RAVLT Embedded Validity Calculator

Clinical caution: This tool implements a published embedded performance validity model, representing an aid to clinical judgement. No single measure of performance validity should be used to assess invalid effort+. Interpret results alongside stand-alone PVTs, clinical context, collateral information, and the broader neuropsychological profile (see also Sweet et al's (2021) AACN Consensus Statement on Validity Assessment).

Input scores

Total Learning

Sum of RAVLT Trials I–V. Possible range is usually 0–75.

Recognition

Recognition score used in the Davis et al. logistic model.

Classification probability cut-off

What is classification probability?

The Davis et al. (2012) model provides an estimated probability of invalid performance based on the scores you enter. They give two cut-offs, based on the probability value above which their estimate is classified as "invalid".

Estimated base rate of invalid performance

Why do I need this?

Base rates are used to estimate the positive and negative predictive values, based on the sensitivity/specificity of the test. This is separate from/additional to Davis et al.'s algorithm. You can enter your own custom estimate or use the estimates here derived from Roor et al.'s meta-analysis of Performance Validity Test (PVTs) failure rates amongst various clinical populations. Roor et al.'s data utilised various PVTs and are not specific to this validity measure.

Result

Enter scores and select Calculate.

Equation implemented

logit = 6.611 − (0.106 × Total Learning) − (0.258 × Recognition)
Estimated probability of invalid performance = e^logit / (1 + e^logit)

Source: Davis, J. J., Millis, S. R., & Axelrod, B. N. (2012). Derivation of an embedded Rey Auditory Verbal Learning Test performance validity indicator. The Clinical Neuropsychologist, 26(8), 1397–1408.

Base rate estimates: Roor, J. J., Peters, M. J. V., Dandachi-FitzGerald, B., & Ponds, R. W. H. M. (2024). Performance validity test failure in the clinical population: A systematic review and meta-analysis of prevalence rates. Neuropsychology Review, 34(1), 299–319. https://doi.org/10.1007/s11065-023-09582-7

Consensus Guidance on Validity Assessment: Sweet, J. J. et al. (2021). American Academy of Clinical Neuropsychology (AACN) 2021 consensus statement on validity assessment. The Clinical Neuropsychologist, 35(6), 1053–1106. https://doi.org/10.1080/13854046.2021.1896036