Response: The value of a historically informed multilevel analysis of Robinson's data

Our story begins where Robinson's classic study ended.1 Could a study of relationship between two variables measured only at the individual-level—emblematic of most epidemiologic and social science research when individual data are available—lead to an impoverished description of the relationship? Using the same data on illiteracy and race that Robinson employed and supplementing it with relevant ecologic data that would have been available at that time, we showed that, in this particular case, studying solely the ‘behavior of individuals’, while ignoring their historical and ecological state context, was both limiting and misleading.2 The comments of the two discussants,3,4 whom we thank for their efforts, underscore the importance of a multilevel approach to scientific research. Neither of their commentaries, importantly, alters the central tenets and conclusions of our study and instead serves only to bolster them. Firebaugh reiterates the importance of a multilevel conceptual and analytical approach and concurs with our empirical observations and interpretations. His insightful and illustrative example of race and voting behaviour makes the crucial distinction between, and shows the simultaneous importance of, the influence of individual race and racial context on individual voting behaviour. Oakes too seems to broadly agree with our overall approach and conclusions. Notably, his reanalysis of our research questions with additional individual-level socio-economic variables led to the same finding demonstrating the robust nature of the empirical association we report. However, Oakes’ lengthy, and occasionally tangential, comment includes problematic statements, some of which misrepresent our study, while others are factually inaccurate. Statements necessitating correction include (i) attribution of motive; (ii) bibliometric searches; (iii) methodological individualism as the basis of multilevel analysis; (iv) the historical realities and impact of Jim Crow; (v) technical and conceptual aspects of multilevel modelling; and (vi) relationships between theory, study design, data analysis and causal inference.