The QME Reading List

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The faculty members of the Quantitative Methods and Evaluation Program at Vanderbilt University have assembled the following list of suggested readings to help our graduate students develop into skilled methodologists. The reading materials are �rated� as follows:

REQuired: An enduring classic in the Field or will be soon.

RECommended: These are interesting for their treatment of specialized topics.

FYI: These are topics that you should know about (at least know that they exist).

Journals

• Annual Review of Psychology REQ (methodology chapters).
  
• Psychological Methods REQ
  
• Multivariate Behavioral Research REQ
  
• Evaluation ReviewREQ
  
• Applied Psychological Measurement REC
  
• Chance REC
  
• Evaluation and Program Planning REC
  
• Psychometrika REC
  
• Sociological Methods and Research REC
  
• New Directions for Evaluation FYI
  
• Psychological Bulletin FYI � pre 1996
  
• American Evaluation Journal FYI
  
• Journal of Consulting and Clinical Psychology FYI
  
• Journal of Applied Psychology FYI
  
• The American Statistician FYI

General Statistical Theory

• Cohen, J. (1968). Multiple regression as a general data-analytic system. Psychological Bulletin, 70, 426-433 REC.
  
  
  
• Efron, B., & Tibshirani, R.J. (1998). An introduction to the bootstrap. New York: Chapman & Hall. REC
  
  
  
• Efron, B.,& Gong, G. (1983). A leisurely look at the bootstrap the jackknife and cross-validation. American Statistician, 37, 36-48. REC
  
  
  
• Hays, W.L. (1994). Statistics. Fort Worth: Harcourt Brace. REQ
  
  
  
• Cohen, J. (1977). Statistical power analysis for the behavioral sciences. New York: Academic Press REQ
  
  
  
• Draper, N.R.,& Smith, H. (1981). Applied regression analysis. New York: JohnWiley.
  
  
  
• Hosmer, D.W., & Lemeshow, S. (1989). Applied logistic regression. New York: John Wiley.REC
  
  
  
• Siegel, S., & Castellan, N.J.,Jr. (1988). Nonparametric statistics for the behavioral sciences. McGraw-Hill: New York.FYI
  
  
  
• Long, J.S. (1997). Regression models for categorical and limited dependent variables. Thousand Oaks, CA: Sage. REC.
  
  
  
• Meehl, P.E.(1978). Theoretical risks and tabular asterisks: Sir Karl, Sir Ronald, the progress soft psychology. Journal of Consulting and Clinical Psychology, 46, 806-834.REQ.
  
  
  
• Maxwell, S.E., & Delaney, H.D. (2000). Designing experiments and analyzing data. Mahwah, N.J.: Erlbaum. REQ

General Multivariate Books

• Johnson, D.W. & Wichern, R. A. (1998). Applied multivariate statistical analysis (4^th ed.) Upper Saddle River, N.J. : Prentice Hall. REQ
  
  
  
• Carroll, J. D., Green, P. E., & Chaturvedi, A. (1997). Mathematical tools for applied multivariate analysis. San Diego : Academic Press. REQ
  
  
  
• Marascuilo, J.A., & Levin, J.R. (1983). Multivariate statistics in the social sciences. Monterey, CA: Brooks/Cole.

Specific Psychometric/Statistical Techniques

Categories Versus Continua/Profile Analysis

• Cronbach, L.J., & Gleser, G .C. (1953). Assessing similarity between profiles. Psychological Bulletin, 50, 456-473.
  
  
  
• Grayson, D. (1987). Can categorical and dimensional views of psychiatric illness be distinguished? British Journal of Psychiatry, 151, 355-361. REC.
  
  
  
• Waller, N.G., & Meehl, P. E. (1998). Multivariate taxometric procedures : distinguishing types from continua. Thousand Oaks, CA : Sage Publications. REC.
  

Factor Analysis/Structural Equation Models

• Alwin, D.F., & Hauser, R.M. (1975). The decomposition of effects in path analysis. American Sociological Review, 40, 37-47. REC.
  
  
  
• Baron, R.M.,& Kenny, D.A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.
  
  
  
• Bollen, K.A.(1989). Structural equations with latent variables. New York: John Wiley. REQ.
  
  
  
• Cliff,N.R. (1983). Some cautions concerning the application of causal modeling methods. Multivariate Behavioral Research, 18, 155-126. REQ.
  
  
  
• Gorsuch, R.L.(1983). Factor analysis. Hillsdale, N.J.: Erlbaum. REC.
  
  
  
• Holmbeck,G.N. (1997). Toward terminological, conceptual, and statistical clarity in the study of mediators and moderators: Examples from the child-clinical and pediatric psychology literatures. Journal of Consulting and Clinical Psychology, 65, 599-610.
  
  
  
• Rogosa, D.R.(1980). A critique of cross-lagged correlation. Psychological Bulletin, 88, 245-258. REC.
  

Item Response Theory

• Embretson,S.E., & Reise, S.P. (2000). Item response theory for psychologists. Mahwah, N.J.: Erlbaum. REQ
  
  
  
• Hambleton, R. K., Swaminathan, H. & Rogers, H. J. (1991). Fundamentals of item response theory.Newbury Park,Calif. : Sage Publications. REQ.
  
  
  
• Hambleton, R. K., Swaminathan, H. (1985). Item response theory: Principles and applications. Boston, MA: Kluwer-Nijhoff Pub. REQ

The Analysis of Change

• Collins, L. M., & Horn, J.L. (1991). Best methods for the analysis of change. Washington, D.C.: American Psychological Association. REC
  
  
  
• Cronbach,L.J., & Furby, L. (1970). How should we measure “change” — or should we? Psychological Bulletin, 74, 68-80. REQ.
  
  
  
• Gottman, J.M.(Ed.)(1995). The analysis of change. Hillsdale, N.J.: Erlbaum.
  
  
  
• Bryk, A.S.,& Raudenbush, S.W. (1992). Hierarchical linear models: Newbury Park: Sage. REQ.
  
  
  
• Diggle, P.J.,Liang, K-Y, & Zeger, S.L. (1996). Analysis of longitudinal data. Oxford: Clarendon.
  
  
  
• Muthen, B.O., & Curran, P.J. (1997). General longitudinal modeling of individual differences in experimental designs: A latent variable framework for analysis and power estimation. Psychological Methods, 2, 371-402. REQ
  
  
  
• Prochaska, J.O.,DiClemente, C.C., & Norcross, J.C. (1992). In search of how people change: Applications to addictive behaviors. American Psychologist, 47, 1102-1114. REC
  
  
  
• Speer, D.C.,& Greenbaum, P.E. (1995). Five methods for computing significant individual client change and improvement rates: Support for an individual growth curve approach. Journal of Consulting and Clinical Psychology, 63(6), 10044-1048. FYI
  
  
  
• Willet, J.B.,& Sayer, A.G. (1994). Using covariance structures analysis to detect correlates and predictors of individual change over time. Psychological Bulletin, 116, 363-381.REQ

Missing Data

• Graham, J.W.,Hofer, S.M., Donaldson, S.I., MacKinnon, D.P., & Schafer, J.L. (1997). Analysis with missing data in prevention research. In K.J. Bryant, M. Windle, & S.G. West (Eds.), The Science of Prevention: Methodological Advances From Alcohol and Substance Abuse Research Washington, D.C.: American Psychological Association.

Multilevel Modeling

• Kreft, I., & De Leeuw, J.D. (1998). Introducing multilevel modeling. London: Sage

Math Basics

• Searle, S.R. (1982). Matrix algebra useful for statistics. New York:John Wiley
  
  
  
• Hagle, T. (1995). Basic Math for Social Scientists: Concepts (Sage University Papers Series. Quantitative Applications in the Social Sciences, No-07-108)
  
  
  
• Iversen, G. (1996). Calculus (Quantitative Applications in the Social Science , Vol 110)
  

Time Series

• Diggle,  P.J. (2000). Time series: A biostatistical introduction. Oxford: Clarendon Press. FYI
  
  
  
• Gottman, J.M. (1981). Time-series analysis: A comprehensive introduction for social scientists. Cambridge,UK: Cambridge University Press. FYI
  
  
  
• McCleary, R., & Hay, R.A, Jr. (1980). Applied time series analysis for the social sciences.Beverly Hills, CA: Sage. REC

General Psychometrics

• Crocker, L. & Algina, J. (1986). Introduction to classical and modern test theory. New York : Holt, Rinehart, and Winston. REQ.
  
  
  
• Gulliksen,H.(1950).Theory of mental tests.New York: John Wiley & Sons. REC.
  
  
  
• Linn, R. L.(1989).Educational measurement (3ed ed.).  New York: Macmillian. FYI
  
  
  
• Lord, F. M.,& Novick, M. R.(1968).Statistical theory of mental test scores.  Reading, MA: Addison-Wesley. REQ.
  
  
  
• McDonald, R.P. (1999). Test theory: A unified treatment. Mahwah, NJ: L. Erlbaum Associates. REQ.
  
  
  
• Cronbach, L.J., & Meehl, P. E.  (1955).  Construct validity in psychological tests. Psychological Bulletin, 52, 281-302. REQ.
  
  
  
• Campbell, D.T., & Fiske, D. W.(1959).Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56, 81-105. REQ
  
  
  
• Cronbach, L.J.(1989).Construct validation after thirty years. In R. L. Linn (Ed.), Intelligence: Measurement, theory, and public policy (pp. 147-171). Urbana: University of Illinois Press.REC
  
  
  
• Embretson, S.E.(1983).Construct validity:Construct representation versus nomothetic span.  Psychological Bulletin, 93, 179-197. REC.
  
  
  
• Grove, W. M.,& Meehl, P. E.(1996). Comparative efficiency of formal (mechanical, algorithmic) and informal (subjective, impressionistic) prediction procedures: The clinical/statistical controversy. Psychology, Public Policy, and Law, 2, 293-323. REQ
  
  
  
• Loevinger, J.  (1957).  Objective tests as instruments of psychological theory.  Psychological Reports, 3, 635-694. REQ
  
  
  
• Mook, D.G. (1983). In defense of external invalidity. American Psychologist, 38, 379-387. REC.
  
  
  
• Schmidt, F. L., & Hunter, J. E.(1997). Measurement error in psychological research: Lessons from 26 research scenarios.Psychological Methods, 1, 199-223.
  
  
  
• Schmidt, F. L., & Hunter, J. E. (1998). The validity and utility of selection methods in personnel psychology:Practical and theoretical implications of 85 years of research findings.Psychological Bulletin, 124, 262-274. REC.
  

Individual Differences

• Cronbach, L. J.(1957). The two disciplines of scientific psychology. American Psychologist, 12, 671-684. REQ
  
  
  
• Dunnette, M. D.(1976). Handbook of industrial and organizational psychology (1st ed.). Chicago: Rand McNally. FYI
  
  
  
• Dunnette, M. D., & L. M. Hough(1990, 1991, 1992, 1993). Handbook of industrial and organizational psychology (2nd ed., vols. 1-4).FYI
  
  
  
• Lubinski, D.(2000a).Scientific and social significance of assessing individual differences:Sinking shafts at a few critical points.”Annual Review of Psychology, 51, 405-444. REQ
  
  
  
• Thorndike, R.M., & Lohman, D. F. (1990).A century of ability testing. Chicago: Riverside. REC.
  
  
  
• Plomin, R.(1990). Nature and nurture: An introduction to human behavioral genetics. Brooks/Cole: Pacific Grove, CA.
  
  
  
• Underwood, B. J.(1975).Individual differences as a crucible in theory construction. American Psychologist, 30, 128-134. REQ
  
  
  
• Wiggins, J. S.(1973).Personality and prediction: Principles of personality assessment.Reading, Mass: Addison-Wesley. REC
  

Program Evaluation:

Major Texts

• Rossi, P.H. , Freeman, H.E. & Lipsey, M.W. (1999). Evaluation: A systematic approach (6^th Edition). Newbury Park, CA: Sage Publications. REQ
  
  
  
• Hedrick, T.E.,Bickman, L., & Rog. D. (1997). Planning applied social research. Newbury Park, CA: Sage Publications. REC
  
  
  
• Boruch, R.F.(1997). Randomized experiments for planning and evaluation: A practical guide. Thousand Oaks, CA: Sage Publications. REC
  
• Shadish, W.R., Cook, T.D., & Leviton, L.C. (1991). Foundations of program evaluation: Theories of Practice. Newbury Park, CA: Sage Publications. FYI
  
  
  
• Cronbach, L.J. (1982). Designing evaluations of educational and social programs. Newbury Park, CA: Sage Publications. REQ
  
  
  
• Yin, R.K. (1984).Case study research: design and methods. Newbury Park, CA: Sage Publications. FYI
  
  
  
• Cook, T.D. & Campbell, D.T. (1979). Quasi-experimentation: Design and analysis issues for field settings. Chicago, Rand McNally College Publishing Company. REQ
  
  
  
• Weiss, C. H.(1972). Evaluation research: Methods of assessing program effectiveness. Englewood Cliffs, NJ: Prentice Hall. FYI
  
  
  
• Campbell, D.T., Stanley, J.C. (1966). Experimental and quasi-experimental designs for research. Chicago: Rand McNally College Publishing Company. REQ
  
  
  
• Webb, E.J.,Campbell, D.T., Schwartz, R.D., & Sechrest, L. (1966). Unobtrusive measures: Nonreactive research in the social sciences. Chicago: Rand McNally College Publishing Company. REC

Review Articles

• Lipsey, M. W., & Cordray, D.S. (2000). Evaluation methods for social interventions. Annual Review of Psychology, 51, 345-376. REQ
  
  
  
  
  
• Sechrest, L., & Figueredo, A.J. (1993). Program evaluation. Annual Review of Psychology, 44, 645-671. FYI
  
  
  
• Cook, T.D., & Shadish, W.R. (1994). Social experiments: Some developments over the past fifteen years. Annual Review of Psychology, 45, 545-580. FYI
  
  
  
• Smith, M.F.(1994). Evaluation: Review of past, preview of the future. Evaluation Practice, 15(3), 215-227. FYI
  

Theory-Driven Evaluation

• Weiss, C.H. (1997). How can theory-based evaluation make greater headway? Evaluation Review, 21(4), 501-524. REC
  
  
  
• Scriven, M. (1998). Minimalist theory: The least theory that practice requires. The American Journal of evaluation, 19(1), 57-72. REC
  
  
  
• Johnson, R.B. (1998). Toward a theoretical model of evaluation utilization. Evaluation and Program Planning, 21(1), 93-110. FYI
  
  
  
• Calsyn, R.J., Roades, L.A., & Klinkenberg, W.D. (1998). Using theory to design needs assessment studies of the elderly. Evaluation and Program Planning, 21(3), 277-286. FYI
  
  
  
• Chen, H.(1990).Theory-driven evaluation. Newbury Park, CA: Sage Publications. REC
  

Meta-analysis and Research Synthesis

• Cooper, H., & Hedges, L.V. (Eds.) (1994). The handbook of research synthesis. New York: Russell Sage Foundation. REC
  
  
  
• Lipsey, M.W., & Wilson, D.B. (2000). Meta-analysis: A practical guide. Thousand Oaks, CA: Sage Publications. REC
  
  
  
• Cordray, D.S., & Fischer, R.L. (1995). Evaluation synthesis. In J. Wholey, H. Hatry, K. Newcomer (Eds.), Handbook of practical program evaluation. San Francisco, CA: Jossey-Bass. FYI
  
  
  
• Cook, T.D., Cooper, H.M., Cordray, D.S., Hartman, H., Hedges, L.V., Lewis, T., Light, R.J., & Mosteller, F.M. (Eds.) (1992). Meta-analysis for explanation: A casebook. New York: Russell Sage Foundation. REC

Secondary Analysis

• Duncan, G.J. (1991). Made in heaven: Secondary data analysis and interdisciplinary collaborators. Developmental Psychology, 27(6), 949-951. FYI
  
  
  
• McCall, R.B. & Appelbaum, M.I. (1991). Some issues of conducting secondary analyses. Developmental Psychology, 27(6), 911-917. FYI
  
  
  
• Cherlin, Andrew (1991). On analyzing other people�s data. Developmental Psychology, 27(6), 946-948. FYI

Survey Research and Questionnaire Construction

• Cochran, W.G.(1977). Sampling techniques (3^rd Edition). New York: John Wiley and Sons. REC
  
  
  
• Groves, R. M.(1989).An introduction to survey error. (Chapter 1)In R. M. Groves, Survey errors and survey costs.New York, NY: John Wiley & Sons.(pp. 1-48). REQ
  
  
  
• Bradburn, N. M., & Sudman, S.(1991).The current status of questionnaire research.(Chapter 2)In Biemer, P. P., Groves, R. M., Lyberg, L. E., Mathiowetz, N. A., & Sudman, S., Measurement errors in surveys. New York, NY: John Wiley & Sons.(pp. 29-40). FYI
  
  
  
• Lessler, J. T., & Kalsbeek, W. D.(1992).Nonresponse: Dealing with the problem. (Chapter In Lessler, J. T., & Kalsbeek, W. D., Nonsampling error in surveys.New York, NY: John Wiley & Sons.(pp. 161-234). REQ
  
  
  
• Sudman, S., Bradburn, N. M., & Schwarz, S.(1996).Methods for determining cognitive processes and questionnaire problems.(Chapter 2)In S. Sudman, N. M., Bradburn, & S. Schwarz, Thinking about answers: The application of cognitive processes to survey methodology.San Francisco, CA: Jossey-Bass.(pp. 15-54). REC
  

  Survey errors and survey costs.New York, NY: John Wiley & Sons. (pp. 357-406). REC
  

  
  
• Dillman, D. A.(1999). Internet and interactive voice response surveys (Chapter 10) In D. A. Dillman, Mail and internet surveys: The tailored design method. New York, NY: John Wiley & Sons.(pp. 352-412). FYI
  
  
  
• Jobe, J. B.,& Mingay, D. J.(1991).Cognition and survey measurement: History and overview.Applied Cognitive Psychology, 5, 15-192 REC
  

Selected Technical Issues in Evaluation

Factors Affecting Statistical Power:

• Boruch, R.F.,& Gomez, H. (1977). Sensitivity, bias and theory in impact evaluation. Professional Psychology. 11,411-434. REQ
  
  
  
• Lipsey, M.W.,(1990). Design sensitivity: Statistical power for experimental research. Newbury Park, CA: Sage Publications. REQ
  
  
  
• Brekke. J.S. & Test, M.A. (1987). A model for measuring implementation of Community Support Programs: Results from three sites. Community Mental Health Journal, 28, 281-299. FYI
  
  
  
• Orwin, R.G., Sonnefeld, L.J., Cordray, D.S., Pion, G.M., & Perl, H.I. (1998). Constructing quantitative implementation scales from categorical service data: Examples from a mult-site evaluation. Evaluation Review, 22(2), 245-288. REC
  
  
  
• Smith, B., & Sechrest, L. (1991). Treatment of aptitude x treatment interactions. Journal of Consulting and Clinical Psychology, 59, 233-244. FYI
  
  
  
• Analysis Issues:
  
  
  
• Little, R.J.,& Yau, L.H.Y. (1998). Statistical techniques for analyzing data from prevention trials: Treatment of no-shows using Rubin�s Causal Model. Psychological Methods, 3(2), 147-159. REC
  
  
  
• Rubin, D.B. and Thomas, N. (2000) Combining propensity score matching with additional adjustments for prognostic covariates. Journal of the American Statistical Association, 95, 573-585. REQ
  
  
  
• Winship, C. & Mare, R.D. (1992). Models for sample selection bias. Annual Review of Sociology, 18, 327-350. FYI
  
  
  
• Winship, C., & Morgan, S.L. (1999). The estimation of causal effects from observational data. Annual Review of Sociology, 25, 659-707. REQ
  
  
  
• Heckman, J.J. (1979). Sample selection bias as a specification error. Econometrica, 47, 153-161. REC
  
  
  
• Murray D.M., Moskowitz, J.M., & Dent, C.W. (1996). Design and analysis issues in community-based drug abuse prevention. American Behavioral Scientist, 39, 853-867. REC
  
  
  
• Heinsman, D.T., & Shadish, W.R. (1996). Assignment methods in experimentation: When do nonrandomized experiments approximate answers from randomized experiments? Psychological Methods, 1, 154-169. FYI
  
  
  
• Alternative Methods for Evaluation:
  
• Cartwight, W.S.(1998). Cost-benefit and cost-effectiveness analysis of drug abuse treatment services. Evaluation Review, 22(5), 609-636. FYI
  
• Scriven, M. (1997). Empowerment evaluation examined. Evaluation Practice, 18(3), 165-175. FYI
  
  
  
• Other Relevant Sources:
  
• AEA Guiding Principles for Evaluators REC
  

Recommended readings not currently classified:

• Hsu, L. M. (1992). Random sampling, randomization, and equivalence of contrasted groups in psychotherapy outcome research. In A.E. Kazdin (Ed.), Methodological issues and strategies in clinical research. (pp. 91-105). Washington, D.C.: American Psychological Association. (reprinted from Journal of Consulting and Clinical Psychology, 1989, 57, 131-137).
  
  
  
• Cohen, P., & Cohen, J. (1984). The clinician’s illusion. Archives of General Psychiatry, 41, 1178-1182.
  
  
  
• Sackett, D.L. (1979). Bias in analytic research. Journal of Chronic Diseases, 32, 51-63.
  
  
  
• Chapman, L.J., & Chapman, J.P. (1978). The measurement of differential deficit. Journal of Psychiatric Research, 14, 303-311.
  
  
  
• Willett, J.B., & Singer, J.D. (1993). Investigating onset, cessation, relapse, and recovery: Why you should, and how you can, use discrete-time survival analysis to examine event occurrence. Journal of Consulting and Clinical Psychology, 61, 952-965.
  
  
  
• Dawes, R.M., & Corrigan, B. (1974). Linear models in decision making. Psychological Bulletin, 81, 95-106.
  
  
  
• Westfall,  P.H., & Young, S.S. (1993). Resampling-based multiple testing. New York: John Wiley.
  
  
  
• Rogosa, D.R., Brandt, D., & Zimkowski, M. (1982). A growth curve approach to the measurement of change. Psychological Bulletin, 90, 726-748.
  
  
  
• Duncan, O.D. (1969). Some linear models  for two-wave, two-variable panel analysis. Psychological Bulletin, 72, 177-182.