A Look at the Difficulty and Predictive Validity of LS/CMI Items With Rasch Modeling

• Author: Guy Giguère,Sébastien Brouillette-Alarie,Christian Bourassa
• DOI: http://doi.org/10.1177/00938548221131956
• Published date: 01 January 2023
• Date: 01 January 2023
• Subject Matter: Original Articles

CRIMINAL JUSTICE AND BEHAVIOR, 2023, Vol. 50, No. 1, January 2023, 118 –138.

DOI: https://doi.org/10.1177/00938548221131956

Article reuse guidelines: sagepub.com/journals-permissions

© 2022 International Association for Correctional and Forensic Psychology

118

A LOOK AT THE DIFFICULTY AND PREDICTIVE

VALIDITY OF LS/CMI ITEMS WITH RASCH

MODELING

GUY GIGUÈRE

Ministère de la Sécurité publique du Québec

SÉBASTIEN BROUILLETTE-ALARIE

CHRISTIAN BOURASSA

Université de Montréal

The current study aimed to provide data on the performance of items, dimensions, and the total score of the Level of Service/

Case Management Inventory (LS/CMI), one of the most internationally used actuarial scales for the prediction of general

recidivism in convicted persons. Using the full population of Quebec’s male incarcerated population evaluated between 2008

and 2015 with a 2-year follow-up (N = 15,961), results indicated that the predictive validity of the scale and its components

was in line or better than effect sizes reported in other validation studies. A Rasch model was computed to obtain the difficulty

parameter of LS/CMI items. Results indicated that items had varying levels of difficulty and covered the whole spectrum of

the risk continuum. However, difficulty in Rasch was uncorrelated with the predictive validity of items, which casts a doubt

on the applicability of some aspects of item response theory to actuarial scales.

Keywords: Level of Service/Case Management Inventory (LS/CMI); predictive validity; Rasch; item response theory;

actuarial scales; general recidivism; convicted persons; incarcerated persons

Risk assessment for crime and violence has grown at a very fast pace during the last 30

years, especially in North America. Following the media coverage of particularly sor-

did sexual aggressions and murders by recidivists, decision-makers from Canadian and

American governments funded the development and implementation of reliable and valid

risk assessment procedures and correctional interventions based on the risk-need-respon-

sivity model (Andrews & Bonta, 2010; Brouillette-Alarie & Lussier, 2018).

The first wave of reliable risk assessment tools is known as static actuarial assessment, a

method that succeeded unstructured clinical judgment with its lackluster inter-rater agree-

ment and poor predictive validity (Dawes et al., 1989; Grove et al., 2000). Actuarial

AUTHORS’ NOTE: The views expressed are those of the authors and not necessarily those of the Ministère

de la Sécurité publique du Québec. Correspondence concerning this article should be addressed to Guy

Giguère, Ministère de la Sécurité publique du Québec, 2525 Boulevard Laurier, Quebec City, Quebec, Canada

G1V 2L2; e-mail: guy.giguere@msp.gouv.qc.ca.

1131956CJBXXX10.1177/00938548221131956Criminal Justice and BehaviorGiguère et al. / LS/CMI ITEMS RASCH MODELING

research-article2022

Giguère et al. / LS/CMI ITEMS RASCH MODELING 119

assessment reliably determines the level of risk by mechanically combining empirically

validated predictors. This method is considered “atheoretical,” because the main inclusion

criterion of an item in a scale is its statistical association with the outcome of interest, not

its theoretical relevance. The first actuarial scales comprised static risk factors only, which

strengthened the perception that these tools were largely atheoretical (Andrews & Bonta,

2010; Bonta, 1996). The second wave of actuarial scales was defined by its inclusion of

dynamic risk factors, also known as criminogenic needs. Therefore, they were better posi-

tioned to follow the evolution of risk over time and suggest intervention targets than instru-

ments that exclusively comprised static risk factors (Andrews & Bonta, 2010; Bonta, 1996,

2002; Gendreau et al., 1996; Hanson & Harris, 2000). The most recent generation of actu-

arial scales is case management risk/need tools (Andrews & Bonta, 2010). In addition to

assessing static and dynamic risk factors, this generation provides clear guidelines to ensure

that case management will be consistent with the results of risk assessment, according to the

risk and need principles of effective correctional intervention. The Level of Service/Case

Management Inventory (LS/CMI; Andrews et al., 2004) is a prime example of a case man-

agement risk/need tool that assesses general recidivism risk.

Having reliable and valid risk assessments has numerous advantages. Overestimation of

risk can lead to the long-term imprisonment of individuals who could otherwise become

productive members of society or actively impair their chances of reintegration upon

release. Indeed, high-risk statuses, such as “sexually violent predator” are known to be sig-

nificant obstacles to reintegration, limiting housing, and employment opportunities (Harris,

2014). Conversely, underestimation of risk can lead to the release of dangerous individuals

and result in new victims. Therefore, precise risk assessments that are neither too high nor

too low have been increasingly seen as a cornerstone of correctional practice since the early

1990s (Brouillette-Alarie & Lussier, 2018).

THE FOCUS OF RISK TOOLS ON PREDICTIVE VALIDITY AND THE NEGLECT OF OTHER

PSYCHOMETRIC ASPECTS

Because the primary objective of actuarial scales is to make the most accurate predic-

tions to inform risk management and intervention efforts, studies on risk tools have tradi-

tionally focused on predictive validity rather than construct validity or other psychometric

aspects (Helmus & Babchishin, 2017). Contrarily to psychometric tests from the field of

psychology or ability tests from the field of education, criminological risk tools are more

interested in making an accurate prediction about the risk of reoffending than determining

the ability of an individual on a construct (e.g., extraversion/introversion, algebra skills).

Therefore, risk tool validation studies have typically neglected relevant sources of evidence

that are potentially necessary to justify the interpretation and uses of scores stemming from

actuarial scales (Helmus & Babchishin, 2017; Messick, 1989). At the forefront of these

sources of evidence lies construct validity, the degree to which a test measures what it

claims to be measuring (Cronbach & Meehl, 1955).

Many authors have advocated for the integration of construct-oriented approaches in

criminological risk assessment practice (Babchishin et al., 2016; Brouillette-Alarie et al.,

2016, 2022; Mann et al., 2010). Clarifying the construct validity of risk tools has many

potential advantages for the field. First, it offers insight into why certain scales predict cer-

tain outcomes better than others, as this is dependent on the constructs they assess and how