Potentialities and Limitations of Multilevel Analysis in Public Health and Epidemiology

  • Ana V. Diez Roux
Part of the Methodos Series book series (METH, volume 2)


Like demography, discussed in the previous chapter, epidemiology traces its origins back to the investigations of John Graunt in the seventeenth century. But the two disciplines soon diverged because of their different objectives: demography seeks to understand how populations evolve in time and space, by interconnecting the phenomena that determine their size and composition, whereas epidemiology tries to understand the history of public-health problems affecting those populations and to combat them. As a result, epidemiology has evolved differently from demography over the centuries. In particular, it has used new aggregation levels and posed new questions, which this contribution will now examine.


Group Level Multilevel Analysis Individual Level Variable Individual Level Factor Disease Causation 
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  1. Alker, H. R. (1969). A typology of ecological fallacies. In M. Dugan and S. Rokkam (Eds.), Social Ecology (pp. 69–86 ). Boston: The MIT Press.Google Scholar
  2. Almeida Filho, N. (1992). Epidemiologia sin números. Serie Paltex, 28. Washington DC: Panamerican Health Organization.Google Scholar
  3. Blakely, T. A., and Woodward, A. J. (2000). Ecological effects in multi-level studies. Journal of Epidemiology and Community Health, 54, 367–374.CrossRefGoogle Scholar
  4. Blalock, H. M. (1984). Contextual-effects models: theoretical and methodological issues. Annual Review of Sociology, l0, 353–372.CrossRefGoogle Scholar
  5. Boyle, M. H., and Willms, J. D. (1999). Place effects for areas defined by administrative boundaries. American Journal of Epidemiology, 149, 577–85.CrossRefGoogle Scholar
  6. Bryk, A. S., and Raudenbush, S. W. (1992). Hierarchical linear models: applications and data analysis methods. Newbury Park, CA: Sage.Google Scholar
  7. Bunge, M. (1979). Causation and determination, causalism and determinism. In Causality in Modern Science (pp. 3–30 ). New York: Dover Publications.Google Scholar
  8. Catalano, R. (1979). Paradigm succession in the study of public health. In R. Catalano, and R. A. Catalano (Eds.), Health, behavior, and the community. An ecological perspective (pp. 87137 ). Oxford: Pergamon Press.Google Scholar
  9. Charlton, B. (1996). Should epidemiologists be pragmatists, biostatisticians or clinical scientists? Epidemiology, 7, 552–554.Google Scholar
  10. Clayton, D., and Kaldor, J. (1987). Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics, 43, 671–681.CrossRefGoogle Scholar
  11. Coleman, J. (1991). Social theory, social research and a theory of action. American Journal of Sociology, 91, 1309–1335.CrossRefGoogle Scholar
  12. Congdon, P. (1995). The impact of area context on long term illness and premature mortality: An illustration of multi-level analysis. Regional Studies, 29, 327–344.CrossRefGoogle Scholar
  13. Daly, M., Duncan, G., Kaplan, G., and Lynch, J. (1998). Macro to micro links in the relation between income inequality and mortality. Milbank Quarterly, 76, 315–339.CrossRefGoogle Scholar
  14. Diez Roux, A. V. (1998). Bringing context back into epidemiology variables and fallacies in multilevel analysis. American Journal of Public Ilealth, 88, 216–222.CrossRefGoogle Scholar
  15. Diez Roux, A. V. (1999). On genes, individuals, society, and epidemiology. American Journal of Epidemiology, 11, 1027–1032.Google Scholar
  16. Diez Roux, A. V., Nieto, F., Muntaner, C., Tyroler, H. A., Comstock, G. W. et al. (1997). Neighborhood environments and coronary heart disease: a multilevel analysis. American Journal of Epidemiology, 146, 48–63.Google Scholar
  17. Diez Roux, A. V., Nieto, F. J., Caulfield, L., Tyroler, H. A., Watson, R. A., and Szklo, M. (1999). Neighborhood differences in diet: the Atherosclerosis Risk in Communities (ARIC) Study. Journal of Epidemiology and Community Health, 53, 55–63.CrossRefGoogle Scholar
  18. Diez Roux, A. V. (2000). Multilevel analysis in public health research. Annual Review of Public Health, 21, 171–92.CrossRefGoogle Scholar
  19. Diez Roux, A. V., Link, B. G, and Northridge, M. E. (2000). A multilevel analysis of income inequa-lity and cardiovascular disease risk factors. Social Science in Medicine. 50, 673–87.CrossRefGoogle Scholar
  20. Diez Roux, A. V., Schwartz, S., and Susser, E. (2002). Ecologic studies and ecologic variables in pu-blic health research. In The Oxford Textbook of Public Health (pp. 493–509 ). London: Oxford University Press.Google Scholar
  21. DiPrete, T. A., and Forristal, J. D. (1994). Multilevel models: methods and substance. Annual Review of Sociology, 20, 331–357.CrossRefGoogle Scholar
  22. DiPrete, T. A., and Grusky, D. (1990). The multilevel analysis of trends with repeated cross-sectional data. Sociological Methodology, 20, 337–368.CrossRefGoogle Scholar
  23. Duncan, C., Jones, K, and Moon, G. (1993). Do places matter? A multi-level analysis of regional va-riation in health-related behavior in Britain. Social Science and Medicine, 37, 725–733.CrossRefGoogle Scholar
  24. Duncan, C., Jones, K., and Moon, G. (1996). Health-related behaviour in context: a multilevel mo-delling approach. Social Science and Medicine, 42, 817–830.CrossRefGoogle Scholar
  25. Duncan, T., Duncan, S., Hops, H., and Alpert, A. (1997). Multilevel covariance structure analysis of intrafamilial substance abuse. Drug and Alcohol Dependence, 46, 167–180.CrossRefGoogle Scholar
  26. Duncan, C., Jones, K., and Moon, G. (1998). Context, composition, and heterogeneity: using multilevel models in health research. Social Science and Medicine, 46, 97–117.CrossRefGoogle Scholar
  27. Duncan, C., Jones, K., and Moon, G. (1999). Smoking and deprivation: are there neighbourhood effects? Social Science and Medicine, 48, 497–505.CrossRefGoogle Scholar
  28. Ecob, R. (1996). A multilevel modelling approach to examining the effects of area of residence on health. Journal of the Royal Statistical Society (A), 159, 61–75.CrossRefGoogle Scholar
  29. Entwisle, B. (1991). Micro-macro theoretical linkages in social demography: a commentary. In J Huber (Ed.), Macro-micro linkages in sociology (pp. 280–286 ). Newbury Park, CA: Sage.Google Scholar
  30. Entwisle, B., Mason, W., Hermalin, H. (1986). The multilevel dependence of contraceptive use onsocioeconomic development and family planning program strength. Demography, 23, 199–216.CrossRefGoogle Scholar
  31. Fiscella, K., and Franks, P. (1997). Poverty or income inequality as predictor or mortality: a longitu-dinal cohort study. British Medical Journal, 314, 1724–1728.CrossRefGoogle Scholar
  32. Forster, J., Murray, D., Wolfson, M., Blaine, T., Wagenaar, A., and Hennrikus, D. (1998). The effects of community policies to reduce youth access to tobacco. American Journal of Public Health. 88, 1193–1198.Google Scholar
  33. Gatsonis, C., Normand, S., Liu, C., and Morris, C. (1993). Geographic variation of procedure utilization: A hierarchical model approach. Medical Care, 31, YS54–YS59.Google Scholar
  34. Gibbons, R., Hedeker, D., Waternaux, C., and Davis, J. (1988). Random regression models: a comprehensive approach to the analysis of longitudinal psychiatric data. Psychopharmacology Bulletin, 24, 438–443.Google Scholar
  35. Goldstein, H. (1994). Multilevel cross-classified models. Sociological Methods and Research, 22, 364–375.CrossRefGoogle Scholar
  36. Goldstein, H. (1995). Multilevel statistical models. New York: Halsted Press.Google Scholar
  37. Gould, M., and Jones, K. (1996). Analyzing perceived limiting long-term illness using U. K. Census microdata. Social Science and Medicine, 42, 857–869.CrossRefGoogle Scholar
  38. Greenland, S. (1992). Divergent biases in ecologic and individual-level studies. Statistics in Medicine, 11, 1209–1223.CrossRefGoogle Scholar
  39. Greenland, S., and Morgenstern, H. (1989). Ecological bias, confounding, and effect modification. International Journal of Epidemiology, 18, 269–274.CrossRefGoogle Scholar
  40. Greenland, S., and Robins, J. (1994). Ecologic studies-biases, misconceptions, and counter-examples. American Journal of Epidemiology, 139, 747–760.Google Scholar
  41. Halloran, M. E. (1998). Concepts of infectious disease epidemiology. In K. Rothman and S. Greenland (eds.), Modern Epidemiology (pp.). Philadelphia: Lippincott-Raven.Google Scholar
  42. Hart, C., Ecob, R., and Davey Smith G. (1997). People, places, and coronary heart disease risk factors: a multilevel analysis of the Scottish Heart Health Study archive. Social Science and Medicine, 45, 893–902.CrossRefGoogle Scholar
  43. Hedeker, D., Gibbons, R., Davis, J. (1991). Random regression models for multicenter clinical trials data. Psychopharmacology Bulletin, 27, 73–77.Google Scholar
  44. Hedeker, D., McMahon, S., Jason, L., and Salina, D. (1994). Analysis of clustered data in community psychology: with an example from a worksite smoking cessation project. American Journal of Community Psychology, 22, 595–615.CrossRefGoogle Scholar
  45. Hermalin, A. (1986). The multilevel approach: theory and concepts. The methodology for measuring the impact of family planning programs on fertility. In Population Studies Addendum Manual IX. 66 (pp. 15–31 ). New York: United Nations.Google Scholar
  46. Hox, J. P., de Leeuw, E. D., and Kreft, I. G. G. (1991). The effect of interviewer and respondent characteristics on the quality of survey data: a multilevel model. In P. P. Biemer, L. E. Lyberg, N. A. Mathiowetz, and S. Sudman (Eds.), Measurement errors in surveys (pp. 439–463 ). New York: John Wiley and Sons.Google Scholar
  47. Humphreys, K., and Carr-Hill, R. (1991). Area variations in health outcomes: Artefact or ecology. International Journal of Epidemiology, 20, 251–258.CrossRefGoogle Scholar
  48. Iversen, G. (1991). Contextual analysis. Newbury Park, CA: Sage.Google Scholar
  49. Jones, K., and Moon, G. (1991). Multilevel assessment of immunisation uptake as a performance measure in general practice. British Medical Journal, 303, 28–31.CrossRefGoogle Scholar
  50. Jones, K., and Duncan, C. (1995). Individuals and their ecologies: analysing the geography of chronic illness within a multilevel modelling framework. Health Place, 1, 27–40.CrossRefGoogle Scholar
  51. Jones, K., and Moon, G. (1991). Multilevel assessment of immunisation uptake as a performance measure in general practice. British Medical Journal, 303, 28–31.CrossRefGoogle Scholar
  52. Kaplan, G. A., Pamuk, E. R., Lynch, J. W., Cohen, R. D., and Balfour, J. L. (1996). Inequality in income and mortality in the United States: analysis of mortality and potential pathways. British Medical Journal, 312, 999–1003.CrossRefGoogle Scholar
  53. Kaufman, J., and Kaufman, S. (2001). Assessment of structured socioeconomic effects on health. F, pidemiology, 12, 157–167.CrossRefGoogle Scholar
  54. Kawachi, 1. (1999). Social capital and community effects on population and individual health. Annual Report. New York Academy of Sciences, 896, 120–130.CrossRefGoogle Scholar
  55. Kennedy, B. P., Kawachi, I., and Prothrow-Stith, D. (1996). Income distribution and mortality: cross-sectional ecological study of the Robin Hood index in the United States. British Medical Journal, 312, 1004–1007.CrossRefGoogle Scholar
  56. Kennedy, B. P., Kawachi, I., Glass, R., and Prothrow-Stith, D. (1998). Income distribution, socioeconomic status and self rated health in the United States: a multilevel analysis. British Medical Journal, 31, 917–921.CrossRefGoogle Scholar
  57. Kleinschmidt, I., Hills, M., and Elliott, P. (1995). Smoking behavior can be predicted by neighbo-Google Scholar
  58. rhood deprivation measures. Journal of Epidemiology and Community Health, 49,S72–S77. Koopman, J. S. (1996). Emerging objectives and methods in epidemiology. American Journal of Pu-blic Health, 86,630–632.Google Scholar
  59. Koopman, J. S., and Lynch, J. (1999). Individual causal models and population system models in epidemiology. American Journal of Public Health, 89, 1170–1174.CrossRefGoogle Scholar
  60. Koopman, J. S., Prevots, D. R., Vaca Marin, M. A., Dantes, H. G., Zarate Aquino, M. L., Longini, I. M., and Sepulveda J. (1991a). Determinants and predictors of dengue infection in Mexico. American Journal of Epidemiology, 133, 1 168–1178.Google Scholar
  61. Koopman, J. S., Longini, I. M., Jacquez, J. A., Simon, C. P., Ostrow, D. G., Martin, W. R., and Woodcock, D. M. (1991b). Assessing risk factors for transmisson of infection. American Journal of Epidemiology, 133, 1199–1209.Google Scholar
  62. Koopman, J. S., and Lynch J. (1999). Individual causal models and population system models in epidemiology. American Journal of Public Health, 1989, 1170–1174.CrossRefGoogle Scholar
  63. Kreft, I., and deLeeuw J. (1998). Introducing multilevel modeling. London: Sage.Google Scholar
  64. Krieger, N. (1994). Epidemiology and the web of causation. Has anyone seen the spider? Social Science and Medicine, 39, 887–903.CrossRefGoogle Scholar
  65. Krieger, N., Zierler, S. (1997). The need for epidemiologic theory. Epidemiology, 8, 212–214.Google Scholar
  66. Langford, L H. (1994). Using empirical Bayes estimates in the geographical analysis of disease risk. Area, 26, 142–149.Google Scholar
  67. Langford, I. H., and Bentham, G. (1996). Regional variations in mortality rates in England and Wales: An analysis using multilevel modelling. Social Science and Medicine, 42, 897–908.CrossRefGoogle Scholar
  68. Langford, I. H., Bentham, G., and McDonald, A. (1998). Multi-level modelling of geographically aggregated health data: A case study of malignant melanoma mortality and UV exposure in the european community. Statistics in Medicine, 17, 41–57.CrossRefGoogle Scholar
  69. Lazarsfeld, P. F., and Menzel, H. (1971). On the relation between individual and collective properties. In A. Etzioni (ed.), A sociological reader on complex organizations (pp. 499–516 ). New York: Holt, Rinehart, and Winston Inc.Google Scholar
  70. LeClere, F. B., and Soobader, M. J. (2000). The effect of income inequality on the health of selected demographic groups. American Journal of Public Health, 90, 1892–1897.Google Scholar
  71. Leung, K., Elashoff, R., Rees, K., Hasan, M., and Legorreta, A. (1998). Hospital-and patient-related characteristics determining maternity length of stay: A hierarchical linear model approach. American Journal of Public Health, 88, 377–81.CrossRefGoogle Scholar
  72. Levins, R, and Lewontin, R. (1985). The Dialectical Biologist. Boston: Harvard University Press.Google Scholar
  73. Leyland, A., and Boddy, F. (1998). League tables and acute myocardial infarction. Lancet, 351, 555558.Google Scholar
  74. Lilienfeld, D., and Stolley, P. (1994). Foundations of epidemiology. Third Edition. New York: Oxford University Press.Google Scholar
  75. Loomis, D., and Wing, S. (1990). Is molecular epidemiology a germ theory for the end of the twentieth century? International Journal of Epidemiology, 19, 1–3.CrossRefGoogle Scholar
  76. Mac Mahon, B., Pugh, T. F., and Ipsen, J. (1960). Epidemiologie Methods. Boston: Little Brown.Google Scholar
  77. Malurstrom, M., Sundquist, J., and Johansson, S. (1999). Neighborhood environment and self-repor-ted health status: a multilevel analysis. American Journal of Public Health, 89, 1181–1189.CrossRefGoogle Scholar
  78. Manor, O., and Kark, J. (1996). A comparative study of four methods for analyzing repeated measures data. Statistics in Medicine, 15, 1143–1159.Google Scholar
  79. Mason, W. (1991). Problems in quantitative comparative analysis: ugly ducklings are to swans as ugly scatter plots are to…? In J. Huber (Ed.), Macro-micro linkages in sociology (pp. 231–243 ). Newbury Park, CA: Sage.Google Scholar
  80. Matteson, D., Burr, J., and Marshall, J. (1998). Infant mortality: a multi-level analysis of individual and community risk factors. Social Science in Medicine, 47, 1841–1854.Google Scholar
  81. McMichael, A. J. (1999). Prisoners of the proximate: Loosening the constraints on epidemiology in an age of change. American Journal of Epidemiology, 149, 887–97.CrossRefGoogle Scholar
  82. Morgenstern, H. (1982). Uses of ecologic analysis in epidemiologic research. American Journal of Public Health, 72, 1336–1344.CrossRefGoogle Scholar
  83. Morgenstern, H. (1995). Ecologic studies in epidemiology: concepts, principles, and methods. Annual Review of Public Health, 16, 61–81.CrossRefGoogle Scholar
  84. O’Campo, P., Xue, X., Wang, M., and Caughy M. (1997). Neighborhood risk factors for low birthwei- ght in Baltimore: a multilevel analysis. American Journal of Public Health, 87, 1113–1118.CrossRefGoogle Scholar
  85. Oppenheimer, K., and Mason, K.O. (1991). Multilevel analysis in the study of social institutions and demographic change. In J. Huber (ed.), Macro-micro linkages in sociology (pp. 223–230 ). Newbury Park, CA: SageGoogle Scholar
  86. Pearce, N. (1996). Traditional epidemiology, modern epidemiology and public health. American Journal of Public Health, 86, 678–683.CrossRefGoogle Scholar
  87. Philippe, P., and Mansi, O. (1998). Nonlinearity in the epidemiology of complex health and disease processes. Theoretical Medicine and Bioethics, 19, 591–607.Google Scholar
  88. Piantadosi, S., Byar, D. P., and Green, S. B. (1988). The ecological fallacy. American Journal of Epidemiology, 127, 893–903.Google Scholar
  89. Pickett, K. E., and Pearl, M. (2001). Multilevel analyses of neighbourhood socioeconomic context and health outcomes: a critical review. Journal of Epidemiology and Community Health, 55, I11–122.Google Scholar
  90. Poole, C., and Rothman, K. J. (1998). Our conscientious objection to the epidemiology wars. Journal of Epidemiology and Community Health, 52, 613–614.CrossRefGoogle Scholar
  91. Rice, N., and Leyland, A. (1996). Multilevel models: applications to health data. Journal of Health Services Research and Policy, 1, 154–64.Google Scholar
  92. Riley, M. W. (1963). Special problems of sociological analysis. In R. K. Merton (Ed.), Sociological Research 1: A case approach (pp. 700–725 ). New York: Harcourt, Brace, and World Inc.Google Scholar
  93. Robert, S. (1999). Socioeconomic position and health: the independent contribution of community socioeconomic context. Annual Review of Sociology, 25, 489–516.CrossRefGoogle Scholar
  94. Robins, J. (1989). The control of confounding by intermediate variables. Statistics in Medicine, 8, 679–701.CrossRefGoogle Scholar
  95. Robins, J. M., Blevins, D., Ritter, G., and Wulfsohn, M. (1992). G-estimation of the effect of prophylaxis therapy for Pneumocystis carinii pneumonia on the survival of AIDS patients. Epidemiology, 3, 319–36.CrossRefGoogle Scholar
  96. Robins, J. M., Hernan, M. A., and Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, I I, 550–60.Google Scholar
  97. Robins, J. M., and Greenland, S. (1992). Identifiability and exchangeability for direct and indirect effects. Epidemiology, 3, 143–55.CrossRefGoogle Scholar
  98. Rose, G. (1985). Sick individuals and sick populations. International Journal of Epidemiology, 14, 32–38.CrossRefGoogle Scholar
  99. Rothman, K. J., and Greenland, S. (1998). Causation and causal inference. In K. J. Rothman, and S. Greenland (Eds.), Modern Epidemiology (pp. 7–28 ). Second Edition. Philadelphia: Lippincott-Raven.Google Scholar
  100. Rountree, P. W., and Clayton, R. (1999). A contextual model of adolescent alcohol use across the rural-urban continuum. Substance Use and Misuse, 34, 495–519.CrossRefGoogle Scholar
  101. Rutter, C., and Elashoff, R. (1994). Analysis of longitudinal data: random coefficient regression modelling. Statistics in Medicine, 13, 1211–1231.CrossRefGoogle Scholar
  102. Scheuch, E. K. (1969). Social context and individual behavior. In M. Dogan, and S. Rokkam (Eds.), Social Ecology (pp. 133–155 ). Boston: The MIT Press.Google Scholar
  103. Schwartz, S. (1994). The fallacy of the ecological fallacy: the potential misuse of a concept and its consequences. American Journal of Public Health, 84, 819–824.CrossRefGoogle Scholar
  104. Schwartz, S., and Carpenter, K. (1999). The right answer for the wrong question: Consequences of type 111 error for public health research. American Journal of Public Health, 89, 1175–1180.CrossRefGoogle Scholar
  105. Schwartz, S., Susser, E., and Susser, M. (1999). A future for epidemiology? Annual Review of Public Health, 20, 15–33Google Scholar
  106. Shouts, S., Congdon, P., and Curtis, S. (1996). Modelling inequality in reported long term illness in the UK: combining individual and area characteristics. Journal of Epidemiology and Community Health, 50, 366–376CrossRefGoogle Scholar
  107. Sixma, H. J., Spreeuwenberg, P. M., and Pasch, M. (1998). Patient satisfaction with the general practitioner: a two-level analysis. Medical Care, 36, 212–229.CrossRefGoogle Scholar
  108. Snijders, T. A., and Bosker, R. J. (1994). Modeled variance in two-level models. Sociological Methods and Research, 22, 342–363CrossRefGoogle Scholar
  109. Snijders, T. A., and Bosker, R. J. (1999). Multilevel analysis: an introduction to basic and advanced multilevel modeling. London: Sage.Google Scholar
  110. Soderfeldt, B., Soderfeldt, M., Jones, K., et al. (1997). Does Organization Matter? A multilevel analysis of the demand-control model applied to human services. Social Science and Medicine, 44, 527–534.CrossRefGoogle Scholar
  111. Sundquist, J., Malmstrom, M., and Johansson, S. (1999). Cardiovascular risk factors and the neighborhood environment: A multilevel analysis. International Journal of Epidemiology, 28, 84 1845.Google Scholar
  112. Susser, M. (1994a). The logic in ecological: I. The logic of analysis. American Journal of Public Health. 84, 825–829.CrossRefGoogle Scholar
  113. Susser, M. (1 994b). The logic in ecological: Ii. The logic of design. American Journal of Public Health, 84, 830–835.Google Scholar
  114. Susser, M., and Susser, E. (1996a). Choosing a future for epidemiology I: Eras and paradigms. American Journal of Public Health, 86, 668–673.Google Scholar
  115. Susser, M., and Susser, E. (1996b). Choosing a future for epidemiology: IL From black box to Chi-nese boxes and eco-epidemiology. American Journal of Public Health, 86, 674–677.CrossRefGoogle Scholar
  116. Susser, M. (1998). Does risk factor epidemiology put epidemiology at risk? Peering into the future. Journal of E pidemiology and Community Health, 52, 608–611.CrossRefGoogle Scholar
  117. Szklo, M., and Nieto, F. J. (2000). Epidemiology: beyond the basics. Gaithersburg, MD: Aspen Publishers.Google Scholar
  118. Taubes, G. (1995). Epidemiology faces its limits. Science, 269, 164–169.CrossRefGoogle Scholar
  119. Tesh, S. N. (1990). Hidden Arguments. Political ideology and disease prevention policy. New York: Rutgers University Press.Google Scholar
  120. Thomas, N., Lonford, N., and Rolph, J. (1994). Empirical Bayes methods for estimating hospital-specific morality rates. Statistics in Medicine, 13, 889–903CrossRefGoogle Scholar
  121. Valkonen, T. (1969). Individual and structural effects in ecological research. In M. Dogan, and S. Rokkam (Ed.), Social Ecology (pp. 53–68 ). Boston: The MIT Press.Google Scholar
  122. Van Den Eeden, P., and Huttner, H. J. (1982). Multi-level research. Current Sociology, 30, 1–178.CrossRefGoogle Scholar
  123. Vandenbroucke, J. P. (1990). Epidemiology in transition: a historical hypothesis. Epidemiology, I, 164–167.Google Scholar
  124. Von Korff, M., Koepsell, T., Curry, S., and Diehr, P. (1992). Multi-level research in epidemiologic research on health behaviors and outcomes. American Journal of Epidemiology, /35, 1077–1082.Google Scholar
  125. Wang, J., Siegal, H. A., Falck, R. S., and Carlson, R. G. (1998). Needle transfer among injection drugusers: a multilevel analysis. American Journal of Drug and Alcohol Abuse, 24, 225–237.CrossRefGoogle Scholar
  126. Ware, J. (1985). Linear models for the analysis of longitudinal studies. The American Statistician, 39, 95–101CrossRefGoogle Scholar
  127. Witte, J. S., Greenland, S., Haile, R. W., and Bird, C. L. (1994). Hierarchical regression analysis ap-plied to a study of multiple dietary exposures and breast cancer. Epidemiology, 5, 612–621.CrossRefGoogle Scholar
  128. Wong, G., and Mason, W. (1985). The hierarchical logistic regression model for multilevel analysis. ‚Journal of the American Statistical Association, 80, 513–524.CrossRefGoogle Scholar
  129. Wong, G.,and Mason, W. (1991). Contextually specific effects and other generalizations of the hierarchical linear model for comparative analysis. Journal of the American Statistical Association, 86, 487–503.CrossRefGoogle Scholar
  130. Yen, I., and Kaplan, G. (1999). Neighborhood social environment and risk of death: multilevel evi- dence from the Alameda County study. American Journal of Epidemiology, 149, 898–907.CrossRefGoogle Scholar

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