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3 article(s) found.
Kuang-hui Chen, Assistant Professor, Department of Political Science, National Chung Cheng University.
A Preliminary Analysis on the Impact of Marriage on Self-Identity (in Chinese) Download
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Given that ethnicity and identity are the principal factors of political cleavage in Taiwan, this article explores the following questions: Whether individuals Taiwanese/Chinese identities are influenced by their spouses' ethnic background? If so, whose identities are more likely to be shaped by the intensive interactions between husbands and wives in a marriage? Answers to these questions are helpful to researchers who are interested in assessing the effect of political socialization experiences during adulthood. This article analyzes pooled survey data from Taiwan's Election and Democratization Study and the main findings are: (1) Ethnic background affects the respondents' self-identities. (2) Respondents tend to marry within their ethnic group. (3) Respondents' self-identities are influenced by their spouses' ethnic background. (4) Although females' self-identities are generally affected by their spouses' ethnicity, the best-educated females' self-identities are less likely to be changed after getting married. (5) The best-educated males' self-identities are more likely to be shifted after getting married than their female counterparts.
Kuang-hui Chen, PhD candidate, Department of Political Science, University of California, Santa Barbara.
Tsung-wei Liu, Associate Professor, Department of Political Science, National Chung-Cheng University
The Examination of Taiwan's Election and Democratization Study Panel Data (in Chinese) Download
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TEDS conducted two waves of panel studies. These panel data can be used to describe the dynamics of Taiwanese voters and to develop related causal models. However, because of panel attrition and panel effect, there may be problems of internal and external validity. The examination of panel data shows that the panel attrition did not occur randomly. There are significant differences between those respondents who participated in the second interview and those who dropped out in terms of demographic characteristics, but no significant difference was found in terms of political attitudes.

Both TEDS 2003 and 2004P were composed of panel samples and independent samples. Panel samples are those respondents who were interviewed in TEDS 2001 and independent samples are those respondents who were never interviewed before. To be interviewed by academic research staff is a special experience, so the respondents may be intrigued to access more political information and become more willing to participate in political activities afterwards. Therefore, the three TEDS surveys could be treated as a quasi-experiment. While the panel samples is treatment group, the independent samples is control group, and the interview is the treatment. This quasi-experiment demonstrates that panel effect did change the respondents' political attitudes and increase their political participation. To sum up the consequences of panel attrition and panel effect, TEDS panel data are biased. Researchers who analyze this data set should be attentive to the issue of biased sample and think about the methods to correct the bias before drawing conclusions or making inferences.
Tsung-wei Liu, Assistant Professor, Department of Political Science, National Chung-Cheng University.
Kuang-hui Chen, Ph.D. candidate, Department of Political Science, University of California, Santa Barbara.
Is Weighting a Routine or Something that Needs to be Justified? (in English) Download
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Survey research as a method of collecting sample data is supposed to produce sample statistics which can estimate the corresponding population parameters if the sampling design is appropriate. However, for reasons such as unit non-response, survey data is usually weighted by the institutes that collect the data or by researchers who analyse the data in order to correct or diminish the discrepancies between sample and population. Sample statistics based on weighted data are more representative of the population parameters than unweighted data in terms of some demographic characteristics.Therefore, to some extent, it seems legitimate to weight data and this manipulation has become a routine when dealing with survey data.

It is true that to weight data could be helpful, but this manipulation needs justifications. This paper therefore tries to argue that to weight data is no panacea and should not be taken for granted when considering the examples in Taiwan’s Election and Democratization Studies (TEDS) surveys. The first section discusses why weighted data is not necessarily representative of the population. As the TEDS surveys show, the turnout, the vote shares of parties, and marital status become more deviant from the population parameters after weighting the data.

If the focus is the relationships between variables, the correlations may be changed by weighting the data in bivariate or multivariate analysis. However, it is not clear whether we manufacture relationships which do not exist or if weighting the data actually helps us approximate the relationships that already exist in the population. Besides, it should be noted that to weight data set as a whole only deals with the problem of unit non-response, but does not solve the problem of item non-response.

The third section discusses why most efforts should be devoted to examining and improving questionnaires, sampling designs, and interviewerm straining and supervision, instead of simply appealing to post-weighting. If everything necessary has been tried, weighting data may be the last resort to improve the estimates. But the justifications for the selection of auxiliary variables and the methods of calculating weight factors should be provided rather than doing it without any explicit considerations. It is also important to consider whether the consequence of weighting is positive or negative.