Bayesian Statistics and Psychometrics
Beschrijving
Course goals
TESTING AND COURSE AIMS
The Bayesian Statistics part of this course is tested with
- An individual assignment that accounts for 50% of students’ grade. This assignment consists of a written report accompanied by an oral exam.
The aims of the Bayesian Statistics part of this course are:
b. Being able to apply that knowledge by using JAGS and R to program Bayesian procedures and analyse data.
c. Being able to judge when, which, and how Bayes procedures can be used to make inferences from data. Being able to formulate the relative advantages and disadvantages of classical and Bayesian inference. Critically reflecting on the covered methods and statistics, and their application in the social and life sciences.
d. Coherently presenting all of the above in a written report and oral presentations.
The psychometrics part of this course is tested with
- Individual (home) assignment(s) (20%), which consists of multiple exercises spread out over multiple weeks
- An individual exam of psychometric theory (30%), which includes classical test theory, factor analysis, item response theory, test equating, and differential item functioning.
With this assignment and exam we measure the extent to which, in psychometrics,
- Students have developed fundamental knowledge and understanding in the state of the art (Knowledge and Understanding)
- Students have develop problem solving abilities in multidimensional contexts (Applying)
- Students are able to determine the most effective research methods to address a research problem, and justifying the choices made (Applying)
- Students are able to advise researchers in applying the current state of the art in methodology and statistics (Judgment)
- Students are capable of autonomous scholarly self-development (Learning skills)
Students give proof of being a responsible and scholarly professional (Learning skills)
SUMMARIZED:
- Assignment Bayesian statistics part: 50% (minimum 5.5)
- Hand-in assignments psychometrics part: 20% (minimum 5)
- Exam psychometrics part: 30% (minimum 5)
To pass the course Bayesian statistics and Psychometrics students need:
- a minimum of 5.50 for the Bayesian statistics part
- a minimum of 5.50 for the psychometrics part (i.e., the weighted average of the psychometrics assignment (40%) and psychometrics exam (60%) needs to be 5.50 or higher)
Content
Bayesian statistics part
The theory and practice of Bayesian statistics will be introduced. The following topics will be discussed: probability, density of the data, prior and posterior distributions, the difference between classical statistics and Bayesian statistics; basics of Bayesian estimation (Bayesian sampling); basics of Bayesian model evaluation. We will use JAGS and R to apply the learned techniques.
Throughout the course we will make use of a flipped classroom approach, where the student studies video lectures and other provided materials (see course manual) in preparation of classes in which we apply and critically reflect on the studied content.
Psychometrics part
Psychometrics concerns the theory and technique of psychological measurement, for instance, constructing assessment tools, measurement instruments and formalized models to connect observed responses to theoretical (latent) attributes such as IQ. The course gives a broad introduction to the field of psychometrics, followed by a number of advanced topics which give an impression of current developments. The introduction will cover classical test theory, factor analysis and item response theory (IRT). As applications of IRT, the topics of test equating and differential item functioning will be presented and practiced. For both techniques, students will learn to use standard state of the art user software, using the statistical software environment R .
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