以最小限制的離散型因素分析模型檢定多群組間的作答風格差異

• Main Authors: Lin, Jyong-Yi, 林炯伊
• Other Authors: 蔡蓉青
• Format: Others
• Language: zh-TW
• Published: 2016
• Online Access: http://ndltd.ncl.edu.tw/handle/17209190491129057033

碩士 === 國立臺灣師範大學 === 數學系 === 104 === The purpose of this study is to develop a test for detecting the difference in response styles between groups under the multiple-group categorical confirmatory factor analysis model. In Study 1, the factors of impact of latent attitude, sample size, the number of questionnaire questions, and the type of minimum free-baseline (MFB) setting were manipulated and their effects on the empirical Type I error and power of the proposed test in detecting different types of response styles investigated. The results indicate that the greater the sample size or the larger degree of response styles, the greater the degree of compliance of thresholds’ characteristics and the power of the test. As for the number of questionnaire questions had no impact with type I & II error. In Study 2, we analyzed the Likert scale data of Second Information Technology in Education Study 1998. In particular, six countries were chosen and examined for the presence of various response styles in their attitude towards the role of computer and other information and communication technologies. We found significant differences in response styles between 11 pairs of countries, among which 6 pairs showing the acquiescent and disacquiescent response styles simultaneously, such as Lithuania in comparison to Norway, France, and HongKong. The results implied that Lithuania was not inclined to midpoint response style with respect to the other three countries. Based on our findings, some recommendations are given as follows: In the analysis of Likert scale, one can first start with a variety of MFB models to check whether there exists any response style between groups, if not, we can anchor one item as the common method to increase power. If so, we select the appropriate MFB method for the different types of response style. For example, while testing for the extreme response style between the two groups, we could choose to anchor the threshold of the middle category.