICAL COMPUTING; OUTCOMES RESEARCH; RACE DIFFERENCE; SEX RATIO; SOCIOECONOMICS; TREATMENT OUTCOME;

CAUSALITY; MODELS, STATISTICAL; RESIDENCE CHARACTERISTICS;

EID: 42949106515     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3139     Document Type: Article

References (36)

1. Wagenaar AC, Murray DM, Wolfson M, Forster JL, Finnegan JR. Communities mobilizing for change on alcohol: design of a randomized community trial. Journal of Community Psychology CSAP, Special Issue 1994; 79-101.
2. Del Conte A, Kling J. A synthesis of MTO research on self-sufficiency, safety and health, and behavior and delinquency. Poverty Research News 2001; 5:3-6.
3. Hannan PJ. Experimental social epidemiology-controlled community trials. In Methods in Social Epidemiology, Oakes JM, Kaufman JS (eds). Jossey-Bass: San Francisco, CA, 2006.
4. Kling JR, Liebman JB, Katz LF. Experimental analysis of neighborhood effects. Econometrica 2007; 75:83-119.
5. Sobel ME. What do randomized studies of housing mobility demonstrate?: causal inference in the face of interference. Journal of the American Statistical Association 2006; 101: 1398-1407.
6. Diez Rouz A, Nieto F, Muntaner C. Neighborhood environments and coronary heart disease: a multilevel analysis. American Journal of Epidemiology 1997; 146:48-63.
7. Sampson RJ, Raudenbush SW, Earls F. Neighborhoods and violent crime: a multilevel study of collective efficacy. Science 1997; 227:918-923.
8. Subramanian SV, Kim DJ, Kawachi I. Social trust and self-rated health in US communities: a multilevel analysis. Journal of Urban Health 2002; 79:S21-S34.
9. Browning CR, Wallace D, Feinberg S, Cagney KA. Neighborhood social processes and disaster-related mortality: the case of the 1995 Chicago heat wave. American Sociological Review 2006; 71:665-682.
10. Rubin DB. Estimating causal effects of treatments in randomized and nonrandomized studies. Journal Educational Psychology 1974; 66:688-701.
11. Rubin DB. Bayesian inference for causal effects: the role of randomization. Annals of Statistics 1978; 6:34-58.
12. Robinson WS. Ecological correlations and the behavior of individuals. American Sociological Review 1950; 15:351-357.
13. Duncan OD, Cuzzort RP, Duncan B. Statistical Geography: Problems in Analyzing Areal Data. Greenwood Press: Westport, CT, 1961.
14. Greenland S, Morgenstern H. Ecological bias, confounding, and effect modification. American Journal of Epidemiology 1989; 18:269-274.
15. Rothman KJ, Greenland S. Modern Epidemiology. Lippincott-Raven: Philadelphia, PA, 1998.
16. Greenland S. Divergent biases in ecologic and individual-level studies. Statistics in Medicine 1992; 11:1209-1223.
17. Greenland S, Robins JM. Invited commentary: ecologic studies - biases, misconceptions, and counterexamples. American Journal of Epidemiology 1994; 139:747-760.
18. Greenland S. A review of multilevel theory for ecologic analyses. Statistics in Medicine 2002; 21:389-395.
19. Haneuse S, Wakefield J. Hierarchical models for combining ecological and case-control data. Biometrics 1992; 63:128-136.
20. Haneuse S, Wakefield J. The combination of ecological and case-control data. Working Paper 292, Berkeley Electronic Press, UW Biostatistics Working Paper Series. Available from: http://www.bepress.com/uwbiostat/paper292.
21. Spirtes P, Glymour C, Scheines R. Causation, Prediction and Search. Springer: New York, 1993.
22. Dawid AP. Causal inference without counterfactuals. Journal of the American Statistical Association 2000; 95:407-424.
23. Gelman A, Hill J. Data Analysis Using Regression and Multilevel/ Hierarchical Models. Cambridge University Press: Cambridge, 2007.
24. Murray D. Design and Analysis of Group-randomized Trials. Oxford University Press: New York, 1998.
25. Hong G, Raudenbush SW. Evaluating kindergarten retention policy: a case study of causal inference for multilevel observational data. Journal of the American Statistical Association 2006; 101:901-910.
26. Verbitsky N, Raudenbush SW. Causal inference in spatial settings: a case study of community policing program in Chicago. Working Paper.
27. Greenland S, Pearl J, Robins JM. Causal diagrams for epidemiologic research. Epidemiology 1999; 10:37-48.
28. Greenland S. Quantifying biases in causal models: classical confounding vs collider-stratification bias. Epidemiology 2003; 14:300-306.
29. Pearl J. Causal diagrams for empirical research. Biometrika 1995; 82:669-688.
30. Pearl J. Causality: Models, Reasoning, and Inference. Cambridge University Press: Cambridge, 2000.
31. Glymour MM. Using causal diagrams to understand common problems in social epidemiology. In Methods in Social Epidemiology, Oakes JM, Kaufman JS (eds). Jossey-Bass: San Francisco, CA, 2006.
32. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika 1983; 70:41-55.
33. Rubin DB. Estimating causal effects from large data sets using propensity scores. Annals of Internal Medicine 1997; 127:757-763.
34. Oakes JM, Johnson PJ. Propensity score matching for social epidemiology. In Methods in Social Epidemiology, Oakes JM, Kaufman JS (eds), Jossey-Bass: San Francisco, CA, 2006.
35. Oakes JM. The (mis)estimation of neighborhood effects: causal inference for a practicable social epidemiology. Social Science and Medicine 2004; 58:1929-1952.
36. Greenland S, Robins JM, Pearl J. Confounding and collapsibility in causal inference. Statistical Science 1999; 14:29-46.