| Summary: | 碩士 === 國立臺灣大學 === 政治學研究所 === 95 === In political behavior study, it is necessary and practical to infer individual behavior from aggregate data, which is called “ecological inference”, when individual-level data is not available. There is no determinate solution to the ecological inference problem so far, and the purpose of this paper is to clarify the applications of different ecological inference methods by comparing Ecological Regression, EI Model and BBH model which are applied in political science recently. Firstly, this paper makes a definition of the ecological inference problem with which the researchers are concerned in political science. Then it explores how these three models solve the ecological fallacy from statistical setting of models, provided that the ecological inference problem is in terms of a 2×2 cross-table. Finally, it evaluates their performance, among which BBH model is replaced by BNH model, in different data which are set up based on different dimension from survey data.
The results show that Ecological Regression, EI Model and BNH model are all biased in the situation when the variable in the margin is correlated with the parameter in the cell. In the situation when the standard deviation of parameter decreases, all of the three models are biased as well. The performance of the three models would not be affected with the changes in the mean of parameter. As for the sample size of the aggregate level, it seems not to affect the performance of any model. Overall, Ecological Regression is worse than EI Model and BNH model and the performance of EI Model and BNH model is in a tie. According to the results mentioned above, this paper discusses the limit of ecological inference methods when they are applied to analyze split-ticket voting.
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