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題名 試題偏難或偏易情況下之Mokken尺度量表問項篩選分析
A Study on Extreme Range of Item Difficulty Parameters for Item Selection in Mokken Scale Analysis作者 高千涵
Gao,Chien Han貢獻者 江振東
高千涵
Gao,Chien Han關鍵詞 自動化問項篩選
AISP日期 2012 上傳時間 11-Jul-2013 16:36:32 (UTC+8) 摘要 在一組問項有次序性(強弱性)的問卷中，若其議題涉隱私或過於敏感，則容易出現給予正向回答的比例偏低的情況；反之若是高度認同的議題，則容易造成給予正向回答的比例都偏高的情形，這兩種情況都屬於問項回答太過一致的問卷，若直接利用這種問卷來分析或許無法取得有用的資訊。 本研究主旨在於探討利用自動化問項篩選工具(AISP)，針對這種問項太過一致的問卷來篩選出符合Mokken尺度量表的問項時所可能衍生的問題。由於利用自動化問項篩選工具的一個缺失點為，篩選出的量表不一定是最好的量表，其中可能包含不適當的問項。因此我們將透過「違反篩選條件的問項個數和比例」的計算，來針對問項難易分佈偏左(正向回答比例低)、偏右(正向回答比例高)的問卷和問項分佈對稱的情況來進行探討。 模擬結果顯示，當問項難易分佈偏左或偏右時，皆會造成違反篩選條件的問項個數和比例逐漸遞增。此外，若問項設計的鑑別度太低，自動化問項篩選工具幾乎無法有效的篩選出適當的問項。
In a questionnaire survey, if the items are related to politics or personal privacy, respondents tend to give a negative response to the items. On the other hand, if the items are highly recognized, most of them answer positively to the items. These two are examples that the responses to the items are too consistent. It is apparent that useful information is hard to come by through the use of such kind of survey data. The automated item selection procedure (AISP) is a tool to select items that form a Mokken scale from questionnaire. However, the items selected by AISP is not necessarily the optimal choice. Therefore, the aim in the study was to investigate whether extreme response items would create more problems when using AISP. Number of items which violates the selection rules was based to judge the possible impact. The simulation results showed that number of violations increased when the items were too consistent. Furthermore, items with low discrimination almost led to ineffective items selection.參考文獻 章英華、傅仰止(2006)。台灣社會變遷基本調查五期一次、六期一次-綜合問卷 組(C00153_1)【原 始數據】。取自中央研究院人文社會科學研究中心調查研究專題中心學術調查崖舊資料庫 http://srda.sinica.edu.tw。dio:10.6141/TW-SRDA-C00153_1-1。Birnbaum, A.(1968). Some latent trait models and their use in inferring an examinee`s ability. In F. M. Lord & M. R. Novick , Statistical theories of mental test scores (pp. 397-472). Reading, MA: Addison-Wesley.Bouwmeester, S. & Sijtsma, K. (2006). Constructing a transitive reasoning test for 6 - to 13 year old children. European Journal of Psychological Assessment, 22, 225-232. Gillespie, M. W., Tanvergert, E. & Kingma, J (1987, 1988). Abortion Attitudes: Effects of item Order and dimensionality. Perceptual and Motor Skills (Volume 74, Issue , pp. 627-642.)Grayson, D. A. (1988). Two-group classification in latent trait theory: Scores with monotone likelihood ratio. Psychometrika, 53, 383-392. Guttman, L. (1950). The utility of scalogram analysis. In S. A. Stouffer, L. Guttman, E. A. Suchman, P. F. Lazarsfeld, S. A. Star, & J. A. Clausen(Eds.), Measurement and prediction . Studies in Social Psychology in World War Ⅱ (Vol. 4, pp. 122-171). New York, NY: Wiley.Hemker, B. T., Sijtsma, K., Molenaar, I. W. & Junker, B. W. (1996), Polytomous IRT models and monotone likelihood ratio of the total score. Psychometrika, 61, 679-693. Loevinger, J. (1948), The technique of homogeneous tests compared with some aspects of "scale analysis" and factor analysis. Psychological Bulletin, 45, 507-530. Meijer, R. R. & Baneke J. J. (2005). Analyzing psychopathology items: A case for nonparametric item response theory modeling. Psychological Methods, 9, 354-368.Mokken, R. J. (1971). A theory and procedure of scale analysis. With application in political research. Berlin, Germany: De Gruyter (Mouton)Mokken, R. J., Lewis, C. & Sijtsma, K. (1986). Rejoinder to "The Mokken scale: A critical discussion. " Applied Psychological Measurement,10, 279-285.Molenaar, I. W. (1991). A weighted Loevinger H-coefficient extending Mokken scaling to multicategory items. Kwantitatieve Methoden, 12(37), 97-117.Molenaar, I. W. & Sijtsma, K. (2000). User`s manual MSP5 for Windows. Groningen: iecProGAMMA.Sijtsma, K. & Junker, B. W. (1996) A survey of theory and methods of invariant item ordering. British Journal of Mathematical and Statistical Psychology, 49, 79-105. 描述 碩士
國立政治大學
統計研究所
100354011
101資料來源 http://thesis.lib.nccu.edu.tw/record/#G0100354011 資料類型 thesis dc.contributor.advisor 江振東 zh_TW dc.contributor.author (Authors) 高千涵 zh_TW dc.contributor.author (Authors) Gao,Chien Han en_US dc.creator (作者) 高千涵 zh_TW dc.creator (作者) Gao,Chien Han en_US dc.date (日期) 2012 en_US dc.date.accessioned 11-Jul-2013 16:36:32 (UTC+8) - dc.date.available 11-Jul-2013 16:36:32 (UTC+8) - dc.date.issued (上傳時間) 11-Jul-2013 16:36:32 (UTC+8) - dc.identifier (Other Identifiers) G0100354011 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/58783 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 統計研究所 zh_TW dc.description (描述) 100354011 zh_TW dc.description (描述) 101 zh_TW dc.description.abstract (摘要) 在一組問項有次序性(強弱性)的問卷中，若其議題涉隱私或過於敏感，則容易出現給予正向回答的比例偏低的情況；反之若是高度認同的議題，則容易造成給予正向回答的比例都偏高的情形，這兩種情況都屬於問項回答太過一致的問卷，若直接利用這種問卷來分析或許無法取得有用的資訊。 本研究主旨在於探討利用自動化問項篩選工具(AISP)，針對這種問項太過一致的問卷來篩選出符合Mokken尺度量表的問項時所可能衍生的問題。由於利用自動化問項篩選工具的一個缺失點為，篩選出的量表不一定是最好的量表，其中可能包含不適當的問項。因此我們將透過「違反篩選條件的問項個數和比例」的計算，來針對問項難易分佈偏左(正向回答比例低)、偏右(正向回答比例高)的問卷和問項分佈對稱的情況來進行探討。 模擬結果顯示，當問項難易分佈偏左或偏右時，皆會造成違反篩選條件的問項個數和比例逐漸遞增。此外，若問項設計的鑑別度太低，自動化問項篩選工具幾乎無法有效的篩選出適當的問項。 zh_TW dc.description.abstract (摘要) In a questionnaire survey, if the items are related to politics or personal privacy, respondents tend to give a negative response to the items. On the other hand, if the items are highly recognized, most of them answer positively to the items. These two are examples that the responses to the items are too consistent. It is apparent that useful information is hard to come by through the use of such kind of survey data. The automated item selection procedure (AISP) is a tool to select items that form a Mokken scale from questionnaire. However, the items selected by AISP is not necessarily the optimal choice. Therefore, the aim in the study was to investigate whether extreme response items would create more problems when using AISP. Number of items which violates the selection rules was based to judge the possible impact. The simulation results showed that number of violations increased when the items were too consistent. Furthermore, items with low discrimination almost led to ineffective items selection. en_US dc.description.tableofcontents 頁數摘要 ---------- 5Abstract ---------- 6第一章 緒論 ---------- 7第一節 研究背景 ----------- 7第二節 動機 ---------- 7第二章 文獻探討 ----------- 10第一節 Guttmam量表 ---------- 10第二節 Mokken 量表 ---------- 12第三節 Mokken 問項篩選步驟 ---------- 22第三章 資料模擬分析 ---------- 25第一節 資料生成模型 ---------- 26第二節 模擬變數 ---------- 27第三節 模擬結果 ---------- 30第四章 實證分析 ---------- 40第一節 分析過程 ---------- 42第二節 資料推論 ---------- 45第三節 結論 ---------- 47第五章 結論與建議 ---------- 48第一節 分析結論 ---------- 48第二節 建議與改進 ---------- 49參考文獻 ---------- 50附錄 ---------- 51 zh_TW dc.format.extent 1143357 bytes - dc.format.mimetype application/pdf - dc.language.iso en_US - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0100354011 en_US dc.subject (關鍵詞) 自動化問項篩選 zh_TW dc.subject (關鍵詞) AISP en_US dc.title (題名) 試題偏難或偏易情況下之Mokken尺度量表問項篩選分析 zh_TW dc.title (題名) A Study on Extreme Range of Item Difficulty Parameters for Item Selection in Mokken Scale Analysis en_US dc.type (資料類型) thesis en dc.relation.reference (參考文獻) 章英華、傅仰止(2006)。台灣社會變遷基本調查五期一次、六期一次-綜合問卷 組(C00153_1)【原 始數據】。取自中央研究院人文社會科學研究中心調查研究專題中心學術調查崖舊資料庫 http://srda.sinica.edu.tw。dio:10.6141/TW-SRDA-C00153_1-1。Birnbaum, A.(1968). Some latent trait models and their use in inferring an examinee`s ability. In F. M. Lord & M. R. Novick , Statistical theories of mental test scores (pp. 397-472). Reading, MA: Addison-Wesley.Bouwmeester, S. & Sijtsma, K. (2006). Constructing a transitive reasoning test for 6 - to 13 year old children. European Journal of Psychological Assessment, 22, 225-232. Gillespie, M. W., Tanvergert, E. & Kingma, J (1987, 1988). Abortion Attitudes: Effects of item Order and dimensionality. Perceptual and Motor Skills (Volume 74, Issue , pp. 627-642.)Grayson, D. A. (1988). Two-group classification in latent trait theory: Scores with monotone likelihood ratio. Psychometrika, 53, 383-392. Guttman, L. (1950). The utility of scalogram analysis. In S. A. Stouffer, L. Guttman, E. A. Suchman, P. F. Lazarsfeld, S. A. Star, & J. A. Clausen(Eds.), Measurement and prediction . Studies in Social Psychology in World War Ⅱ (Vol. 4, pp. 122-171). New York, NY: Wiley.Hemker, B. T., Sijtsma, K., Molenaar, I. W. & Junker, B. W. (1996), Polytomous IRT models and monotone likelihood ratio of the total score. Psychometrika, 61, 679-693. Loevinger, J. (1948), The technique of homogeneous tests compared with some aspects of "scale analysis" and factor analysis. Psychological Bulletin, 45, 507-530. Meijer, R. R. & Baneke J. J. (2005). Analyzing psychopathology items: A case for nonparametric item response theory modeling. Psychological Methods, 9, 354-368.Mokken, R. J. (1971). A theory and procedure of scale analysis. With application in political research. Berlin, Germany: De Gruyter (Mouton)Mokken, R. J., Lewis, C. & Sijtsma, K. (1986). Rejoinder to "The Mokken scale: A critical discussion. " Applied Psychological Measurement,10, 279-285.Molenaar, I. W. (1991). A weighted Loevinger H-coefficient extending Mokken scaling to multicategory items. Kwantitatieve Methoden, 12(37), 97-117.Molenaar, I. W. & Sijtsma, K. (2000). User`s manual MSP5 for Windows. Groningen: iecProGAMMA.Sijtsma, K. & Junker, B. W. (1996) A survey of theory and methods of invariant item ordering. British Journal of Mathematical and Statistical Psychology, 49, 79-105. zh_TW
