catSurv (version 1.5.0)

checkStopRules: Check if Stop and/or Override Rules are Met

Description

Evaluates the specified stopping and/or override rules to check if respondent should be asked further questions.

Usage

checkStopRules(catObj)

Value

The function checkStopRules returns a boolean. TRUE indicates all specified stopping rules are met and no specified overrides are met. No further items should be administered. FALSE indicates at least one specified stopping rule is not met, or if any specified override threshold is met. Additional items should be administered.

Arguments

catObj

An object of class Cat

Author

Haley Acevedo, Ryden Butler, Josh W. Cutler, Matt Malis, Jacob M. Montgomery, Tom Wilkinson, Erin Rossiter, Min Hee Seo, Alex Weil

Details

The stopping rule thresholds are stored in the following Cat object slots: lengthThreshold, seThreshold, infoThreshold, and gainThreshold. The override thresholds are stored in the following Cat object slots: lengthOverride, gainOverride. A value of NA indicates the rule will not be used in evaluating if further questions should be administered. A user can specify any combination of stopping rules and/or overrides.

Stopping Rules:

lengthThreshold: Number of question's answered \(\geq a\)

seThreshold: \(SE(\hat{\theta}) < a\)

infoThreshold: \(FI < a\) \(\forall\) remaining items

gainThreshold: \(SE(\hat{\theta}) - \sqrt{EPV} | < a\) \(\forall\) remaining items

Overrides:

lengthOverride: Number of question's answered \(< a\)

gainOverride: \(|SE(\hat{\theta}) - \sqrt{EPV} | \geq a\) \(\forall\) remaining items

References

Babcock, Ben, and David J. Weiss. 2009. ``Termination Criteria in Computerized Adaptive Tests: Variable-Length CATs are not Biased." Proceedings of the 2009 GMAC Conference on Computerized Adaptive Testing. Vol. 14.

See Also

Cat-class, estimateSE, expectedPV, fisherInf

Examples

## Loading ltm Cat object
data(ltm_cat)

## Store example answers
setAnswers(ltm_cat) <- c(1,0,1,0,1,0,0,0,1,1, rep(NA, 30))

## Stop administering items if standard error of ability
## estimate is low enough
setSeThreshold(ltm_cat) <- .5
checkStopRules(ltm_cat)

## Now stop if standard error is low enough, but only if respondent has
## answered 11 questions 
setLengthOverride(ltm_cat) <- 11
checkStopRules(ltm_cat)

## When respondent has answered 11 questions and standard error
## of ability estimate is below .5, stop administering items
setAnswers(ltm_cat) <- c(1,0,1,0,1,0,0,0,1,1,0, rep(NA, 29))
checkStopRules(ltm_cat)