Item Response Theory

Recommended Prerequisites

Some advanced knowledge of statistics is recommended, such as multiple regression models, semi- and non-parametric regression models, exploratoty and confirmatory factor analysis, structure equation models, and growth curve models.  

Teaching Methods

This course will use a multitude of strategies and activities, using oral presentations, in-class discussions, group work, problem solving and data analysis using open source statistical software such as R (https://www.r-project.org/) and RStudio (https://rstudio.com/), and critical analysis of the different applications of the methodologies covered.

Learning Outcomes

This course's main objective is to enable students to use IRT (Item response Theory) in designing, and evaluating instruments in neuropsychology.  

Work Placement(s)

No

Syllabus

This course main topics are:

- Unidimensional IRT (Item Response Theory) models for dichotomous and polytomous item response data,

- Multidimensional IRT models, including the bifactor model,

- Assumptions under IRT models, how to evaluate them, and methods of establishing model to data fit,

- Applications of IRT models, including the assessment of differential item functioning, person fit, and computerized adaptive testing.

 

The primary software used in the course will be R (https://www.r-project.org/), and in particular RStudio (https://rstudio.com/), both open source software, where we will mainly use the R libraries mirt and psych. 

Head Lecturer(s)

Bruno Cecílio de Sousa

Assessment Methods

Assessment
Frequency: 50.0%
Laboratory work or Field work: 50.0%

Bibliography

Chalmers, R., P. (2012). mirt: A Multidimensional Item Response Theory Package for the R Environment.

Journal of Statistical Software, 48(6), 1-29.

Embretson, S. E., & Reise, S. P. (2000). Item Response Theory for Psychologists. Erlbaum.

Li, H.-H., & Stout, W. (1996). A new procedure for detection of crossing DIF. Psychometrika, 61,

647-677.

Meade, A. W. (2010). A taxonomy of effect size measures for the differential functioning of items

and scales. Journal of Applied Psychology, 95, 728-743.

Revelle, W. (in preparation) An Introduction to Psychometric Theory with applications in R. Springer.

at https://personality-project.org/r/book/

Thissen, D., Pommerich, M., Billeaud, K., & Williams, V. S. L. (1995). Item Response Theory

for Scores on Tests Including Polytomous Items with Ordered Responses. Applied Psychological

Measurement, 19, 39-49.

Thissen, D., & Wainer, H. (2001). Test Scoring. Lawrence Erlbaum Associates.