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While most psychometric models are based on latent trait theories, CDA requires a cognitive information processing approach to model the psychology of test performance because the score inference is specifically targeted to the examinees' cognitive skills.
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Model testing was conducted based on latent variable scores.
It uses an approach similar in spirit to that used in STRUCTURE, except it is based on latent class analysis.
The model is based on latent connectivity templates and makes intuitive assumptions about the data generation process.
The method used was based on latent content analysis for narrative text [ 18- 20].
Individuals are grouped based on latent growth factors, namely intercept (initial status) and slope.
The method based on latent trajectory analysis was centered and used to create trajectories [ 33].
The Rasch model, named after a Danish mathematician [ 31], is based on a latent trait theory and falls into the modern psychometric approach category.
Since the latent trait is assumed to follow a normal distribution, we shall make the assumption that the above-mentioned formula is also well suited for sample size calculation based on the latent trait distribution.
The fact that the number of subjects given by the classical formula, based on the latent trait, has to be increased using the ratio to reach the expected power for Rasch modelling could deliver a wrong message.
In this brief summary, we focused on unidimensional IRT models, concerned with the measurement of one latent trait, however these models wouldn't be appropriate in the measurement of more than one latent construct or trait.
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