stochCurtailXval: Simulate stochastic curtailment using leave-one-out CV
In marjoleinF/curtail: A package for test curtailment

Description Usage Arguments Details Value References Examples

Simulates stochastic curtailment on an existing dataset of item scores, using leave-one-out (LOO) cross validation, and a user-specified cut-off value. For a given observation, all other observations will be used to derive the probabilities of obtaining a final test score greater than or equal to the cut-off value.

1 2	stochCurtailXval(dataset, Xstar, gamma0 = .95, gamma1 = .95, plot = TRUE, verbose = FALSE)

`dataset`	A dataframe, containing item scores only.
`Xstar`	Cut-off value to be used for classifying observations as 'at risk' (test-score values greater than or equal to the cut-off value) or 'not at risk' (test-score values less than cut-off value)
`gamma0`	The threshold for the probability, calculated using the 'not-at-risk' training observations, that the classification decision based on the stochastically curtailed version will match that of the full-length instrument.
`gamma1`	The threshold for the probability, calculated using the 'at-risk' training observations, that the classification decision based on the stochastically curtailed version will match that of the full-length instrument.
`plot`	Should test length distribution be plotted?
`verbose`	Should progress be plotted to the command line?

The code is still under development and might change in future versions.

The function prints accuracy estimates to the command line, and plots the curtailed test length distribution. In addition, the function invisibly returns a list with the following elements:

`test.results`	data.frame with columns full.lenght.decision (classification decsion according to full-length test); curtailed.decision (classification decision according to curtailed test administration); current.item (item at which testing was halted); current.score (cumulative testscore at item at which testing was halted).
`curtailed.test.length.distribution`	Descriptive statistics of number of items administered and number of tests curtailed.
`confusion.martrix`	Confusion matrix of full-length and curtailed test classification decisions.
`accuracy`	Correct classification rate (accuracy), sensitivity and specificity.

Fokkema, M., Smits, N., Finkelman, M. D., Kelderman, H., & Cuijpers, P. (2014). Curtailment: A method to reduce the length of self-report questionnaires while maintaining diagnostic accuracy. Psychiatry Research 215, 477-482.

Fokkema, M., Smits, N., Kelderman, H., Carlier, I.V. & Van Hemert, A.M. (2014). Combining decision trees and stochastic curtailment for assessment length reduction of test batteries used for classification. Applied Psychological Measurement, 38(1), 3-17.

Finkelman, M.D., Smits, N., Kim, W. & Riley, B. (2012). Curtailment and stochastic curtailment to shorten the CES-D. Applied Psychological Measurement, 36(8), 632-658.

    ## Only first 100 observations are specified here, to reduce computation time: 
    tmp <- stochCurtailXval(itemscores[1:100,], 19, gamma0=.95, gamma1=.95) 
    tmp$curtailed.test.length.distribution