Future Courses

These are courses that I'd one day like to teach. For some of the courses, I've put a little thought into what I'd like to cover and occasionally, those readings appear below. I'm also open to teaching anything I've taught before or developing new applied statistical courses. All material below is in development and readings may change.

• COURSE: Factor Analysis

  • On What Kind of Data is Good to Factor Analyze

    1. Curran (1994) Dissertation on Non-Normal Data

    2. West, Curran, and Finch (1995) on Non-Normal Data

    3. Curran, West, and Finch (1999) on Non-Normal Data

• • General Overview

    • Fabrigar, Wegener, MacCallum, & Strahan (1999) on exploratory factor analysis

    • Bryant & Yarnold (1995) on Principal Componets Analysis, Exploratory Factor Analysis, and Confirmatory Factor Analysis

    • Kahn (2006) on factor analysis

• • Principal Components Analysis (PCA) - What it is and why it's not the same as factor analysis, even if it sometimes gets you similar results

    • Hotelling (1933)

    • Keith Widaman presentation on PCA

    • Data for class example PCA

    • Syntax for class example PCA

    • Output for class example PCA

• • Deciding Numbers of Components

    • Parallel Analysis Program

    • O'Conner's (2000) article about the Parallel Analysis Program

    • Restructured PANAS Data Set

    • Articles on Example

      • Watson, Clark, & Tellegen (1988)

      • PANAS-X Manual

    • Syntax to run parallel analysis program on PANAS data

• • Extraction Methods

    • Swain (1975) on factor extractions

    • Non-Iterative Extractions for EFA

      • Albert (1944)

      • Ihara & Kano (1986)

      • Kano (1990a)

      • Kano (1990b)

      • Kano (1991)

      • Cudek (1991)

      • Browne & Tateneni (1997)

• • Exploratory Factor Analysis (EFA)

    • Notes on Eigenvalues and Eigenvectors

    • Factor Analysis Notes

    • Spearman (1904)

    • SPSS Syntax for PANAS EFA

    • SPSS Output from PANAS EFA

    • Browne's Comprehensive Exploratory Factor Analysis (CEFA) Program

    • CEFA Manual

    • Lee (2010) reviewing the CEFA program

    • Input file for PANAS data for CEFA

    • Command file for PANAS for CEFA (varimax rotation)

    • Output file for PANAS from CEFA

• • Modes of Data Analysis

    • Cattell Chapter on The Data Box

    • Molenaar (1987) on dynamic factor analysis

    • Ferrer & Nesselroade (2003) example on extending P-technique into dynamic factor analysis

    • Russell, Jones, & Miller (2007) on P-technique in psychotherapy process research

• • Standard Errors for Factor Loadings in EFA

    • Rippee (1953)

    • Cliff & Hamburger (1967)

    • Cliff & Pennell (1967)

    • Pennell (1968)

    • Jennrich & Sampson (1966)

    • Pennell (1972)

    • Jennrich (1973)

    • Jennrich & Thayer (1973)

    • Jennrich (1974)

    • Clarkson (1979)

    • Jennrich & Clarkson (1980)

    • Chatterjee (1984)

    • Cudek & O'Dell (1994)

    • Tateneni (1998) dissertation on standard errors in EFA

    • Jamshidian & Jennrich (2002)

    • Zhang, Preacher, & Luo (2010)

• • Rotations

    • Crawford and Ferguson (1970) on factor rotations

    • Browne (2001) on rotation methods

    • SPSS PANAS Data

    • SPSS Syntax for varimax and directly oblimin with kappa = 0 (i.e., quartimax) rotation

    • SPSS Output for rotated factor solutions

    • CEFA Input File

    • CEFA Command File for Crawford-Ferguson (CF) Varimax Rotation

    • CEFA Output File for CF Orthogonal Varimax Rotation

    • CEFA Command File for Targeted Factor Analysis

    • CEFA Output File for Targeted Factor Analysis

    • CEFA Command File for Oblique CF Quartimax

    • CEFA Ouput File for Oblique CF Quartimax Rotation

    • CEFA Command File for Yates's Geomin Rotation

    • CEFA Output File for Yate's Geomin Rotation

• • Confirmatory Factor Analysis (CFA)

    • Structural Equation Modeling Notes

    • Joreskog (1969)

    • Link to the student version of LISREL

    • PANAS Data as .dat file for input

    • LISREL syntax for input - 2 correlated factors

    • LISREL output - 2 correlated factors

    • LISREL model - 2 correlated factors

• • Multigroup CFA

    • Gregorich, S. E. (2006). Do self-report instruments allow meaningful comparisons across diverse population groups? Testing measurement invariance using the confirmatory factor analysis framework. Medical care, 44(11 Suppl 3), S78-S94. (pdf)

• Multilevel Factor Analysis

  • Reise, S. P., Ventura, J., Nuechterlein, K. H., & Kim, K. H. (2005). An illustration of multilevel factor analysis. Journal of Personality Assessment, 84(2), 126-136. (pdf)

• COURSE: Item Response Theory

  • 1. Engelhard, G. E., Jr. (1997). Introduction to the section on measurement.Educational Measurement: Issues and Practice, 16(4), 5-7.

    2. Traub, R. E. (1997). Classical test theory in historical perspective. Educational Measurement: Issues and Practice, 16(4), 8-14.

    3. Brennan, R. (1997). A perspective on the history of generalizability theory. Educational Measurement: Issues and Practice, 16(4), 14-20.

    4. Bock, R. D. (1997). A brief history of item response theory. Educational Measurement: Issues and Practice, 16(4), 21-32.

    5. Wright, B. D (1997). A history of social science measurement. Educational Measurement: Issues and Practice, 16(4), 33-45.

    6. Lu, I. R. R., Thomas, D. R., & Zumbo, B. D. (2005). Embedding IRT in structural equation models: A comparison with regression based on IRT scores. Structural Equation Modeling, 12, 263-277.

    7. Edwards, M. C. (2009). An introduction to item response theory using the need for cognition scale. Social and Personality Psychology Compass 3/4, 507-529. (supplemental files)

    8. Loken, E. & Rulison, K. L. (2010). Estimation of a four-parameter item response theory model. British Journal of Mathematical and Statistical Psychology, 63,509-525.

• COURSE: Meta-Science

Clinical Utility vs. Scientific Accuracy

• Key Readings

  • First, M.B., Pincus, H.A., Levine, J.B., Williams, J.B.W., Ustun, B., & Peele, R. (2004). Clinical utility as a criterion for revising psychiatric diagnoses. American Journal of Psychiatry, 161, 946–954. (pdf)

  • Shedler, J., & Westen, D. (2004). Dimensions of personality pathology: An alternative to the Five Factor Model. American Journal of Psychiatry, 161,1743-1754. (pdf).

  • Widiger, T.A., & Trull, T.J. A simplistic understanding of the five-factor model. The American Journal of Psychiatry 162(8), 1550-1551. (pdf)

  • Westen, D., Waller, N., Shedler, J., & Blagov, P. (in press). Dimensions of personality and personality pathology: Factor structure of the Shedler-Westen Assessment Procedure-II (SWAP-II), Journal of Personality Disorders.

  • Shedler, J., Beck, A., Fonagy, P., Gabbard, G. O., Gunderson, O., Kernberg, O., Michels, R., & Westen, D. (2010). Personality disorders in DSM-5. American Journal of Psychiatry, 167(9), 1026-1028. (pdf)

  • Skodol, A. E., (2011). Revision of the personality disorder model for DSM-5. American Journal of Psychiatry, 168(1), 97. (pdf)

  • Shedler, J., Beck, A.T., Fonagy, P., Gabbard, G. O., Kernberg, O., Michels, R., & Westen, D. (2011). Response to the Skodol letter. American Journal of Psychiatry, 168(1), 97-98. (pdf)

• Additional Resources

  • Glover, NG, Crego, C, Widiger, T.A. (2012). The clinical utility of the Five Factor Model of personality disorder. Personality Disorders, 3(2), 176-84. (pdf)

  • Gore, W.L., & Widiger, T.A. (2013). The DSM-5 dimensional trait model and five-factor models of general personality. Journal of Abnormal Psychology 122(3), 816-21. (pdf)

  • Mullins-Sweatt, S.N., & Widiger, T.A. (2011). Clinician's judgments of the utility of the DSM-IV and five-factor models for personality disordered patients. Journal of Personality Disorders, 25(4). 463-77. (pdf)

  • Shedler, J., & Westen, D. (2004). Refining personality disorder diagnoses:Integrating science and practice. American Journal of Psychiatry, 161, 1-16. (pdf)

  • Skodol, A. E. (2012). Personality disorders in DSM-5. Annual Review of Clinical Psychology, 8, 317-344. (pdf).

  • Spitzer, R.L., First, M.B., Shedler, J.S., Westen, D., & Skodol, A. (2008). Clinical utility of five dimensional systems for personality diagnosis: A consumer preference study. Journal of Nervous and Mental Disease, 196, 356-374. (pdf)

  • Trull, T. J. (2012). The Five Factor Model of Personality Disorder and DSM-5. Journal of Personality, 80(6), 1697-1720. (pdf).

  • Westen, D. (2006). Drizzling on the 5+3 factor parade: A response to Trull. In T. Widiger & E. Simonson (Eds.), Dimensional models of personality disorder: Refining the research agenda for DSM-V (pp. 189-194). Washington, D.C.: American Psychiatric Press. (pdf)

  • Westen, D., Shedler, J., Bradley, B., & DeFife, J.A. (2012). An empirically derived taxonomy for personality diagnosis: Bridging science and practice in conceptualizing personality. American Journal of Psychiatry, 169(3), 273-284. (pdf)

  • Westen, D., & Shedler, J. (1999). Revising and assessing Axis II, Part 1:Developing a clinically and empirically valid assessment method. American Journal of Psychiatry, 156, 258-272. (pdf)

  • Westen, D., & Shedler, J. (1999). Revising and assessing Axis II, Part 2: Toward an empirically based and clinically useful classification of personality disorders.American Journal of Psychiatry, 156, 273-285. (pdf)

  • Widiger, T.A. & Costa P.T., Jr (2012). Integrating normal and abnormal personality structure: the Five-Factor Model. Journal of Personality, 80(6), 1471-506. (pdf)

Idiographic Methodology

• Nesselroade

• Molenaar

• Ram

• Lamielle

• Ioannidis & Garber (2011) (pdf)

Null-Hypothesis Significance Testing

• Cohen, J. (1994). The earth is round (p < .05). American Psychologist, 49, 997-1003. (pdf)

• Lambden, C. (2012). Significance tests as sorcery: Science is empirical−−significance tests are not. Theory & Psychology, 22, 67-90 (pdf)

• Schmidt, F., L, & Hunter, J. E. (1997). Eight common but false objections to the discontinuation of significance testing in the analysis of research data. In L. L. Harlow, S. A. Mulaik & J. H. Steiger (Eds.), What if there were no significance tests? (pp. 37-64). London: Lawrence Erlbaum Associates. (pdf)

• P-hacking (pdf)

• COURSE: Regression

• Matrix Formulations of Multiple Regression

  • Matrix Inversion Notes

  • Inversion and Regression Syntax

  • Inversion and Regression Output

  • Data

• Moderation and Simple Slopes

  • Lecture

  • Data Used in Lecture

  • Syntax Used in Lecture

  • Output for Lecture

  • SAS Syntax to do the same thing as SPSS

  • Holmbeck, 2002

  • Link to Preacher Moderation Materials

• Mediation

  • Lecture -- Conceptual Portion

  • Lecture -- SPSS Portion

  • Data for Example in Lecture

  • Syntax for mediation example in class

  • Baron & Kenny, 1986

  • Syntax for bootsrapped regression in SPSS using nonlinear regression

  • Moderated Mediation Syntax from Class

  • Output for class

  • Link to Preacher and Hayes Mediation Script and Material

  • Link to Preacher and Hayes Moderated Mediation Material

  • Shrout and Bolger (2002) on why we should bootstrap mediation

  • Fritz & and MacKinnon (2007) on required sample size to detect mediation

• Dummy Coding, Moderation with Continuous and Categorical, and Quadratic/Polynomial Effects

  • Lecture

  • Vitamin C Data for Class Example

  • Syntax for Class

  • Output for Class

  • Cohen, 1968

• Logistic Regression

  • Titanic Data for Class

  • Chapter on Titanic Data

  • Syntax for Class

  • Output for Class

• Generalized Linear Models [GzLM]

  • Lecture

  • Gill, 2001

  • Data for Class

  • Syntax for Class

  • Output for Class

  • Walk through of output with additional notes on GzLM

  • Nelder & Wedderburn (1972)

• COURSE: Test Theory