Home >  University of Edinburgh Graduate School of Social and Political Studies ADVANCED QUANTITATIVE METHODS, 2004 RECOMMENDED TEXTS: There is no r

University of Edinburgh Graduate School of Social and Political Studies ADVANCED QUANTITATIVE METHODS, 2004 RECOMMENDED TEXTS: There is no r


    University of Edinburgh

    Graduate School of Social and Political Studies

      ADVANCED QUANTITATIVE METHODS, 2004

RECOMMENDED TEXTS:

There is no required text for the course. The text which most obviously covers the course material is:

      Tacq J  (1997).  Multivariate analysis techniques in social science research, Sage, London. 

      Two texts cover the main sub-topics of the course: Causal Analysis and Dimensional Analysis. You are strongly recommended to purchase a copy of:

          *Cohen, J & Cohen, P (1983) Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences, Second edition. Hillsdale, NJ: Lawrence Erlbaum Associates

          *Bartholomew, DJ, Steele, F, Moustaki,I & Galbraith, JL (2002)The Analysis and Interpretation of Multivariate Data for Social Scientists , London: Chapman and Hall.

      A definitive reference textbook is:

          *Tabachnick, Barbara G. and Linda S. Fidell (2001). Using Multivariate Statistics, Fourth Edition. Boston: Allyn and Bacon

      A valuable text covering the subject material of the course and oriented to running relevant SPSS and SAS programs is:

          *Stevens, James P (2002) Applied Multivariate Statistics for the Social Sciences, Fourth Edition. Hillsdale, NJ: Lawrence Erlbaum Associates (includes CD of Syntax / Run Files). 

          You are also recommended to read or purchase relevant titles from the Sage Quantitative Applications in the Social Sciences cited below.

           

          COURSE MATERIALS

          N.B: Course documentation, Lecture OHPs and Powerpoint Materials, Preliminary and Follow-up Reading materials and Web references are available on http://www.tonycoxon.com (University of Edinburgh: AQM 2004) and will subsequently be transferred to the Edinburgh WebCT system. 
          EXTENDED BIBLIOGRAPHY:

          A: MULTIVARIATE STATISTICAL ANALYSIS

            Chatfield, C & Collins, AJ (nd) Introduction to Multivariate Analysis London: Chapman and Hall

            Dillon, W. R., & Goldstein, M. (1984). Multivariate analysis: Methods and applications. N. Y.: Wiley.

            Fox, J. (1997). Applied Regression Analysis, Linear Models and Related Methods. Thousand Oaks, CA: Sage.

            Gnanadesikan, R. (1977). Statistical data analysis of multivariate observations, N.Y.: Wiley.

            Joseph F. Hair, Jr., Rolph E. Anderson, Ronald L. Tatham (1987) Multivariate data analysis with readings, New York : Macmillan.

            Harris, R. J. (1975). A Primer of multivariate statistics. N.Y.: Academic Press.

            Johnson, R. A., & Wichern D. W. (1992). Applied multivariate statistical analysis, Prentice Hall, 1992, 3rd Ed. [ISBN 0-13-041773-4]

            Morrison, D. F. (1990). Multivariate statistical methods (3rd ed.), N.Y.: McGraw Hill.]

            Overall, J. E. & Klett, C. J. (1972). Applied multivariate analysis N.Y.: McGraw Hill.

            Tabachnick, B. G. & Fidell, L. S. (1996). Using Multivariate Statistics Harper Collins, 1996, 3nd Ed.

            Tatsuoka, M. M. (1988). Multivariate analysis. (2nd ed.) N.Y.: Wiley.

            Timm, N. H. (1974). Multivariate analysis with applications in education and psychology. Belmont, CA: Brooks/Cole.

            Van de Geer, J. P. (1971). Introduction to multivariate analysis for the social sciences. San Francisco: W. H. Freeman.  

          B: CAUSAL ANALYSIS: MULTIPLE LINEAR REGRESSION & STRUCTURAL EQUATIONAL MODELLING

           

              Achen, Christopher H. (1982). Interpreting and using regression. Series: Quantitative Applications in the Social Sciences, No. 29. Thousand Oaks, CA: Sage Publications

           

              Allison, Paul D. (1999). Multiple regression. Thousand Oaks, CA: Pine Forge Press.

           

              Berk, Richard A. (2003). Regression analysis: A constructive critique. Thousand Oaks, CA: Sage Publications.

           

              Berry, William D. (1993). Understanding Regression Assumptions. Series: Quantitative Applications in the Social Sciences, No. 92. Thousand Oaks, CA: Sage Publications

           

              Cohen, J. and P. Cohen, P. (1983). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. (2nd ed.). Lawrence Erlbaum Assoc.

           

              Duncan, O. D. (1975). Introduction to structural equation models. New York: Academic Press.

           

              Fox, John (1991). Regression Diagnostics. Thousand Oaks, CA: Sage Publications. Quantitative Applications in the Social Sciences Series No. 79.

           

              Goldberger, A.S. & Duncan, O.D. (Eds) (1982). Structural Equation Models in the Social Sciences, New York: Seminar Press.

              Hardy, Melissa A. (1993). Regression with dummy variables. Thousand Oaks, CA: Sage Publications. Series: Quantitative Applications in the Social Sciences, No. 93.

           

              Jaccard, James, Robert Turrisi, and Choi K. Wan (1990). Interaction effects in multiple regression. Thousand Oaks, CA: Sage Publications. Series: Quantitative Applications in the Social Sciences, No. 72.

           

              Menard, Scott (1995). Applied logistic regression analysis. Thousand Oaks, CA: Sage Publications. Series: Quantitative Applications in the Social Sciences, No. 106.

           

              Miles, Jeremy and Mark Shevlin (2001). Applying regression and correlation. Thousand Oaks, CA: Sage Publications.

           

              Schroeder, Larry D., David L. Sjoquist, and Paula E. Stephan (1986). Understanding regression analysis: An introductory guide. Thousand Oaks, CA: Sage Publications. Series: Quantitative Applications in the Social Sciences, No. 57.

           
           
           

          C: DIMENSIONAL ANALYSIS:

                (A) PRINCIPAL COMPONENTS & FACTOR ANALYSIS

              Everitt, B. S. (1984). An Introduction to Latent Variable Models. New York: Chapman and Hall.

            Gorsuch, R. L. (1983). Factor analysis (2nd. ed.) Hillsdale, N.J.: Erlbaum.

              Harman, H. H. (1967). Modern factor analysis. (2nd ed.). Chicago: University Press.

              Jackson, J. E. (1991). A user's guide to principal components. NY: Wiley.

            Kim, J.-O. and Mueller, C. W. (1978). Factor analysis: Statistical methods and practical issues. Beverly Hills, CA: Sage Publications. (QASS)

            Lawley, D.N. & Maxwell, A.E. (1971) Factor Analysis as a Statistical Method, 2nd ed. London: Butterworth

           
           
           

                (B) MULTIDIMENSIONAL SCALING

           

              Arabie, P., Carroll, J. D., & DeSarbo, W. S. (1987).

              Three-way scaling and clustering. Newbury Park:  Sage

           

              Bagozzi R P(ed (1994) Advanced Methods in Marketing Research, Oxford: Blackwell.

           

              Birnbaum M (1998) Handbook of Perception and Cognition, Vol 3: Measurement, Judgement and Decision Making, 2nd edition.

           

              Borg I, Groenen P (1997) Modern Multidimensional Scaling New York: Springer Verlag 

           

              Cox TF, Cox AA (1994) Multidimensional Scaling, London Chapman & Hall

           

              Coxon, APM (1999) Sorting data: collection and analysis, Newbury Park: Sage

           

              Everitt BS, Rabe-Hesketh S (1997) The Analysis of Proximity Data, London: Arnold

           

              Kruskal,, J.B. and Wish, M. (1978) Multidimensional Scaling. Sage. QASS No. 11

           

              Weller SC, Romney AK (1990) Metric Scaling: Correspondence Analysis, Newbury Park: Sage

            Young FW (1987) Multidimensional Scaling: History, Theory, Applications, Hillsdale: Lawrence Erlbaum

            see also: definitive bibliography on three-way scaling: http://www.leidenuniv.nl/fsw/three-mode/bibliogr/biblio_a.htm

           

          APPENDIX: SAGE QASS SERIES

          (Full list available; these are volumes appropriate to the AQM course)


          No. Title Author(s) AQM BLOCK
          3 Causal Modeling, 2nd Edition Asher 1
          6 Canonical Comparison and Factor Comparison Levine 3
          11 Multidimensional Scaling Kruskal & Wish 3***
          12 Analysis of Covariance Wildt & Ahtola 2
          13 Introduction to Factor Analysis Kim & Mueller 3***
          14 Factor Analysis Kim & Mueller 3*
          17 Reliability and Validity Assessment Carmines & Zeller 1
          19 Discriminant Analysis Klecka 2
          20 Log-Linear Models Knoke & Burke 2
          22 Applied Regression Lewis-Beck 2***
          29 Interpreting and Using Regression Achen 2**
          32 Measures of Association Liebetrau 1
          33 Confirmatory Factor Analysis Long 3
          34 Covariance Structures Long 2
          37 Nonrecursive Causal Models Berry 2
          44 Cluster Analysis Aldenderfer & Blashfield 3*
          45 Linear Probability, Logit, and Probit Models Aldrich & Nelson 2
          47 Canonical Correlation Analysis Thompson 2
          50 Multiple Regression in Practice Berry & Feldman 2**
          54 Multivariate Analysis of Variance Bray & Maxwell 2
          55 The Logic of Causal Order Davis 1*
          57 Understanding Regression Analysis Schroeder, Sjoquist, & Stephan 2*
          65 Three-Way Scaling and Clustering Arabie, Carroll, & DeSarbo 3**
          69 Principal Components Analysis Dunteman 3***
          72 Interaction Effect in Multiple Regression Jaccard, Turris, & Wan 2*
          74 Experimental Design and Analysis Brown, & Melamed 1
          75 Metric Scaling Weller & Romney 3*
          78 Data Theory and Dimensional Analysis Jacoby 3*
          79 Regression Diagnostics Fox 2
          86 Logit Modeling DeMaris 2
          92 Understanding Regression Assumptions Berry 2
          93 Regression With Dummy Variables Hardy 2
          94 Loglinear Models With Latent Variables Hagenaars 2
          101 Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models Liao 2
          102 Typologies and Taxonomies Bailey 3
          105 Causal Analysis With Panel Data Finkel 2
          106 Applied Logistic Regression Analysis Menard 2**
          111 Regression Models: Censored, Sample Selected, or Truncated Data Breen 2
          112 Tree Models of Similarity and Association Corter 3*
          114 LISREL Approaches to Interaction Effects in Multiple Regression Jaccard & Wan 2
          120 Statistical Graphics for Visualizing Data Jacoby 3
          121 Applied Correspondence Analysis Clausen 3
          126 Latent Class Scaling Analysis Dayton 3
          127 Sorting Data: Collection and Analysis Coxon 3** (!)
           

          Star rating:

          *** very important or crucial reading

          ** desirable

          * important

                (could be useful or for the cognoscenti)


          AQM 2004 (page )

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