Analysis of Clinical Data From a Cognitive Diagnosis Modeling Framework

References

• American Psychiatric Association. (2000). Diagnostic and statistical manual of mental disorders, (text revision). Washington, DC: Author.
   Google Scholar
• American Psychiatric Association. (2013). Diagnostic and statistical manual of mental disorders (5th ed.). Arlington, VA: American Psychiatric Publishing.
   Google Scholar
• Brown, T. A., Campbell, L. A., Lehman, C. L., Grisham, J. R., & Mancill, R. B. (2001). Current and lifetime comorbidity of the DSM-IV anxiety and mood disorders in a large clinical sample. Journal of Abnormal Psychology, 110, 585–599.
   Google Scholar
• Budescu, D. V., & Rodgers, J. L. (1981). Corrections for spurious influences on correlations between MMPI scales. Multivariate Behavioral Research, 16, 483–497.
   Google Scholar
• Buse, A. (1982). The likelihood ratio, Wald, and Lagrange multiplier tests: An expository note. American Statistician, 36, 153–157.
   Google Scholar
• Butcher, J. N., Dahlstrom, W. G., Graham, J. R., Tellegen, A., & Kaemmer, B. (2001). MMPI-2: Manual for administration and scoring (Rev. ed.). Minneapolis: University of Minnesota Press.
   Google Scholar
• Camara, W. J., Nathan, J. S., & Puente, A. E. (2000). Psychological test usage implications in professional psychology. Professional Psychology: Research and Practice, 31, 141–154.
   Google Scholar
• Cohen, A., & Farley, F. H. (1979). The common item in measurement: Effect on structure. Multivariate Behavioral Research, 14, 91–108.
   Google Scholar
• Dahl, A. A. (1986). Some aspects of the DSM–III personality disorders illustrated by a consecutive sample of hospitalised respondents. Acta Psychiatrica Scandinavica, 73(Suppl. 328), 61–67.
   Google Scholar
• de la Torre, J. (2008). An empirically-based method of Q-matrix validation for the DINA model: Development and applications. Journal of Educational Measurement, 45, 343–362.
   Google Scholar
• de la Torre, J. (2009a). A cognitive diagnosis model for cognitively based multiple-choice options. Applied Psychological Measurement, 33, 163–183.
   Google Scholar
• de la Torre, J. (2009b). DINA model and parameter estimation: A didactic. Journal of Educational and Behavioral Statistics, 34, 115–130.
   Google Scholar
• de la Torre, J. (2011). The generalized DINA model framework. Psychometrika, 76, 179–199.
   Google Scholar
• de la Torre, J., & Chiu, C. Y. (2016). A general method of empirical Q-Matrix validation. Psychometrika, 81, 253–273.
   Google Scholar
• de la Torre, J., & Lee, Y. S. (2013). Evaluating the Wald test for item-level comparison of saturated and reduced models in cognitive diagnosis. Journal of Educational Measurement, 50, 355–373.
   Google Scholar
• Dimitrov, D. M. (2007). Least squares distance method of cognitive validation and analysis for binary items using their item response theory parameters. Applied Psychological Measurement, 31, 367–387.
   Google Scholar
• Dimitrov, D. M., & Atanasov, D. V. (2012). Conjunctive and disjunctive extensions of the least squares distance model of cognitive diagnosis. Educational and Psychological Measurement, 72, 120–138.
   Google Scholar
• Dolan-Sewell, R. T., Krueger, R. F., & Shea, M. T. (2001). Co-occurrence with syndrome disorders. In W. J. Livesley (Ed.), Handbook of personality disorders (pp. 84–104). New York, NY: Guilford Press.
   Google Scholar
• Doornik, J. A. (2003). Object-Oriented Matrix Programming using Ox (Version 3.1) [Computer software]. London, England: Timberlake Consultants Press.
   Google Scholar
• Duijsens, I. J., Eurelings-Bontekoe E. H. M., & Diekstra, R. F. W. (1996). VKP: Questionnaire on personality traits (ICD-10/DSM-IV Manual Research Version). Geneva, Switzerland: World Health Organization.
   Google Scholar
• Eaton, N. R., Krueger, R. F., Markon, K. E., Keyes, K. M., Skodol, A. E., Wall, M., … Grant, B. F. (2013). The structure and predictive validity of the internalizing disorders. Journal of Abnormal Psychology, 122, 86–92.
   Google Scholar
• Embretson, S. E. (1984). A general latent trait model for response processes. Psychometrika, 49, 175–186.
   Google Scholar
• Gibeau, P., & Choca, J. (2005). The diagnostic efficiency of the MCMI-III in the detection of Axis I disorders. In R. J. Craig (Ed.), New directions on interpreting the Millon Clinical Multiaxial Inventory-III (MCMI-III) (pp. 272–283). Hoboken, NJ: Wiley.
   Google Scholar
• Haertel, E. H. (1989). Using restricted latent class models to map the skill structure of achievement items. Journal of Educational Measurement, 26, 301–323.
   Google Scholar
• Henson, R., Templin, J., & Willse, J. (2009). Defining a family of cognitive diagnosis models using log-linear models with latent variables. Psychometrika, 74, 191–210.
   Google Scholar
• Hsu, L. (1992). Correcting correlations of personality scales for spurious effects of shared items. Multivariate Behavioral Research, 27, 31–41.
   Google Scholar
• Jaeger, J., Tatsuoka, C., Berns, S. & Varadi, F. (2006). Distinguishing neurocognitive functions using partially ordered classification models. Schizophrenia Bulletin, 32, 679–691.
   Google Scholar
• Junker, B. W., & Sijtsma, K. (2001). Cognitive assessment models with few assumptions, and connections with nonparametric item response theory. Applied Psychological Measurement, 25, 258–272.
   Google Scholar
• Kelly, T. L. (1927). The interpretation of educational measurement. New York, NY: World Book.
   Google Scholar
• Krueger, R. F., & Eaton, N. R. (2010). Personality traits and the classification of mental disorders: Toward a more complete integration in DSM-5 and an empirical model of psychopathology. Personality Disorders: Theory, Research, and Treatment, 1, 97–118.
   Google Scholar
• Lord, F. M., & Novick, M. R. (1968). Statistical theories of mental test scores. Reading, MA: Addison-Welsley.
   Google Scholar
• Meehl, P. E., & Rosen, A. (1955). Antecedent probability and the efficiency of psychometric signs, patterns, or cutting scores. Psychological Bulletin, 52, 194–216.
   Google Scholar
• Millon, T. (1994). Manual for the MCMI-III. Minneapolis, MN: National Computer Systems.
   Google Scholar
• Millon, T., Millon, C., Davis, R., & Grossman, S. (2009). MCMI-III Manual (4th ed.). Minneapolis, MN: Pearson Assessments.
   Google Scholar
• Modestin, J. (1987). Quality of interpersonal relationships: The most characteristic DSM-III BPD criterion. Comprehensive Psychiatry, 28, 397–342.
   Google Scholar
• Nurnberg, H. G., Hurt, S. W., Feldman, A., & Suth, R. (1987). Efficient diagnosis of borderline personality disorder. Journal of Personality Disorders, 1, 307–315.
   Google Scholar
• Nurnberg, H. G., Raskin, M., Levine, P. E., Pollack, S., Siegel, O., & Prince, R. (1991). Hierarchy of DSM-III-R criteria efficiency for the diagnosis of borderline personality disorder. Journal of Personality Disorders, 5, 211–224.
   Google Scholar
• Pearson, K. (1897). Mathematical contributions to the theory of evolution. On a form of spurious correlation which may arise when indices are used in the measurement of organs. Proceedings of the Royal Society of London, 60, 489–502.
   Google Scholar
• Rojas, G., de la Torre, J., & Olea, J. (2012, April). Choosing between general and specific cognitive diagnosis models when the sample size is small. Paper presented at the Annual Meeting of the National Council on Measurement in Education, Vancouver, British Columbia, Canada.
   Google Scholar
• Rossi, G., Elklit, A., & Simonsen, E. (2010). Empirical evidence for a four factor framework of personality disorder organization: Multigroup confirmatory factor analysis of the Millon Clinical Multiaxial Inventory–III personality disorders scales across Belgian and Danish data samples. Journal of Personality Disorders, 24, 128–150.
   Google Scholar
• Rossi, G., & Sloore, H. (2005). International uses of the MCMI-III: Does interpretation change? In R. J. Craig (Ed.), New directions on interpreting the Millon Clinical Multiaxial Inventory-III (MCMI-III) (pp. 144–161). Hoboken, NJ: Wiley.
   Google Scholar
• Rossi, G., Sloore, H., & Derksen, J. (2008). The adaptation of the MCMI-III in two non-English-speaking countries: State of the art of the Dutch language version. In T. Millon & C. Bloom (Eds.), The Millon inventories: A practitioner's guide to personalized clinical assessment (2nd ed., pp. 369–386). New York, NY: Guilford Press.
   Google Scholar
• Rossi, G., van der Ark, L. A., & Sloore, H. (2007). Factor analysis of the Dutch-language version of the MCMI-III. Journal of Personality Assessment, 88, 144–157.
   Google Scholar
• Rupp, A. A., & Templin, J. L. (2008). Unique characteristics of diagnostic classification models: A comprehensive review of the current state-of-the-art. Measurement, 6, 219–262.
   Google Scholar
• Rupp, A. A., Templin, J. L., & Henson, R. A. (2010). Diagnostic measurement: Theory, methods, and applications. New York, NY: Guilford Press.
   Google Scholar
• Saulsman, L. M. (2011). Depression, anxiety, and the MCMI-III: Construct validity and diagnostic efficiency. Journal of Personality Assessment, 93, 76–83.
   Google Scholar
• Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., Amorim, P., Janavs, J., Weiller, E., ... Dunbar, G. C. (1998). The Mini-International Neuropsychiatric Interview (M.I.N.I.): The development and validation of a structured psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry, 59, 522–533.
   Google Scholar
• Tatsuoka, K. K. (1983). Rule space: An approach for dealing with misconceptions based on item response theory. Journal of Educational Measurement, 20, 345–354.
   Google Scholar
• Tatsuoka, K. K. (1990). Toward an integration of item-response theory and cognitive error diagnosis. In N. Frederiksen, R. Glaser, A. Lesgold, & M. G. Shafto (Eds.), Diagnostic monitoring of skill and knowledge acquisition (pp. 453–488). Hillsdale, NJ: Erlbaum.
   Google Scholar
• Templin, J. L., & Henson, R. A. (2006). Measurement of psychological disorders using cognitive diagnosis models. Psychological Methods, 11, 287–305.
   Google Scholar
• von Davier, M. (2005). A general diagnostic model applied to language testing data (ETS Research Report No. RR-05-16). Princeton, NJ: Educational Testing Service.
   Google Scholar
• Wainer, H., Vevea, J. L., Camacho, F., Reeve, B. B., III, Rosa, K., Nelson, L., … Thissen, D. (2001). Augmented scores: “Borrowing strength” to compute scores based on small numbers of items. In D. Thissen & H. Wainer (Eds.), Test scoring (pp. 343–388). Mahwah, NJ: Erlbaum.
   Google Scholar
• Wetzler, S., & Marlowe, D. B. (1993). The diagnosis and assessment of depression, mania, and psychosis by self-report. Journal of Personality Assessment, 60, 1–31.
   Google Scholar
• Widiger, T. A., Hurt, S., Frances, A., Clarkin, J., & Gilmore, M. (1984). Diagnostic efficiency and DSM-III. Archives of General Psychiatry, 41, 1005–1012.
   Google Scholar