社會研究方法：因果推論課程綱要（暫定）2013.09.15 課程名稱：社會研究方法─因果推論
學分數：上（3）
授課時間：周一下午第5-7節（97學年度上學期）
授課/實習教室：綜合院館南棟270836
任課教師：關秉寅
研究室：綜合院館南棟8F 270844室
諮詢時間：星期二下午2 pm – 4 pm
聯絡方式：校內分機50844；E-mail: soci1005@https://www.doczj.com/doc/b811902088.html,.tw
教學網頁：https://www.doczj.com/doc/b811902088.html,.tw/~soci1005
壹、課程介紹
科學解釋的核心是從事因果推論。社會是個複雜開放的體系，社會科學家經常是使用觀察性資料（observational data），而非實驗設計的方法來瞭解所欲研究的現象。因此，長期以來，社會科學家對於如何從事因果推論，有不同的觀點。甚至有些觀點主張因果推論是屬於形上的範疇，或根本不應該是社會科學發展的重點。即便如此，從事經驗研究的社會科學家，仍然企圖以各種研究方法來瞭解社會現象的因果關係，特別是當這些研究有重要政策意涵或影響時。
近幾年來，不論是在社會科學哲學或是社會研究方法論上，對於因果推論有更明確的論證及看法。本課程的目的則是介紹以counterfactual架構為基礎所發展出來的一些量化研究的因果推論方法。在此架構基礎上，本課程將探討因果推論的基礎觀念，以及符合這些觀念的研究設計與統計分析方法。透過對這些新進方法
瞭解，也可進一步瞭解傳統主流的量化研究方法，如迴歸分析等的限制。修習本課程的同學應對基本社會科學研究方法，以及迴歸分析等多變項的統計分析方法有一定程度的理解。
貳、上課方式
本門課的上課方式包括講授、討論與報告。
參、課程要求
本課程使用的教科書（均為綜圖指定參考書）
Morgan, Stephen L. and Christopher Winship, 2007, Counterfactuals and Causal Inference: Methods and Principles for Social Research. Cambridge: Cambridge
University Press.（以下簡稱MW）
Guo, Shenyan and Mark W. Fraser, 2010, Propensity Score Analysis: Statistical Methods and Applications. Los Angeles, CA: Sage.（以下簡稱GF）Morgan, Stephen L. (ed.), 2013, Handbook of Causal Analysis for Social Research. New York: Springer.（以下簡稱Handbook）
除了上列教科書外，每週依進度另有補充閱讀教材。部份補充閱讀教材可由本校線上資料庫，以及以下討論counterfactual causal analysis的網站取得：
https://www.doczj.com/doc/b811902088.html,/~cwinship/cfa.html。
另可參考American Educational Research Association放在網路上的白皮書：
Schneider, Barbara, Martin Carnoy, Jeremy Kilpatrick, William H. Schmitt, and Richard J. Shavelson, 2007, Estimating Causal Effects Using Experimental and
Observational Designs. Washington, D. C.: American Educational Research
Association.
https://www.doczj.com/doc/b811902088.html,/uploadedFiles/Publications/Books/Estimating_Causal_Eff
ects/Causal%20Effects.pdf (Date visited: Sept. 15, 2013).
修習本課程的同學應分工負責議題的報告及討論。所有同學均應依進度研習教材，積極參與討論。
除了積極參與討論外，修習同學要繳交兩種作業：
第一種作業是輪流由同學就該週之閱讀教材負責撰寫摘要及提出討論議題。繳交時間是分工報告當週。
第二種作業每位同學都要做的期末報告。此報告的內容配合本課程學習到的研究方法，撰寫一可用大型資料庫如台灣教育長期追蹤資料庫（TEPS）之實證研究
計畫。此報告分成兩個部分。第一部份包括（1）提出清楚的研究問題意識，說明所欲研究的議題為何，為何有興趣研究此議題等；（2）針對此一研究的議題做初步的文獻探討。所探討的文獻以過去十年內發表者，且為利用大型觀察資料從事研究者為主。此部份之書面報告以兩頁為原則，並於第九週做口頭報告。口頭報告之形式與前述各週之報告相同。
期末報告的第二部份則為結合第一部份提出一研究計畫。計畫內容應包括下列之內容：（1）提出一些清楚的研究架構，因果模式及假設；（2）使用的分析方法；（3）初步研究發現。
所有的作業引用文獻及參考書目之格式應依《台灣社會學刊》之規定
（https://www.doczj.com/doc/b811902088.html,.tw/Publication/file/sample_2006_7.pdf）。所有報告均應打字。
*本課程實施「榮譽自重制度」，修習本課程同學應遵守考試不作弊，作業不抄襲，也不給別人抄襲的規範。請在每一作業後親筆書寫「本次作業為本人依循學術規範所完成，絕非抄襲他人，亦未給他人抄襲」等語，並簽名。若有抄襲嫌疑，經第三者調查屬實後，本學期的成績為零分，以後亦不得選修本人之課程。
肆、評分標準
平常上課表現：10%
讀書摘要及口頭報告：40%
期末報告：50%
伍、本學期課程進度（各週需做摘要報告的閱讀教材視選修人數而定；以下書目前有*者為必讀教材）
第一週：課程介紹
第二週：因果分析的基礎概念
閱讀教材：*MW, Ch. 1, “Introduction.”
*Handbook, Ch. 3, “Types of Causes.”
Handbook, Ch. 2, “A History of Causal Analysis in the Social Sciences.”
*Holland, Paul W., 1986, “Statistics and Causal Inference.”Journal of the American Statistical Association 81: 945-960.
Sobel, Michael E., 1995. “Causal Inference in the Social and Behavioral Sciences.” Pp. 1-38 in Handbook of Statistical Modeling for the
Social and Behavioral Sciences, edited by G. Arminger, C. C. Clogg,
and M. E. Sobel. New York: Plenum.
*Sobel, Michael, E., 1996, “An Introduction to Causal Inference.”
Sociological Methods and Research 24: 353-379.
Pearl, Judea, 2000, “Epilogue: The Art and Science of Cause and Effect.”
Pp. 331-358 in Causality: Models, Reasoning, and Inference, by J.
Pearl. Cambridge: Cambridge University Press. (see also
https://www.doczj.com/doc/b811902088.html,/LECTURE/lecture_sec1.htm)
Pearl, Judea, 1999, “Reasoning with Cause and Effect.”
https://www.doczj.com/doc/b811902088.html,/IJCAI99/ijcai-99.pdf (Date visited: August
30, 2008).
第三週：反事實（counterfactual）分析的架構
閱讀教材：*MW, Ch. 2, “The Counterfactual Model.”
*GF, Ch. 2, “Counterfactual Framework and Assumptions.”
Handbook, Ch. 5, “Causal Models and Counterfactual.”
*Gangl, Markus, 2010, “Causal Inference in Sociological Research.”
Annual Review of Sociology 36: 21-47 (此階段至少讀21-32).
Heckman, James, 2005, “The Scientific Model of Causality.”
Sociological Methodology 35: 1-98.
Cook, Thomas D., 2002, “Randomized experiments in Educational Policy Research: A Critical Examination of the Reasons that the
Educational Evaluation Community Has Offered for not Doing
Them.”Educational Evaluation and Policy Analysis 24: 175-199.
Rubin, Donald R., 1974, “Estimating Causal Effects of Treatments in Randomized and Nonrandomized Studies.”Journal of Educational
Psychology 66: 688-701.
Winship, Christopher and Stephen L. Morgan, 1999, “The Estimation of Causal Effects from Observational Data.”Annual Review of
Sociology 25: 659-706.
第四週：估計因果效應─條件控制（conditioning）
閱讀教材：*MW, Ch. 3, “Estimating Causal Effects by Conditioning.”
*GF, Ch. 3, “Conventional Methods for Data Balancing.”
*Rosenbaum, Paul R., 2005, “Observational Study.” Pp. 1451-1462 in Encyclopedia of Statistics in Behavioral Science, Volume 3, edited by
B. S. Everitt and D.
C. Howell. Chichester: John Wiley and Sons.
Freedman, David A., 2004, “Graphical Models for Causation, and the Identification Problem.”Evaluation Review 28: 267-293.
*Pearl, Judea, 1995, “Causal Diagrams for Empirical Research.”
Biometrika 82: 669-688.
第五～七週：估計因果效應─配對估計（matching estimators）
閱讀教材：*MW, Ch. 4, “Matching Estimators of Causal Effects.”
*GF, Ch. 5, “Propensity Score Matching and Related Models.”
*GF, Ch. 6, “Matching Estimators.”
*GF, Ch. 7, “Propensity Score Analysis with Nonparametric Regression.”
*Caliendo, Marco and Sabine Kopeinig, 2008, “Some Practical Guidance for the Implementation of Propensity Score Matching.”Journal of
Economic Surveys 22: 31-72.
*Morgan, Stephen L., 2001, “Counterfactuals, Causal Effect
Heterogeneity, and the Catholic School Effect on Learning.”
Sociology of Education 74: 341-374.
Dehejia, Rajeev H. and Sadek Wahba, 2002, “Propensity Score Matching for Non-experimental Causal Studies.”The Review of Economics and
Statistics 84: 151-161.
Rosenbaum, Paul R. and Donald B. Rubin, 1986, “The Central Role of the Propensity Score in Observational Studies for Causal Effects.”
Biometrika 70: 41-55.
Smith, Herbert L., 2001, “Matching with Multiple Controls to Estimate Treatment Effect in Observational Studies.”Sociological
Methodology 27: 325-353.
Smith, Jeffrey A. and Petra E. Todd, 2005, “Does Matching Overcome LaLonde?s Critique of Nonexperimental Estimators?”Journal of
Econometrics 125: 305-353.
*Xie, Yu, Jeannie E. Brand, and Ben Jann, 2012, “Estimating
Heterogeneous Treatment Effects with Observational Data.”
Sociological Methodology 42: 314-347.
第八週：估計因果效應─迴歸分析
閱讀教材：*MW, Ch. 5, “Regression Estimators of Causal Effects.”
Duncan, Otis D., 1966, “Path Analysis: Sociological Examples.”
American Journal of Sociology 72: 1-16.
Freedman, David, 1997, “From Association to Causation via Regression.”
Advances in Applied Mathematics 18: 59-110.
*Gelman, Andrew and Jennifer Hill, 2007, “Ch. 9 Causal Inference Using Regression on Treatment Variable.” Pp. 167-198 in Data Analysis
Using Regression and Multilevel/Hierarchical Models. New York:
Cambridge University Press.
https://www.doczj.com/doc/b811902088.html,/~gelman/arm/chap9.pdf (Date
accessed: Sept. 15, 2013).
Freedman, David and Richard A. Berk, 2008. “Weighting Regression by Propensity Scores.”Evaluation Review 32 (4): 392-409.
Krueger, Alan B., 1993, “How Computers Have Changed the Wage
Structure: Evidence from Micro Data.”Quarterly Journal of
Economics 108: 33-60.
DiNardo, John E. and Jorn-Steffen Pischke, 1997, “The Return to
Computer Use Revisited: Have Pencils Changed the Wage
Structure too?”Quarterly Journal of Economics 112: 291-303.
Frank, Kenneth A., 2000, “Impact of a Confounding Variable on the
Inference of a Regression Coefficient.”Sociological Methods and
Research 29: 147-194.
Morgan, Stephen L. and Jennifer J. Todd, 2008, “A Diagnostic
Routine for the Detection of Consequential Heterogeneity of
Causal Effects.”Sociological Methodology 38: 231-281.
第九週：研究計畫口頭報告
第十週：Issues of Identification and Sensitivity Analysis
閱讀教材：*MW, Ch. 6, “Identification in the Absence of a Complete Model of
Causal Exposure.”
*GF, Ch. 8, “Selection Bias and Sensitivity Analysis.”
*Harding, David J., 2004, “Counterfactual Models of Neighborhood
Effects: The Effect of Neighborhood Poverty on Dropping out and
Teenage Pregnancy.”American Journal of Sociology 109: 676-719.
Becker, Sascha O. and Marco Caliendo, 2007, “Sensitivity Analysis for
Average Treatment Effects.”The Stata Journal 7(1): 71-83.
Rosenbaum, Donald R., 2005, “Sensitivity Analysis in Observational
Studies.” Pp. 1809-1814 in Encyclopedia of Statistics in Behavioral
Science, Volume 4, edited by B. S. Everitt and D. C. Howell.
Chichester: John Wiley and Sons.
Manski, Charles, Gary D. Sandefur, Sara McLanahan and Daniel Powers, 1992, “Alternative Estimates of the Effect of Family Structure
During Adolescence on High School Graduation.”Journal of the
American Statistical Association, 87: 25-37.
Rosenbaum, Paul R., 1990, “Dropping out of High School in the United States: An Observational Study.”Journal of Educational Statistics,
11: 207-224.
第十一週：估計因果效應─工具變項
閱讀教材：*MW, Ch. 7, “Instrumental Variable Estimators of Causal Effects.”
*GF, Ch. 4, “Sample Selection and Related Models.”
*Bollen, Kenneth A., 2012, “Instrumental Variables in Sociology and
Social Science.”Annual Review of Sociology 38: 37-72.
Angrist, Joshua D. and Alan B. Kruger, 2001, “Instrumental Variables
and the Search for Identification: From Supply and Demand to
Natural Experiments.”Journal of Economic Perspectives 15:
69-85.
Angrist, Joshua D., Guido W. Imbens, and Donald R. Rubin, 1996,
“Identification of Causal Effects Using Instrumental Variables.”
Journal of American Statistical Association 91: 444-455.
Angrist, Joshua D. and Alan B. Kruger, 1991, “Does Compulsory School Attendance Affect Schooling and Earnings?”Quarterly Journal of
Economics 106: 979-1014.
Foster, E. M. and Sara McClanahan, 1996, “An Illustration of the Use of Instrumental Variables: Do Neighborhood Conditions Affect a
Young Person?s Chance of Finishing High School?”Psychological
Methods 1: 249-260.
Rosenzweig, Mark R. and Kenneth I. Wolpin, 2000, “Natural …Natural
Experiments? in Economics.”Journal of Economic Literature 38:
827-874.
DiPrete, Thomas A., and Markus Gangl, 2004. “Assessing bias in the
estimation of causal effects: Rosenbaum bounds on matching
estimates and instrumental variables with imperfect instruments.”
Sociological Methodology 34: 271-310.
第十二~十四週：因果效應估計─重複觀察
閱讀教材：*MW, Ch. 9, “Repeated Observations and the Estimation of Causal
Effects.”
*Handbook, Ch. 7, “Fixed Effects, Random Effects, and Hybrid Models for Causal Analysis.”
*Allison, Paul D., 2009, Fixed Effects Regression Models. Thousand Oaks, CA: Sage. Ch. 1 ~ Ch. 3.
*Angrist, Joshua D. and J?rn-Steffen Pischke, 2009, “Ch. 6 Getting a Little Jumpy: Regression Discontinuity Designs.” Pp. 251-267 in
Mostly Harmless Econometrics: An Empiricist Companion.
Princeton, NJ: Princeton University Press.
*Bollen, Kenneth A. and Jeannie E. Brand, 2010, “A General Panel Model with Random and Fixed Effects: A Structural Equation
Approach.”Social Forces 89 (1): 1-34.
*Finkel, Steven E., Causal Analysis with Panel Data. Thousand Oaks, CA: Sage. Ch. 1 ~ Ch. 3.
Halaby, Charles N., 2004, “Panel Models in Sociological Research: Theory into Practice.”Annual Review of Sociology 30: 507-544. Johnson, David R., 1995, “Alternative Methods for the Quantitative Analysis of Panel Data in Family Research: Pooled Time-Series
Models”Journal of Marriage and the Family 57: 1065-1077. Johnson, David, 2005, “Two-Wave Panel Analysis: Comparing Statistical Methods for Studying the Effects of Transitions.”Journal of
Marriage and Family 67: 1061-1075.
Benjamin R. Karney and Thomas N. Bradbury, 1995, “Assessing Longitudinal Change in Marriage: An Introduction to the Analysis of Growth Curves.” Journal of Marriage and the Family 57:
1091-1108.
Regression Discontinuity
Jacob, Brian A. and Lars Lefgren, 2004, “Remedial Education and Student Achievement: A Regression Discontinuity Analysis.”The
Review of Economics and Statistics 86: 226-244.
Difference in difference
Dynarski, Susan M., 2003, “Does Aid Matter? Measuring the Effect of Student Aid on College Attendance and Completion.”The American Economic Review 93: 279-288.
Fixed effects
Garces, Eliana, Duncan Thomas, and Janet Currie, 2002, “Longer-term
Effects of Head Start.”The American Economic Review 92:
999-1012.
Budig, Michelle J. and Paula England, 2001, “The Wage Penalty for
Motherhood.”American Sociological Review 66: 204-225.
Vanlaningham, Jody, David R. Johnson, & Paul Amato, 2001, “A Marital Happiness, Marital Duration, and the U-shaped Curve: Evidence
from a Five-Wave Panel Study, Social Forces 79:1313-1342.
Panel data
Sun, Yongming, 2001, “Family Environment and Adolescents'
Well-Being before and after Parents' Marital Disruption: A
Longitudinal Analysis.”Journal of Marriage and the Family 63:
697-713.
Warren, John Robert, Jennifer T. Sheridan and Robert M. Hauser, 2002, “Occupational Stratification across the Life Course: Evidence from
the Wisconsin Longitudinal Study.” American Sociological Review
67: 432-455.
第十五週：機制與因果解釋
閱讀教材：*MW, Ch. 8, “Mechanisms and Causal Explanation.”
*Handbook, Ch. 12, “New Perspectives on Causal Mediation Analysis.”
Goldthorpe, John H., 2001, “Causation, Statistics, and Sociology.”
European Sociological Review 17: 1-20.
Hedstr?m, Peter, 2005, “Social Mechanism and Explanatory Theory.” Pp.
11-33 in Dissecting the Social: On the Principles of Analytical
Sociology. Cambridge: Cambridge University Press.
Machamer, Peter, Lindley Darden, and Carl F. Craver, 2000, “Thinking about Mechanisms.”Philosophy of Science 67: 1-25.
Reskin, Barbara F., 2003, “Including Mechanisms in our Models of
Ascriptive Inequality.”American Sociological Review 68: 1-21.
Sayer, Andrew, 2000, “Key Features of Critical Realism in Practice: A Brief Outline.” Pp. 10-28 in Realism and Social Science. London:
Sage.
第十六週：進階議題
閱讀材料：*MW, Ch. 10, “Counterfactual Causality and Future Empirical Research in
the Social Sciences.”
*Handbook, Ch. 15, “Eight Myths About Causality and Structural
Equation Models.”
*Handbook, Ch. 16, “Heterogeneous Agents, Social Interactions, and
Causal Inference.”
Arpino, Bruno and Fabrizia Mealli, 2011, “The Specification of the
Propensity Score in Multilevel Observational Studies.”
Computational Statistics and Data Analysis 55 (4): 1770-1780.
Leite, Walter L., Robert Sandbach, Rong Jin, Jann W. MacInnes, and M.
Grace-Ann Jackman, 2012, “An Evaluation of Latent Growth
Models for Propensity Score Matched Groups.” Structural Equation
Modeling: An Multidisciplinary Journal 19 (3): 437-456.
Hong, Guanglei and Yu Bin, 2008, “Effects of Kindergarten Retention on Children's Social-Emotional Development: An Application of
Propensity Score Method to Multivariate, Multilevel Data.”
Developmental Psychology 44(2): 407-421.
Hong, Guanglei, 2010, “Marginal Mean Weighting Through Stratification: Adjustment for Selection Bias in Multilevel Data.”Journal of
Educational and Behavioral Statistics 35 (5): 499-531.
McKenzie, David, John Gibson, and Steven Stillman, 2006, “How
Important is Selection? Experimental versus Non-experimental
Measures of the Income Gains from Migration.” World Bank Policy
Research Working Paper 3906.
https://www.doczj.com/doc/b811902088.html,/servlet/WDSContentServer/WDSP/I
B/2006/05/01/000016406_20060501143118/Rendered/PDF/wps390
6.pdf (Date visited: August 30, 2008).
Glazerman, Steven, Dan M. Levy, and David Myers, 2003,
“Nonexperimental vs. Experimental Estimates of Earnings Impacts.”
The Annals of the American Academy of Political and Social Science
589:63-93.
Kaplan, David and Jianshen Chen, 2012, “A Two-Step BAYESIAN
Approach for Propensity Score Analysis: Simulations and Case
Study.”Psychometrika 77 (3): 581-609.
第十七～十八週：總結及研究計畫報告