Display of IBR Data:
|Offense Type||Incidents||Offenses||Person Victims||Offenders|
|Crimes Against Persons:||676,361||676,361||755,841||779,526|
|Sex Offenses: Forcible||37,876||37,876||41,315||42,250|
|Sex Assault with Object||2,235||2,235||2,439||2,524|
|Sex Offenses: Non-forcible||2,953||2,953||3,073||3,253|
Crimes Against Property:
|Burglary/Breaking & Entering||269,728||269,728||202,349||303,476|
|Credit Card/ATM Fraud||16,872||16,872||13,407||19,208|
|Theft from Building||143,939||143,940||103,865||159,446|
|Theft from Coin Machine||6,647||6,647||922||7,436|
|Theft from Motor Vehicle||246,260||246,260||228,227||258,765|
|Theft of Vehicle Parts||70,305||70,305||57,457||72,810|
|All Other Larceny||428,116||428,117||267,554||462,030|
|Motor Vehicle Theft||127,692||127,692||105,003||138,859|
|Stolen Property Offenses||15,122||15,122||11,418||20,500|
Crimes Against Society:
|Drug Equipment Violations||56,746||56,746||--||81,118|
|Weapon Law Violations||32,541||32,541||--||42,348|
NOTE: We are not able to accurately match offenders with offenses; in this
example, all offenders are matched with all offenses occurring in the incident. As a
result, these numbers may be inflated. For example, two offenders break into an
apartment building and steal jewelry. One of the offenders also assaults a man in
the apartment. The incident would list two offenses and two offenders. NIBRS
does not tell us which offender is responsible for which offense, or even if one offender
is only responsible for one offense.
*This figure does not include 188 incidents that were missing offense information.
**It is unlikely that shoplifting offenses have individual victims. These incidents may be miscoded.
To create this table, the segments without offense information were matched to an offense file that had been aggregated by the agency number. Frequencies of offenses were then run. The output of the resulting tables were summed and entered into the table above. As you can see, very few incidents included multiple types of offenses.
Download SPSS code to replicate this table (.sps)
The SPSS code provided here produces separate tables showing the frequencies of incidents, offenses, victims, and known offenders. The information was manually combined into the table presented above.
Note: Please check that the variable names used in this syntax match the variable names in your data file. If you need assistance, contact JRSA.
The Crime Analysis, Research and Development Unit of the FBI has also produced line graphs depicting drug offenses. These graphs are another example of the analysis that can be done using NIBRS. NOTE: This syntax uses the Offense data file. Please see Reading NIBRS Data into SPSS to create the necessary file.
Three line graphs are presented. Although the FBI looked at the rates of offenses occurring each month, the following examples present simple counts, which are easily graphed in SPSS. One SPSS syntax file is available to produce all of the graphs presented below.
In 2000, there were 243,249 drug offenses reported in NIBRS. Most of these (77%) were drug/narcotic violations. All of these included the required type of criminal activity entry. When all offenses are grouped together, possessing/concealing is the most frequently reported type of drug activity.
Since each offense can have more than one reported criminal activity type, the total does not equal the number of offenses.
Graph 1. User-Related Drug Activity
This graph looks at drug offenses (drug/narcotic violations and drug equipment violations) with the criminal activity coded as either buying/receiving or using/consuming. Although other criminal activities may apply to users, they do not distinguish users from dealers and are not included in the following table.
As can be seen in this graph, the majority of user-related offenses reported in NIBRS occurred in March, with the fewest reported in December. These data should be graphed over multiple years to determine whether there is a large increase from December to January or whether user-related offenses continued to decline into 2001.
Graph 2. Dealer-Related Drug Activity
This graph looks at drug offenses with criminal activity coded as distributing/selling. Again, other criminal activities may apply to dealers, but they do not distinguish users from dealers and are not included.
Similar to the data for users, the greatest number of dealer-related drug offenses reported in NIBRS occurs in March, with a decline in June and July.
Figure 3. Comparison of User- and Dealer-Related Drug Activity
This graph combines the information from both of the previous graphs. The trends are similar, with more offenses related to dealing drugs than using drugs reported in NIBRS.
Download SPSS Code to replicate these
When using this code, be sure and check that the variable names match the names in your data file. If you need assistance using this file, please email JRSA.