e propose a comprehensive statistical model for analyzing multiparty, district-level elections. This model, which provides a tool for comparative politics research analogous to that which regression analysis provides in the American two-party context, can be used to explain or predict how geographic distributions of electoral results depend upon economic conditions, neighborhood ethnic compositions, campaign spending, and other features of the election campaign or aggregate areas. We also provide new graphical representations for data exploration, model evaluation, and substantive interpretation. We illustrate the use of this model by attempting to resolve a controversy over the size of and trend in the electoral advantage of incumbency in Britain. Contraiy to previous analyses, all based on measures now known to be biased, we demonstrate that the advantage is small but meaningfkl, varies substantially across the parties, and is not growing. Finally, we show how to estimate the party from which each party's advantage is predominantly drawn. w e propose the first internally consistent statistical model for analyzing multiparty, districtlevel aggregate election data. Our model can

Although integrating multiple levels of data into an analysis can often yield better inferences about the phenomenon under study, traditional methodologies used to combine multiple levels of data are problematic. In this paper, we discuss several methodologies under the rubric of multilevel analysis. Multilevel methods, we argue, provide researchers, particularly researchers using comparative data, substantial leverage in overcoming the typical problems associated with either ignoring multiple levels of data, or problems associated with combining lower-level and higher-level data (including overcoming implicit assumptions of fixed and constant effects). The paper discusses several variants of the multilevel model and provides an application of individual-level support for European integration using comparative political data from Western Europe.

Studies of contextual processes have always involved the possibility that if individuals aggregation into geographic units is not exogenous to their values on the dependent variable, then what appear to be contextual processes may be due solely to selection effects. We propose a method to test whether observed contextual effects are real or phantom. Individuals integration into their neighborhoods is measured by response latency on questions about the neighborhood; if contextual effects are based on what happens to people in their neighborhoods (i.e., the apparent effects are not due solely to selection effects), they should be more pronounced among those who are most integrated into their neighborhood. An empirical example illustrates the technique. We propose instrumentation by which electoral studies can test for true contextual effects; the availability of this test should encourage a greater emphasis in electoral studies on the search for contextual processes. 1 1.