1. NCCU Academic Hub
  2. 社會科學學院
  3. 政治學系
  4. 學位論文
Please use this identifier to cite or link to this item: https://ah.lib.nccu.edu.tw/handle/140.119/34493
DC FieldValueLanguage
dc.contributor.advisor黃旻華zh_TW
dc.contributor.author呂宜勵zh_TW
dc.creator呂宜勵zh_TW
dc.date2006en_US
dc.date.accessioned2009-09-19T07:29:00Z-
dc.date.available2009-09-19T07:29:00Z-
dc.date.issued2009-09-19T07:29:00Z-
dc.identifierG0093252005en_US
dc.identifier.urihttps://nccur.lib.nccu.edu.tw/handle/140.119/34493-
dc.description碩士zh_TW
dc.description國立政治大學zh_TW
dc.description政治研究所zh_TW
dc.description93252005zh_TW
dc.description95zh_TW
dc.description.abstract政治學者近年來已將多層線性模型當作研究政治文化的重要工具，不但應用在既有的資料庫分析上，同時也希望在資料蒐集過程中將所需要的資料特性納入抽樣設計裏，以期能克服目前此法在應用上所面臨的問題。在眾多問題中，最重要的莫過於是「總樣本數一定下個體和總體層次樣本數組合如何影響推論可靠性的問題」，學界對此過往是採取「30/30原則」，也就是個體和總體層次的樣本數都至少要在30個以上推論才會比較穩定，但近來許多研究顯示，如果將個體層次的樣本數縮減到15個而極大化總體層次樣本數，所得出的推論會比「30/30原則」來得更穩定，因此許多學者紛紛倡議應採用新發現而捨棄「30/30原則」。本文針對這樣的提議，利用教育學及政治學二領域資料，從模型意含的討論，進而使用模擬方法來測試這樣的提議是否站得住腳。 \n\n本文發現「極大化總體層次樣本數」原則並不能當作普遍認知，因為過往的所有文獻皆對單一母體資料進行剖析，尚未察覺母體資料型態影響參數表現的可能性，然而，本研究變化不同資料特性進行模擬結果顯示，母體資料結構確實會造成不同的參數表現，以致最適樣本組合也跟著不同。另外，我們觀察到固定效果和隨機效果的最適樣本配置偏重於不同層次的樣本數目，固定參數、固定效果以總體層次為主，但隨機參數、隨機效果、迴歸參數等卻不能忽視個體層次樣本個數，所以研究者都應該認真思考其在意的參數為何，才能針對所關切的現象本身設計出最適樣本配置，而做出實質且有效的討論。zh_TW
dc.description.tableofcontents第一章 導論...............................................1\n第一節 研究動機與目的......................................1\n第二節 複層次迴歸模型的應用.................................4\n第三節 多層線性模型的數學基礎...............................8\n第四節 文獻檢閱...........................................16\n第五節 章節安排...........................................21\n第二章 研究設計...........................................23\n第一節 研究方法與研究架構..................................23\n第二節 資料來源與模型設定..................................27\n第三節 研究限制...........................................30\n第三章 教育學調查的模擬結果................................37\n第一節 固定參數的表現.....................................40\n第二節 隨機效果的表現.....................................51\n第三節 迴歸參數的表現.....................................60\n第四節 小結..............................................63\n第四章 世界價值調查的模擬結果..............................65\n第一節 固定效果的表現.....................................67\n第二節 隨機效果的表現.....................................71\n第三節 迴歸參數的表現.....................................75\n第四節 小結..............................................76\n第五章 結論與展望.........................................77\n第一節 研究發現...........................................77\n第二節 對政治學研究的意義..................................79\n第三節 未來研究的方向.....................................81\n參考書目...................................................83\n一.中文部份................................................83\n二.英文部份...............................................83zh_TW
dc.format.extent44689 bytes-
dc.format.extent83473 bytes-
dc.format.extent70325 bytes-
dc.format.extent87145 bytes-
dc.format.extent230557 bytes-
dc.format.extent178843 bytes-
dc.format.extent440518 bytes-
dc.format.extent752787 bytes-
dc.format.extent108045 bytes-
dc.format.extent70100 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypeapplication/pdf-
dc.language.isoen_US-
dc.source.urihttp://thesis.lib.nccu.edu.tw/record/#G0093252005en_US
dc.subject多層線性模型zh_TW
dc.subject一般化貝氏模型zh_TW
dc.subject反覆抽樣zh_TW
dc.subject抽樣設計zh_TW
dc.title多層線性模型的分層樣本數組合問題：對跨國政治文化研究的啟示zh_TW
dc.typethesisen
dc.relation.reference一. 中文部份zh_TW
dc.relation.reference黃紀zh_TW
dc.relation.reference2005 「多層抽樣設計芻議」，發表於「台灣選舉與民主化調查研究方工作坊」學術研討會(TEDS Workshop)，民國94年3月26、27日，台北：政治大學綜合院館三樓演講廳。zh_TW
dc.relation.reference黃旻華zh_TW
dc.relation.reference2005 「EM演算法在多層線性模型中的應用」，發表於「台灣經驗政治研究的現況與展望」學術研討會，民國94年12月23日，台北：中央研究院人社中心制度與行為研究專題中心。zh_TW
dc.relation.reference黃信豪zh_TW
dc.relation.reference2006 「多層模於選民投票行為研究的應用：以2004年總統選舉為例」，東吳政治學報，第22期，頁161-201。zh_TW
dc.relation.reference二. 英文部份zh_TW
dc.relation.referenceAchen, Christopher H. and W. Philips Shivelyzh_TW
dc.relation.reference1995 Cross-Level Inference. Chicago: The University of Chicago Press.zh_TW
dc.relation.referenceAfshartous, D.zh_TW
dc.relation.reference1995 “Determination of Sample Size for Multilevel Model Design.” Paper AERA Conference, San Francisco, 18-22. april 1995.zh_TW
dc.relation.referenceAlvarez, R. Michael,Geoffrey Garrett and Peter Langezh_TW
dc.relation.reference1991 “Government Partisanship, Labor Organization, and Macroeconomic Performance.” American Political Science Review 85:539-556.zh_TW
dc.relation.referenceBassiri, D.zh_TW
dc.relation.reference1998 Large and Small Properties of Maximum Likelihood Estimates for the Hierarchical Linear Model. Ph. D. thesis, Department of Counseling, Educational Psychology and Special Education, Michigan State University.zh_TW
dc.relation.referenceBeck, Nathaniel and Jonathan N. Katzzh_TW
dc.relation.reference1995 “What to do (and Not to Do ) with Time-Series Cross-Section Data.” American Political Science Review 89: 633-647.zh_TW
dc.relation.referenceBilly, John O. G. and David E. Moorezh_TW
dc.relation.reference1992 “A Multilevel Analysis of Marital and Nonmarital Fertility in the U.S.” Social Forces 70(4): 977-1011.zh_TW
dc.relation.referenceBlalok, R. D.zh_TW
dc.relation.reference1984 “Contextual-effects models: theoreticaland methodological issues.” Annual Review of Sociology. 10:353-372.zh_TW
dc.relation.referenceBrowne, W. J. and D. Draperzh_TW
dc.relation.reference2000 “Implementation and performance issues in the Bayesian and likelihood fitting of multilevel models.” Computational Statistics, 15:391-442.zh_TW
dc.relation.referenceBryk, Anthony S. and Stephen W. Raudenbushzh_TW
dc.relation.reference1992 Hierarchical Linear Models: Applications and Data Analysis Methods Newbury Park, CA: Sage.zh_TW
dc.relation.referenceBusing, F.zh_TW
dc.relation.reference1993 Distribution Characteristics of Variance Estimates in Two-level Models. Department of Psychometric and research Methodology, Leiden University, Leiden.zh_TW
dc.relation.referenceCohen, Michael P.zh_TW
dc.relation.reference1988 Statistical Power Analysis for the Behavioral Sciences. Mahwah, NJ: Laurence Erlbaum Associate.zh_TW
dc.relation.reference1992 “A Power Primer.” Psychological Mulletin,112(1):155-159.zh_TW
dc.relation.reference1998 “Determining Sample Sizes for Surveys with Data Analyzed by Hierarchical Linear Models.” Journal of Official Statistics, 14(3):267-275.zh_TW
dc.relation.referenceColeman J. S., Hoffer T. and Kilgore S. B.zh_TW
dc.relation.reference1982 High School Achievement: Public, Catholic and Other Schools Compared. New York: Basic Books.zh_TW
dc.relation.referencede Leeuw, Jan and Ita Kreft.zh_TW
dc.relation.reference1986 “Random Coefficient Models for Multilevel Analysis.” Journal of Educational Statistics 11:57-85.zh_TW
dc.relation.referenceDempster, A. P., D. B. Rubin, and R. K. Tsutakawazh_TW
dc.relation.reference1981 “Estimation in Covariance Components Models” Journal of the American Statistical Association, 76(374):341-353.zh_TW
dc.relation.referenceDiPrete, Thomas A. and Jerry D. Forristalzh_TW
dc.relation.reference1994 “Multilevel Models: Methods and Substance” Annual Review of Sociology 20:331-357.zh_TW
dc.relation.referenceGoldstein, Harveyzh_TW
dc.relation.reference1986 “Multilevel Mixed Linear Model Analysis Using Iterative Generalized Least Squares.” Biometrika 74:43-56.zh_TW
dc.relation.referenceGrodsky, Eric and Devah Pagerzh_TW
dc.relation.reference2001 “ The Structure of Disadvantage: Individual and Occupational Determinants of the Black-White Wage Gap” American Sociological Review 66(4): 542-567.zh_TW
dc.relation.referenceHansen, Morris H.zh_TW
dc.relation.reference1953 Sample Survey Methods and Theory, Volume II (Theory). New York: Wiley.zh_TW
dc.relation.referenceHarville, David A.zh_TW
dc.relation.reference1974 “Optimal Procedures for Some Constrained Selection Problems” Journal of the American Statistical Association 69(346):446-452.zh_TW
dc.relation.referenceHox, J. Joopzh_TW
dc.relation.reference1998 “Multilevel modeling: When and Why.” In I. Balderjahn, R. Mathar, & M. Schader eds., Classification, data analysis, and data highways pp.147-154. New York: Springer.zh_TW
dc.relation.reference2002 Multilevel Analysis Techniques and Applications New Jersey: Lawrence Erlbaum.zh_TW
dc.relation.referenceHox, J. Joop, and Cora J. M. Maaszh_TW
dc.relation.reference2001 “The Accuracy of Multilevel Structural Equation Modeling With Pseudobalanced Groups and Small Samples” Structural Equation Modeling 8(2):157-174.zh_TW
dc.relation.referenceHuang, Min-huazh_TW
dc.relation.reference2004 “Why Do People Support Political Islam? Empirical Evidence from Eight Muslim Societies.” Taiwanese Political Science Review(《台灣政治學刊》) 8(2): 245-320.zh_TW
dc.relation.referenceHuckfeldt, Robert and John Spraguezh_TW
dc.relation.reference1987 “Networks in Context: The Social Flow of Political Information.” American Political Science Review 81:1197-1216.zh_TW
dc.relation.referenceJackson, John E.zh_TW
dc.relation.reference1992 “ Estimation of Models with Variable Coefficients.” Political Analysis 3:27-49.zh_TW
dc.relation.referenceJones, Kelvin, Ronald John Johnston and Charles J. Pattiezh_TW
dc.relation.reference1992 “ People, Places and Regions: Exploring the Use of Multi-Level Modeling in the Analysis of Electoral Data.” British Journal of Political Science 22: 343-348.zh_TW
dc.relation.referenceKim, K.S.zh_TW
dc.relation.reference1990 Multilevel data analysis: A comparison of analytical alternatives. Ph. D. thesis, University of California Los Angeles.zh_TW
dc.relation.referenceKish,Lesliezh_TW
dc.relation.reference1965 Survey Sampling. New York: Wiley.zh_TW
dc.relation.referenceKreft, Ita G. G.zh_TW
dc.relation.reference1996 Are Multilevel Techniques Necessary? An Overview, Including Simulation Studies. California State University, Los Angeles.zh_TW
dc.relation.referenceKreft, Ita G. G. and Jan de Leeuwzh_TW
dc.relation.reference1998 Introducing Multilevel Modeling. London: Sage.zh_TW
dc.relation.referenceLau, Richard R.zh_TW
dc.relation.reference1989 “Individual and Contextual Influences on Group Identification.” Social Psychology Quarterly 52:220-231.zh_TW
dc.relation.referenceLee, Valerie E. and Julia B. Smithzh_TW
dc.relation.reference1995 “ Effects of High School Restructuring and Size on Early Gains in Achievement and Engagement” Sociology of Education 68(4):241-270.zh_TW
dc.relation.referenceLee, Valerie E., Todd K. Chow-Hoy, David T. Burkam, Douglas Geverdt and Becky A. Smerdonzh_TW
dc.relation.reference1998 “Sector Differences in High School Course Taking: A Private School or Catholic School Effect?” Sociology of Education 71(4):313-335.zh_TW
dc.relation.referenceLichter Daniel T., Diane K. McLaughlin, George Kephart and David J. Landryzh_TW
dc.relation.reference1992 “Race and the Retreat from Marriage among American Women: A Shortage of Marriageable Men?” American Sociology Review 57:781-799.zh_TW
dc.relation.referenceLongford, Nicholas T.zh_TW
dc.relation.reference1993 Random Coefficient Models. Oxford: Clarendon Press.zh_TW
dc.relation.referenceMacKuen, Michael and Courtney Brownzh_TW
dc.relation.reference1987 “Political Context and Attitude Change.” American Political Science Review 91:471- 490.zh_TW
dc.relation.referenceMarschall, Melissa J.zh_TW
dc.relation.reference2004 “Citizen Participation and the Neighborhood Context: A New Look at the Coproduction of Local Public Goods” Political Research Quarterly 57(2):231-244.zh_TW
dc.relation.referenceMass, Cora J. M. and Joop J. Hoxzh_TW
dc.relation.reference2001 “Robustness of multilevel parameter estimates against small sample sizes.” In J.Blasius, J. Hox, E. de Leeuw and P. Schmidt eds., Social science Methodology in the New Millennium. Proceedings of the Fifth International Conference on Logic and Methodology. Opladen, FRG: Leske+Budrich.zh_TW
dc.relation.reference2004 “Robustness Issues in Multilevel Regression Analysis.”Stistica Neerlandica 58(2):127-137.zh_TW
dc.relation.reference2005 “Sufficient Sample Sizes for Multilevel Modeling.” Methodology 1(3):86-92.zh_TW
dc.relation.referenceMiethe, Terance D. and David McDowallzh_TW
dc.relation.reference1991 “Contextual Effects in Models of Criminal Victimization” Social Forces 71: 741-759.zh_TW
dc.relation.referenceMok, Magdalenazh_TW
dc.relation.reference1995 “Sample Size Requirements for 2-Level Designs in Educational Research.” Multilevel Modelling newsletter 7(2):11-15.zh_TW
dc.relation.referenceMorrison, D. F.zh_TW
dc.relation.reference1969 Multivariate Statistical Methods. McGraw-Hill, London, New York.zh_TW
dc.relation.referenceMussoline, Lawrence and Roger C. Shousezh_TW
dc.relation.reference2001 “School Restructuring as a Policy Agenda: Why One Size May not Fit All.” Sociology of Education 74(1):43-58.zh_TW
dc.relation.referenceMuthen, B. and A. Satorrazh_TW
dc.relation.reference1995 “Complex Sample Data in Structural Equation Modeling. In P. V. Marsden ed. Sociological Methodology pp.267-316. Oxford, England: Blackwell.zh_TW
dc.relation.referenceOliver, J. Eric and Tali Mendelbergzh_TW
dc.relation.reference2000 “Reconsidering the Environmental Determinants of White Racial Attitudes” American Journal of Political Science 44(3):573-589.zh_TW
dc.relation.referencePeffley, Mark and Robert Rohrschneiderzh_TW
dc.relation.reference2003 “Democratization and Political Tolerance in Seventeen Countries: A Multilevel Model of Democratic Learning.” Political Research Quarterly 56(3):243-257.zh_TW
dc.relation.referencePong, Suet-Lingzh_TW
dc.relation.reference1998 “ The School Compositional Effect of Single Parenthood on 10th- Grade Achievement” Sociology of Education 71(1): 23-42.zh_TW
dc.relation.referencePrzewrski, Adam and Henry Teunezh_TW
dc.relation.reference1970 The Logic of Comparative Social Inquiry. New York: Wiley-Interscience.zh_TW
dc.relation.referenceRaffe D. and J. D. Willmszh_TW
dc.relation.reference1989 “Schooling and the Discouraged Worker: Local-Labour-Market Effects on Educational Participation” Sociology 23:559-581.zh_TW
dc.relation.referenceRaudenbush, Stephen and Anthony S. Brykzh_TW
dc.relation.reference1986 “A Hierarchical Model for Studying School Effects” Sociology of Education 59(1):1-17.zh_TW
dc.relation.referenceRohrschneider, Robertzh_TW
dc.relation.reference2002 “The Democracy Deficit and Mass Support for an EU-Wide Government” American Journal of Political Science 46(2):463-475.zh_TW
dc.relation.referenceRowan, Brian, Fang-Shen Chiang and Robert J. Millerzh_TW
dc.relation.reference1997 “Using Research on Employees’ Performance to Study the Effects of Teachers on Students’ Achievement” Sociology of Education 70(4):256-284.zh_TW
dc.relation.referenceSampson, Robert J. and Stephen W. Raudenbushzh_TW
dc.relation.reference1999 “Systematic Social Observation of Public Spaces: A New Look at Disorder in Urban Neighborhoods.” The American Journal of Sociology 105(3): 603-651.zh_TW
dc.relation.referenceShrout, P. E. and J. L. Fleisszh_TW
dc.relation.reference1979 “Intraclass Correlation: Uses in Assessing Rater Reliability.” Psychological Bulletin 86:420-428.zh_TW
dc.relation.referenceSmith, A. F. M.zh_TW
dc.relation.reference1973 “A general Bayesian linear model” Journal of the Royal Statistical Society ,Series B, 35:61-75.zh_TW
dc.relation.referenceSnijders, Tom A. B. and Roel J. Boskerzh_TW
dc.relation.reference1993 “Standard Errors and Sample Size for Two-Level Research” Journal of Educational Statistics 18(3):237-259.zh_TW
dc.relation.reference1999 Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling, London: Sage.zh_TW
dc.relation.referenceSteenbergenm, Marco R. and Bradford S. Joneszh_TW
dc.relation.reference2002 “Modeling Multilevel Data Structures” American Journal of Political Science 46(1): 218-237.zh_TW
dc.relation.referenceVan der Leeden, R. and F. Busingzh_TW
dc.relation.reference1994 First Iteration versus IGLS/RIGLS Estimates in Two-level Models: a Monte Carlo Study with ML3. Department of Psychometrica and research Methodology, Leiden University, Leiden.zh_TW
dc.relation.referenceVan der Leeden, R., F. Busing and E. Meijerzh_TW
dc.relation.reference1995 “Applications of bootstrap methods of two-level models” Paper, Multilevel Conference, Amsterdam, April 1-2, 1995.zh_TW
dc.relation.referenceWestern, Bruce.zh_TW
dc.relation.reference1998 “Causal Heterogeneity in Comparative Research: A Bayesian Hierarchical Modeling Approach.” American Journal of Political Science 42:1233-1259.zh_TW
dc.relation.referenceWestern, Bruce and Simon Jackmanzh_TW
dc.relation.reference1994 “Bayesian Inference for Comparative Research” American Political Science Review 88(2): 412-423.zh_TW
dc.relation.referenceWharton, Amy S., Thomas Rotolo and Sharon R. Birdzh_TW
dc.relation.reference2000 “Social Context at Wark: A Multilevel Analysis of Job Satisfaction.” Sociological Forum 15(1):65-69.zh_TW
dc.relation.referenceWillms, J. Douglas and S. Jacobsenzh_TW
dc.relation.reference1990 “Growth in Mathematics Skills during the Intermediate Years: Sex Differences and School Effects.” Int. J. Educ. Res. 14:157-174.zh_TW
item.openairecristypehttp://purl.org/coar/resource_type/c_46ec-
item.languageiso639-1en_US-
item.openairetypethesis-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
Appears in Collections:學位論文
Files in This Item:
File Description SizeFormat
25200501.pdf43.64 kBAdobe PDF2View/Open
25200502.pdf81.52 kBAdobe PDF2View/Open
25200503.pdf68.68 kBAdobe PDF2View/Open
25200504.pdf85.1 kBAdobe PDF2View/Open
25200505.pdf225.15 kBAdobe PDF2View/Open
25200506.pdf174.65 kBAdobe PDF2View/Open
25200507.pdf430.19 kBAdobe PDF2View/Open
25200508.pdf735.14 kBAdobe PDF2View/Open
25200509.pdf105.51 kBAdobe PDF2View/Open
25200510.pdf68.46 kBAdobe PDF2View/Open
Show simple item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.