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Merlo, J., Chaix, B., Ohlsson, H., Beckman, A., Johnell, K., Hjerpe, P., Rastam, L. and Larsen, K. (2006) A Brief Conceptual Tutorial of Multilevel Analysis in Social Epidemiology: Using Measures of Clustering in Multilevel Logistic Regression to Investigate Contextual Phenomena. Journal of Epidemiology and Community Health, 60, 290-297.
http://dx.doi.org/10.1136/jech.2004.029454

has been cited by the following article:

• TITLE: Statistical Significance of Geographic Heterogeneity Measures in Spatial Epidemiologic Studies

  AUTHORS: Min Lian

  KEYWORDS: Spatial Epidemiology, Heterogeneity, Statistical Significance, 95% Confidence Interval, 95% Credible Interval

  JOURNAL NAME: Open Journal of Statistics, Vol.5 No.1, February 6, 2015

  ABSTRACT: Assessing geographic variations in health events is one of the major tasks in spatial epidemiologic studies. Geographic variation in a health event can be estimated using the neighborhood-level variance that is derived from a generalized mixed linear model or a Bayesian spatial hierarchical model. Two novel heterogeneity measures, including median odds ratio and interquartile odds ratio, have been developed to quantify the magnitude of geographic variations and facilitate the data interpretation. However, the statistical significance of geographic heterogeneity measures was inaccurately estimated in previous epidemiologic studies that reported two-sided 95% confidence intervals based on standard error of the variance or 95% credible intervals with a range from 2.5th to 97.5th percentiles of the Bayesian posterior distribution. Given the mathematical algorithms of heterogeneity measures, the statistical significance of geographic variation should be evaluated using a one-tailed P value. Therefore, previous studies using two-tailed 95% confidence intervals based on a standard error of the variance may have underestimated the geographic variation in events of their interest and those using 95% Bayesian credible intervals may need to re-evaluate the geographic variation of their study outcomes.