# Publications: Methodology

Aldenderfer, M. and R. Blashfield (1984). Cluster Analysis. Newbury Park, CA, SAGE Publications, Inc.

Arruda, J. E., M. D. Weiler, et al. (1996). “A guide for applying principal-components analysis and confirmatory factor analysis to quantitative electroencephalogram data.” International Journal of Psychophysiology **23**: 63-81.

Atlas, R. and J. Overall (1994). “Comparative evaluation of two superior stopping rules for hierarchical cluster analysis.” Psychometrika **59**: 581-591.

Beaman, J. and J. Vaske (1995). “An ipsative clustering model for analyzing attitudinal data.”Journal of Leisure Research **27**: 168-191.

Bentler, P. M. (1990). “Comparative fit indices in structural models.” Psychological Bulletin**107**: 238-246.

Bullock, H. E. and L. L. Harlow (1994). “Causation issues in structural equation modeling research.” Structural Equation Modeling **1**: 253-267.

Campbell, D. T. and J. C. Stanley (1963). Experimental and Quasi-experimental Designs for Research. Boston, Houghton Mifflin Company.

Cattell, R. B. (1966). “The screen test for the number of factors.” Multivariate Behavioral Research **1**: 245-276.

Cliff, N. (1983). “Some cautions concerning the application of causal modeling methods.”Multivariate Behavioral Research **18**: 115-126.

Cohen, S. and G. M. Williamson (1987). Perceived stress in a probability sample of the United States. Psychology and Health. S. Spacapan and S. Oskamp. Newbury Park, CA, Sage**: **31-67.

Colby, S. M. and W. F. Velicer (?). “A comparison of four alternative procedures for handling missing data in time series analysis.” .

Cronbach, L. J. (1951). “Coefficient alpha and the internal structure of tests.” Psychometrika**16**: 297-334.

Ding, L., W. F. Velicer, et al. (1995). “Effects of estimation methods, number of indicators per factor, and improper solutions on structural equation modeling fit indices.” Structural Equation Modeling **2**(2): 119-144.

Eckes, T. and P. Orlik (1993). “An error variance approach to two-mode hierarchical clustering.” Journal of Classification **10**: 51-74.

Fava, J. L. and W. F. Velicer (1992). “The effects of overextraction on factor and component analysis.” Multivariate Behavioral Research **27**: 387-415.

Fava, J. L. and W. F. Velicer (1992). “An empirical comparison of factor, image component, and scale scores.” Multivariate Behavioral Research **27**: 301-322.

Fava, J. L. and W. F. Velicer (1996). “The effects of underextraction in factor and component analyses.” Educational and Psychological Measurement **56**(6): 907-929.

Fitzgerald, T. E. and J. O. Prochaska (1990). “Nonprogressing profiles in smoking cessation: What keeps people refractory to self-change?” Journal of Substance Abuse **2**: 87-105.

Guadagnoli, E. and W. F. Velicer (1988). “Relation of sample size to the stability of component patterns.” Psychological Bulletin **103**(2): 265-275.

Guadagnoli, E. and W. F. Velicer (1991). “A comparison of pattern matching indices.”Multivariate Behavioral Research **26**: 323-343.

Harrop, J. W. and W. F. Velicer (1985). “A comparison of alternative approaches to the analysis of interrupted time series.” Multivariate Behavioral Research **20**: 27-44.

Harrop, J. W. and W. F. Velicer (1990). “Computer programs for interrupted time series analysis: I. A quantitative evaluation.” Multivariate Behavioral Research **25**(2): 219-231.

Harrop, J. W. and W. F. Velicer (1990). “Computer programs for interrupted time series analysis: II. A quantitative evaluation.” Multivariate Behavioral Research **25**: 233-248.

Horn, J. I. (1965). “A rationale and test for the number of factors in factor analysis.”Psychometrika **30**: 179-185.

Hughes, S., W. Velicer, et al. (1990). The application of cluster analysis to smoking cessation research. American Psychological Association, Boston, MA.

Johnson, S. (1992). “Methodological issues in diabetes research.” Diabetes Care **15**: 1658-1667.

Joreskog, K. G. and Sorbom (1989). LISREL 7: A guide to the program and applications. Chicago, IL, SPSS, Inc.

King, A. C., M. Kiernan, et al. (1997). “Can we identify who will adhere to long-term physical activity? Signal detection methodology as a potential aid to clinical decision making.” Health Psychology **16**: 380-389.

Kraemer, H. C. (1988). “Assessment of 2 x 2 associations: Generalization of signal detection methodology.” The American Statistician **42**: 37-49.

Lang, J. M. and K. J. Rothman (1998). “That confounded p-value.” Epidemiology **9**: 7-8.

Latane, B., A. Nowak, et al. (1994). “Measuring emergent social phenomena: Dynamism, polarization, and clustering as order parameters of social systems.” Behavioral Science **39**: 1-24.

Lautenschlager, G. J. (1989). “A comparison of alternatives to conducting Monte Carlo analyses for determining parallel analysis criteria.” Multivariate Behavioral Research **24**(3): 265-395.

Levesque, D. and R. Gelles (1997). Battering men: Applying the Transtheoretical model to desistance and change. 5th International Family Violence Research Conference, Durham, NH.

Loftus, G. R. (1996). “Psychology will be a much better science when we change the way we analyze data.” Current Directions in Psychological Science **5**: 161-171.

Maddock, J. E., R. G. LaForge, et al. (1997). “Development of a short psychometrically reliable alcohol problem index for college students.” Unpublished manuscript.

Marsh, H. W., J. R. Balla, et al. (1988). “Goodness-of-fit indices in confirmatory factor analysis: The effect of sample size.” Psychological Bulletin **103**: 391-410.

Martin, R. A., W. F. Velicer, et al. (1995). “Latent transition analysis applied to the stages of change for smoking cessation.” Addictive Behaviors **20**: 67-80.

McDonald, R. P. and H. W. Marsh (1990). “Choosing a multivariate model: Noncentrality and goodness of fit.” Psychological Bulletin **107**: 247-255.

Meehl, P. E. (1954). Clinical versus Statistical Prediction: A Theoretical Analysis and Review of the Literature. Minneapolis, MN, University of Minnesota Press.

Milligan, G. W. (1980). “An examination of the effect of six types of error perturbation on fifteen clustering algorithms.” Psychometrika **45**: 325-342.

Milligan, G. W. (1981). “A review of Monte Carlo tests of cluster analysis.” Multivariate Behavioral Research **16**: 379-407.

Milligan, G. W. and M. C. Cooper (1987). “Methodology review: Clustering methods.” Applied Psychological Measurement **11**: 329-354.

Mueller, R. O. (1996). General structural equation modeling. Basic Principles of Structural Equation Modeling. New York, NY, Springer-Verlag New York, Inc.**: **129-178.

Norman, G. (1998). A cluster analytic test of the Transtheoretical model applied to exercise behavior. Psychology. Kingston, RI, University of Rhode Island.

Norman, G. J., W. F. Velicer, et al. (1998). “Dynamic typology clustering with the stages of change for smoking cessation.” Addictive Behaviors **23**: 139-153.

Overall, J. and K. Magee (1992). “Replication as a rule for determining the number of clusters in hierarchial cluster analysis.” Applied Psychological Measurement **16**: 119-128.

Rodgers, J. and T. Thompson (1992). “Seriation and multidimensional scaling: A data analysis approach to scaling asymmetric proximity matrices.” Applied Psychological Measurement **16**: 105-117.

Rossi, J. S. (1982). Meta-analysis, power analysis and artifactual controversy: The case of spontaneous recovery of verbal associations. Eastern Psychological Association, Baltimore, MD.

Rossi, J. S. (1985). “Tables of effect size for z score tests of differences between proportions and between correlation coefficients.” Educational and Psychological Measurement **45**: 737-743.

Rossi, J. S. (1987). “One-way ANOVA from summary statistics.” Educational and Psychological Measurement **47**: 37-38.

Rossi, J. S., J. O. Prochaska, et al. (1988). A cluster-analytic approach to defining light and heavy smoking. American Psychological Association, Atlanta, GA.

Rossi, J. S. (1988). “ONEWAY: A BASIC program for computing ANOVA from summary statistics.” Behavior Research Methods, Instruments and Computers **20**(3): 347-348.

Rossi, J. (1990). “Statistical power of psychological research: What have we gained in 20 years?” Journal of Consulting and Clinical Psychology **58**: 646-656.

Rossi, J. S. (1990). How often are our statistics wrong? A statistics class exercise. Teaching Psychology: A Handbook. J. Hartley and W. J. McKeachie. Hillsdale, NJ, Lawrence Erlbaum Associates. **14: **98-101.

Rossi, J. S. (?). Inadequate statistical power and artifactual controversy: Some consequences of statistical significance testing ((Draft). What If There Were No Significance Tests? L. Harlow and S. Mulaik. Hillsdale, NJ, Lawrence Erlbaum.

Sharma, S., S. Durasula, et al. (1989). “Some results on the behavior of alternate covariance structure estimation procedures in the presence of non-normal data.” Journal of Marketing Research **26**: 214-221.

SPSS (1990). SPSS Base System (Release 4.0) [Computer software]. Chicago, IL, Author.

Tabachnick, B. G. and L. S. Fidell (1989). Using Multivariate Statistics. New York, NY, Harper Collins Publisher,Inc.

Tucker, L. R. and C. Lewis (1973). “A reliability coefficient for maximum likelihood factor analysis.” Psychometrika **38**: 1-10.

VanBuuren, S. and W. Heiser (1989). “Clustering N objects into K groups under optimal scaling of variables.” Psychometrika **54**: 699-706.

Velicer, W. F. (1974). “An empirical comparison of the stability of factor analysis, principal component analysis, and image analysis.” Educational and Psychological Measurement **34**: 563-572.

Velicer, W. F. (1976). “Determining the number of components from the matrix of partial correlations.” Psychometrika **41**: 321-327.

Velicer, W. F. (1976). “The relation between factor score estimates, image scores and principal component scores.” Educational and Psychological Measurement **36**: 149-159.

Velicer, W. F. (1977). “An empirical comparison of factor, image, and principal component patterns.” Multivariate Behavioral Research **12**: 3-22.

Velicer, W. F. (1978). “Suppressor variables and the semipartial correlation coefficient.”Educational and Psychological Measurement **38**: 953-958.

Velicer, W. F., A. C. Peacock, et al. (1982). “A comparison of component and factor patterns: A Monte Carlo approach.” Multivariate Behavioral Research **17**: 371-388.

Velicer, W. F. (1982). “Prediction and association for N-way classification tables.” Evaluation Review **6**(2): 247-266.

Velicer, W. F. and J. Harrop (1983). “The reliability and accuracy of time series model identification.” Evaluation Review **7**(4): 551-560.

Velicer, W. F., C. C. DiClemente, et al. (1984). “Item format and the structure of the personal orientation inventory.” Applied Psychological Measurement **8**(4): 409-419.

Velicer, W. F. and R. P. McDonald (1984). “Time series analysis without model identification.”Multivariate Behavioral Research **19**: 33-47.

Velicer, W. F., J. M. Govia, et al. (1985). “Item format and the structure of the Buss-Durkee hostility inventory.” Aggressive Behavior **11**: 65-82.

Velicer, W. F. and J. L. Fava (1987). “An evaluation of the effects of variable sampling on component, image, and factor analysis.” Multivariate Behavioral Research **22**: 193-209.

Velicer, W. F., J. L. Fava, et al. (1988). Component Analysis Extended [Computer Program]. Kingston, RI, University of Rhode Island.

Velicer, W. F. and D. N. Jackson (1990). “Component analysis versus common factor analysis: Some issues in selecting an appropriate procedure.” Multivariate Behavioral Research **25**(1): 1-28.

Velicer, W. F. and D. N. Jackson (1990). “Component analysis versus common factor analysis: Some further observations.” Multivariate Behavioral Research **25**(1): 97-114.

Velicer, W. F. and R. P. McDonald (1991). “Cross-sectional time series designs: A general transformation approach.” Multivariate Behavioral Research **26**(2): 247-254.

Velicer, W. F., S. L. Hughes, et al. (1992). “An empirical Typology of subjects within stages of change (Abstract).” International Journal of Psychology **27**: 623.

Velicer, W. F., C. A. Redding, et al. (1992). “A time series investigation of three nicotine regulation models.” Addictive Behaviors **17**: 325-345.

Velicer, W. F. (1994). Time Series Models of Individual Substance Abusers. Advances in Data Analysis for Prevention, Intervention and Research. L. M. Collins and L. A. Seitz. Rockeville, MD, National Institute on Drug Abuse**: **264-299.

Velicer, W. V., R. A. Martin, et al. (1996). “Latent transition analysis for longitudinal data.”Addiction **91**(Suppl.): S197-S209.

Velicer, W. F. (1996). Stability of well-defined structures, CPRC.

Velicer, W. and G. Norman (1996). “Dynamic typologies: Cluster analysis in the temporal domain.” **Submitted for review**.

Velicer, W. F. and B. A. Plummer (1998). “Time series analysis in historiometry: A comment on Simonton.” Journal of Personality **66**(3): 477-486.

Velicer, W. F. and J. L. Fava (1998). “Effects of variable and subject sampling on factor pattern recovery.” Psychological Methods **3**(2): 231-251.

Wallace, R. B. and P. L. Colsher (1990). “Enhancing the utility of quantity-frequency measures of alcohol consumptions with assessments of problem drinking in a population study: A methodologic note.” Annals of Epidemiology **1**: 157-165.

Ward, J. H., Jr. (1963). “Hierarchical grouping to optimize an objective function.” Journal of the American Statistical Association **58**: 236-244.

Yates, F. (1934). “Contingency tables involving small numbers and the chi-square test.”Journal of the Royal Statistical Society (Series B) **1(Suppl.)**: 217-235.

Zwick, W. R. and W. F. Velicer (1982). “Factors influencing four rules for determining the number of components to retain.” Multivariant Behavioral Research **17**: 253-269.

Zwick, W. R. and W. F. Velicer (1986). “A comparison of five rules for determining the number of components to retain.” Psychological Bulletin **99**: 432-442.