## Lawrence T. DeCarlo

### Professional Background

#### Educational Background

#### Scholarly Interests

#### Selected Publications

### publications

DeCarlo, L. T., Kim, Y. K., & Johnson, M. S. (2011). A hierarchical rater model for constructed responses, with a signal detection rater model. Journal of Educational Measurement, 48, 333-356. pdf

DeCarlo, L. T. (2011). Signal detection theory with item effects. Journal of Mathematical Psychology, 55, 229-239. pdf

DeCarlo, L. T. (2011). On the analysis of fraction subtraction data: The DINA model, classification, latent class sizes, and the Q-matrix. Applied Psychological Measurement, 35, 8-26. pdf typo correction

O'Connell, K. A., Shiffman, S., & DeCarlo, L. T. (2011). Does extinction of responses to cigarette cues occur during smoking cessation? Addiction, 106, 410-417.

DeCarlo, L. T. (2010). On the statistical and theoretical basis of signal detection theory and extensions: Unequal variance, random coefficient, and mixture models. Journal of Mathematical Psychology, 54, 304-313. pdf

DeCarlo, L. T. (2008). Studies of a latent-class signal-detection model for constructed response scoring (ETS Research Rep. No. RR-08-63). Princeton NJ: ETS. pdf

DeCarlo, L. T. (2008). Process dissociation and mixture signal detection theory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 1565-1572. pdf

Teghtsoonian, M., Teghtsoonian, R., & DeCarlo, L. T. (2008). The influence of trial-to trial recalibration on sequential effects in cross-modality matching. Psychological Research, 72, 115-122. pdf

DeCarlo, L. T. (2007). The mirror effect and mixture signal detection theory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 18-33. pdf

DeCarlo, L. T. (2006). Sequential effects in successive ratio estimation. Perception & Psychophysics, 68, 861-871. pdf

DeCarlo, L. T. (2005). A model of rater behavior in essay grading based on signal detection theory. Journal of Educational Measurement, 42, 53-76. pdf typo correction

DeCarlo, L. T. (2005). On bias in magnitude scaling and some conjectures of Stevens. Perception & Psychophysics, 67, 886-896. pdf

DeCarlo, L. T. (2003). An application of signal detection theory with finite mixture distributions to source discrimination. Journal of Experimental Psychology: Learning, Memory, and Cognition, 29, 767-778. pdf

DeCarlo, L. T. (2003). Source monitoring and multivariate signal detection theory, with a model for selection. Journal of Mathematical Psychology, 47, 292-303. pdf

DeCarlo, L. T. (2003). Using the PLUM procedure of SPSS to fit unequal variance and generalized signal detection models. Behavior Research Methods, Instruments, & Computers, 35, 49-56. pdf

DeCarlo, L. T. (2003). An application of a dynamic model of judgment to magnitude production. Perception & Psychophysics, 65, 152-162. pdf

DeCarlo, L. T. (2002). Signal detection theory with finite mixture distributions: Theoretical developments with applications to recognition memory. Psychological Review, 109, 710-721. pdf

DeCarlo, L. T. (2002). A latent class extension of signal detection theory, with applications. Multivariate Behavioral Research, 37, 423-451. pdf

DeCarlo, L. T., & Luthar, S. S. (2000). Analysis and class validation of a measure of parental values perceived by early adolescents: An application of a latent class model for rankings. Educational and Psychological Measurement, 60, 578-591. pdf

DeCarlo, L. T. (1998). Signal detection theory and generalized linear models. Psychological Methods, 3, 186-205. pdf typo correction

DeCarlo, L. T. (1997). On the meaning and use of kurtosis. Psychological Methods, 2, 292-307. pdf

DeCarlo, L. T. (1994). A dynamic theory of proportional judgment: Context and judgment of length, heaviness, and roughness. Journal of Experimental Psychology: Human Perception & Performance, 20, 372-381. pdf

DeCarlo, L. T., & Tryon, W. W. (1993). Estimating and testing autocorrelation with small samples: A comparison of the C-statistic to a modified estimator. Behavior Research and Therapy,31, 781-788. pdf

DeCarlo, L. T. (1992). Intertrial interval and sequential effects in magnitude scaling. Journal of Experimental Psychology: Human Perception & Performance, 18, 1080-1088. pdf

DeCarlo, L. T. & Cross, D. V. (1990). Sequential effects in magnitude scaling: Models and theory. Journal of Experimental Psychology: General, 104, 375-396. pdf

#### HUDM 4050: Introduction to measurement

An introduction to basic concepts and issues in measurement. Descriptive statistics, scales of measurement, norms, reliability, validity. Advantages and limitations of measurement techniques are discussed and illustrated.

#### HUDM 5059: Psychological measurement

Open to doctoral and Ed.M. students in psychology; others only by permission. A previous course in statistics or measurement is recommended. An in-depth examination of measurement and associated techniques, norms, classical test theory, reli-ability, validity, item response theory, issues, and applications.

#### HUDM 6030: Multilevel longitudinal data analysis

Prerequisite: HUDM 5122. Multilevel models include a broad range of models called by various names, such as random effects models, multi-level models, and growth curve models. This course introduces the background and computer skills needed to understand and utilize these models.

#### HUDM 6055: Latent structure analysis

Permission required. Prerequisite: HUDM 5122. Recommended: HUDM 6122. Study of latent structure analysis, including measurement models for latent traits and latent classes, path analysis, factor analysis, structural equations, and categorical data analysis.

#### HUDM 6122: Multivariate analysis I

Permission required. Prerequisite: HUDM 5122 or equivalent; HUDM 5123 is recommended. An introduction to multivariate statistical analysis, including matrix algebra, general linear hypothesis and application, profile analysis, principal components analysis, discriminant analysis, and classification methods.

#### HUDM 6123: Multivariate analysis II

Permission required. Prerequisite: HUDM 6122. A continuation of multivariate statistical analysis, including canonical analysis, MANOVA, factor analysis, and categorical data analysis.

### Documents & Papers

Download: DeCarlo, Kim, Johnson (2011). [PDF]