Partially Specified Actuarial Tables and the Poor Performance of Static-99R

American Psychology-Law SocietyMarch 2013 Portland, OR 1

Partially Specified Actuarial Tables and the Poor Performance of Static-99R

Richard Wollert Ph.D. Jacqueline Waggoner Ed.D.

Washington State Vancouver University of Portland

[email protected] [email protected]

http://richardwollert.com wordpress.up.edu/waggoner

360.737.7712 503.943.8012

Actuarial Instruments for Sex Offender Risk Assessment

Contain “risk items” correlated with sexual recidivism.

Each risk item is subdivided into categories.

An offender is assigned to only 1 category per risk item.

American Psychology-Law Society March 2013 Portland, OR 2

Actuarial Manual Sets forth criteria for assigning offenders

to item categories. Contains coding rules that weight each

category. Some categories scored as zero, some

as 1 or more, a few as – 1 or less.


Actuarial Manual

An offender is assigned to a “risk group” per his score.

Some groups include a range of scores. We call them “bins.”


One-Way Model (Once Called “Partial Specification” but Dropped as a Misnomer)

Tries to capture the effects of risk factors on recidivism with a single number.

First generation actuarials were one-way models.

The 10-item Static-99 is an example. Offenders got one point for “current age

less than 25.” No points if older.



One-way Actuarial Table for Static-99 Score Bins and

Point Scores (from Hanson & Thornton, 2000, p. 129).

The “Age Invariance Effect” (Hirschi & Gottfredson, 1983)

Sexual recidivism declines with age throughout life (Hanson, 2002).

The decline is linear. The effect applies to all risk bins (Wollert, 2006;

Hanson, 2006). Static-99 combined bin-wise rates for all ages. This masked the fact that different age groups

have different recidivism rates.


Static-99 Underestimated Young Offender Rates (-%) and Overestimated Old Offender Rates (+%)

Even With Optimum (Unweighted) Scaling L


The MATS-1 (Wollert et al., 2010) Took Into Account the Linearity of Age Invariance and Addressed the Estimation Errors of Static-99 MATS-1 = “Multisample Age-Stratified Table of

Sexual Recidivism Rates.” Removes age item from Static-99, so it has 9

“non-age predictor” (NAP) items. Recidivism focus is on an offender’s age and

NAP score (able to capture interactions). Also called a “two-way” model.



MATS-1 Recidivism Rates

Static-99R Is A One-Way Model Designed To Account For The Age Effect

Described in Helmus et al., 2012. Age-weighting was used. 18-34 group: One point added. 40-59 group: One point subtracted. 60-70+ group: Three points subtracted.


Static-99R Performed Poorly

Construction sample ROC = .708. Validation sample ROC = .720. Static-99 validation sample ROC = .713. Recidivism rate for the Static-99R high

bin < 27%.


How Age-Weighting Undermined Static-99R’s Performance: Part 1 of a 3 Part Story

243 young offenders were moved to the highest risk bin from lower Static-99 bins because they received an extra point.This is “upscale dilution.” Less dangerous

offenders are mixed with more dangerous offenders = high bins have lower rates (Waggoner et al., 2008).


How Static-99R’s Performance Was Undermined by Age-Weighting: Part 2.

230 old offenders were taken out of the high bin and moved to lower bins because they received negative points.This is “downscale enrichment.” More

dangerous offenders are mixed with less dangerous offenders = low bins have higher rates.


How Static-99R’s Performance Was Undermined by Age-Weighting: Part 3.

The numbers of recidivists and nonrecidivists in each bin were about the same for Static-99 and Static-99R when offender data were pooled across age groups.

It is impossible to obtain accuracy differences using ROC tests when the binwise distributions of recidivists and nonrecidivists for two tests are about the same.



The Number of Recidivists and Nonrecidivists In Each Static-99 and Static-99R Bin Were Similar

Static-99R Bins Underestimate Recidivism for Young Offenders and Overestimate It for Old Offenders.


Discussion

Age-weighting did not enhance Static-99R.

Like Static-99, it underestimates young offender rates and overestimates old offender rates.


A Solution to Age-Weighting Problems: Convert Static-99R to a 2-Way Model

Take all the age points out of Static-99R. Stratify Static-99R NAP bins by age in one table. Use external data and frequency or Bayesian

math to construct another table like the first. Assign the cells in Table 1 to bins on the basis

of the cell-wise recidivism rates in Table 2.e.g., cells with very large rates in Table 2

make up Table 1’s “high” bin category, etc.


References Hanson, R. K. (2002). Recidivism and age. Journal of Interpersonal

Violence,17, 1046-1062. Hanson, R. K. (2006). Does Static-99 predict recidivism among older

sexual offenders? Sexual Abuse: A Journal of Research and Treatment, 18, 343-355.

Hanson, R. K. & Thornton, D. (2000). Improving risk assessments for sex offenders: A comparison of three actuarial scales. Law and Human Behavior, 24, 119-136.

Helmus, L., Thornton, D., Hanson, R. K., & Babchishin, K. M. (2012). Improving the predictive accuracy of the Static-99 and Static-

2002 with older sex offenders: Revised age weights. Sexual Abuse: A Journal of Research and Treatment, 24(1), 64-101. DOI: 10.1177/1079063211409951.


References Hirschi, T. & Gottfredson, M. (1983). Age and the explanation of crime.

American Journal of Sociology, 89, 552-584. Waggoner, J., Wollert, R., & Cramer, E. (2008). A respecification of

Hanson’s updated Static-99 experience table that controls for the effects of age on sexual recidivism among young offenders. Law, Probability and Risk, 7, 305-312.

Wollert, R. (2006). Low base rates limit expert certainty when current actuarial tests are used to identify sexually violent predators:

An application of Bayes’s Theorem. Psychology, Public Policy, and Law, 12, 56-85.

Wollert, R. (2007, August). Validation of a Bayesian Method for Assessing Sexual Recidivism Risk. Presented in San Francisco at the 2007 APA conference. http://www.richardwollert.com


References Wollert, R., Cramer, E., Waggoner, J., Skelton, A., & Vess, J.

(2010). Recent research (N=9,305) underscores the importance of using age-stratified actuarial tables in sex offender risk assessments. Sexual Abuse: A Journal of Research and Treatment, 22, 471-490. DOI: 10.1177/1079063210384633.

Acknowledgements

The authors are indebted to Brian Abbott, David Cooke, Ted Donaldson, Elliot Cramer, and Diane Lytton for reading and commenting on previous versions of this presentation.


Partially Specified Actuarial Tables and the Poor Performance of Static-99R

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