CTT, DeVellis 2006

7 important questions on CTT, DeVellis 2006

What drives up de chronbach's alpha?

  • The amount of items in a scale/test; this increases k/k-1 closer to 1
  • the correlation/covariance between items; this increases test variance without increasing item variance.

Hat is the dependability coefficient?

  • Instead of the reliability, generalizability theory has the dependability coefficient
  • the dependability coefficient is the ratio between variance that is attributable to the person effect; differences in ability/attribute and the total variance.
  • this describes the extend to which total variance is due to person effects and not due to other facets.

What is the generalizability coefficient?

The generalizability coefficient is the ratio of variance due to person effects and variance due to person effects, item effects, rater effects, and item-rater interaction effects.
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What are g studies and d studies?

A g-study is done to identify the variance decomposition in a test.
a d-study is a study that takes this variance decomposition and modifies the test to get a more desirable variance decomposition.

How can the main effects of variance decomposition be interpreted?

Variance due to differences in individual ability, difference in item difficulty and differences in rater leniency

How can the interaction effects be interpreted in variance decomposition?

  • Variance due to differences in item difficulty for individuals with different abilities
  • variance due to differences in rater leniency for individuals with higher or lower abilities
  • variance due to differences rater leniency for more or less difficult items

How can you interpret cronbach's alpha and what can you do with it?

  • If cronbach's alpha is .6, This means that at least 60% of the variance in true scores can be linearly predicted from the observed scores.
  • from cronbach's alpha the sem of the test scores can be calculated.
  • this sem can be used as a standard deviation of test scores to calculate a 95% ci around the test scores via: test score - 1.96*sem | test score + 1.96*sem

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