Lifetime Likelihood Computations With NIBRS

• Author: Karen G. Weiss,James J. Nolan,Stacia Gilliard-Matthews,Yoshio Akiyama
• Published date: 01 December 2015
• Date: 01 December 2015
• DOI: 10.1177/1525107115623505
• Subject Matter: Articles

Article

Lifetime Likelihood

Computations With

NIBRS

Yoshio Akiyama

1

, James J. Nolan

2

, Karen G. Weiss

2

,

and Stacia Gilliard-Matthews

3

Abstract

This article explores the conditions and assumptions under which it is possible to use

National Incident-Based Reporting System (NIBRS) in lifetime crime computations,

particularly for nonfatal violent crimes. We describe methods for using NIBRS to

study lifetime risk for a variety of crimes and show how researchers and policy makers

can apply these methods using readily available software such as Microsoft Excel.

Finally, we demonstrate in two different studies how NIBRS can be used to estimate

lifetime risk at the state and national levels. In doing so, we introduce the concept of

the ‘‘average person’’ in each age–sex–race grouping to calculate the risk of victimi-

zation for this hypothetical person only.

Keywords

UCR, NIBRS, Lifetime Likelihood

Introduction

Lifetime risk estimations are important tools in the field of public health. They provide

assessments of risk at various points along the life course based on age, race, and sex

for particular diseases such as cancer, schizophrenia, and heart disease, among many

others. Lifetime risk computations help policy makers better understand the nature

1

Retired from teaching and government service

2

West Virginia University, Morgantown, WV, USA

3

Rutgers University, Camden, NJ, USA

Corresponding Author:

James J. Nolan, West Virginia University, Morgantown, WV, USA.

Email: jim.nolan@mail.wvu.edu

Justice Research and Policy

2015, Vol. 16(2) 129-146

ªThe Author(s) 2016

Reprints and permission:

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DOI: 10.1177/1525107115623505

jrx.sagepub.com

and extent of diseases and how best to respond to them. They also provide ways to

quantify the success or failures of public policy aimed at reducing risk for everyone

in a population or for subgroups in the population which experience risk dispropor-

tionate to their representation. Groups like the National Cancer Institute (NCI) regu-

larly publish reports that reflect disparity in risk for diseases across age, race, and sex

groupings. For example, a recent NCI report indicates that although African Ameri-

cans are 6%less likely than White Americans to develop cancer over their lifetime,

they are more likely than Whites to develop stomach and prostate cancer by 39%and

38%, respectively (Howlader et al., 2014). Clearly, this is important information for

public policy makers whose goal is to help reduce this risk.

Crime victimization is another form of health risk that affects the population differ-

ently, especiallyby age, sex, and race. But the limitations of theexisting national crime

data oftenprevent this type of analysis.Lifetime likelihood computations are possiblevia

the NationalCrime VictimizationSurvey (NCVS), the SummaryUniform Crime Report-

ing (UCR) Program,

1

and the National Incident-Based Reporting System (NIBRS) but

with qualifications and specific limitations.The NCVS lifetime likelihoodcomputations

are onlynational in scope and do not includechildren under 12 or victimsof murder. Sum-

mary UCRdata can be used to compute the likelihoodof murder victimizationover a life-

timefor all ages and age groupings.But this is not possiblefor any other UCRindex crime

category becauseinformation about the age, sex, and race of the victim isnot captured.

Since NIBRS does collect age, sex, and race data from the victims of violent crime, it

is now possible to compu te the lifetime risk of viole nt crime victimizatio n. Using the

methods we describein this article, estimates of riskcan be made from birth to a specific

age, suchas 18 or 25 or for any otherage over a lifetime. Risk estimatescan also be estab-

lished from a specific age, say 45, through the rest of a person’s life.

The purpose of this article is to explore the conditions and assumptions under

which it is possible to use NIBRS in lifetime crime computations, particularly for non-

fatal violent crimes such as intimate partner violence and aggravated assault. Just as

assessing risk is an important tool for health research, understanding lifetime risk is

relevant to crime research and policy.

In the pages that follow, we briefly outline findings from the few lifetime risk stud-

ies conducted using NCVS and summary UCR data. We then describe methods for

using NIBRS to study lifetime risk for a variety of crimes and also show how research-

ers and policy makers can apply these methods using readily available software such

as Microsoft Excel. Finally, we demonstrate in two different studies how NIBRS can

be used to estimate lifetime risk at the state and national levels. In doing so, we intro-

duce the concept of the ‘‘average person’’ in each age–sex–race grouping to calculate

the risk of victimization for this hypothetical person.

Lifetime Risk Estimates With National Crime

Victimization Data

In 1987, the Bureau of Justice Statistics (BJS) published Lifetime Likelihood of Victi-

mization which reported estimates of the likelihood of victimization in the United

130 Justice Research and Policy 16(2)