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UCR
FBI databases of crimes reported to police
Index Crimes
8 major crimes used to measure crime
Violent Crime Index
Murder, rape, robbery, aggravated assault
Property Crime Index
Burglary, larceny, motor vehicle theft, and arson
Crime Rate
(Number of crimes / population) x 100,000
Crime Dip
Crime decline beginning in the 1990s
Hot Spots
Areas with concentrated crime
NIBRS
Detailed crime reporting system that replaced many UCR limitations (National Incident-Based Reporting System)
Hierarchy Rule
Only the most serious offense is counted
Sampling
Selecting part of a population to represent the whole
Sampling Frame
List of all population members
Simple Random Sampling
Everyone has equal chance
Stratified Random Sampling
Population divided into groups then sampled
Proportionate Stratified Sample
Groups sampled according to population size
Disproportionate Stratified Sample
Groups intentionally over- or under-sampled
Cluster Sample
Randomly select groups instead of individuals
Systematic Sample
Every nth person selected
Random Start
Random beginning point for systematic sampling
Multistage Sample
Multiple sampling methods combined
Probability Sampling Advantages
Representative and Generalizable
Probability Sampling Disadvantages
Expensive and time consuming
Quota Sample
Fill categories until quotes met
Accidental Sample
Whoever is available
Purposive Sample
Participants chosen for specific characteristics
Snowball Sample
Participants recruit others
Non Probability Sampling Advantages
Cheap, easy, and useful for hidden populations
Non Probability Sampling Disadvantages
Less representative and limited generalization
Focus Groups
Small group discussion
Mock Trials
Simulated court proceedings
Criminal Profiling
Predict offender traits from crime characteristics
Variable List
List of variables to be measured
Dummy Tables
Tables prepared before data collection
Pretest
Trial run of survey
Mail Surveys
Surveys distributed through mail
Increasing Mail Responses
Follow-up letters, incentives, personalized contacts, and return envelopes
Self-Report Surveys
People report their own behaviors
Known-Group Validation
Determines if survey distinguishes known groups
Lie Scales
Detect dishonesty
Internal Consistency
Items measure same concept
Keyboard Entry
Respondent enters answers directly
Coder Monitoring
Checks coding accuracy
Codesheet
Records coded responses
Coding
Assign numbers to responses
Codebook
Explains coding system
Structured Interview
Predetermined question
Unstructured Interview
Flexible conversation
Depth Interview
Detailed exploration
Interviewer Effect
Interviewer influences answers
Randomized Response Technique (RRT)
Protects anonymity on sensitive questions
Probing
Follw-up questions
Editing
Checking completed interview
Vignettes
Short situations used for responses
Scenarios
Hypothetical situations
Screening Questions
Determine eligibility
CAPI
Computer-assisted Personal Interviewing
CART
Computer-Assisted Telephone Interviewing
SPSS
Statistical analysis software
Random Digit Dialing
Randomly generated phone numbers
Branching Procedure
Questions depend on previous answers
Dark Figure of Crime
Crimes not reported to police
NCVS
National Crime Victimization Survey
Crime Panel
Same people surveyed repeatedly
Bounding
Reduced duplicate reporting
Telescoping Reporting
crime outside the time frame
Demand Characteristics
Participants alter answers because of expectations
Reverse Record Check
Start with people and determine if crimes were reported
Verbal Reports vs. Behavior
What people say vs. what they do
Participant Observation
Researcher participants while observing
Verstehen Approach
Understanding from participant perspective
Complete Participant
Identity hidden
Participant-as-Observer
Participants know researcher
Observer-as-Particpant
Minimal participation
Complete Observer
Observation only
Objectivity
Remaining unbiased
Going Native
Researcher becomes too involved
Field Notes
Written observations
Mnemonics
Memory aids before writing notes
Visual Criminology
Use of photos/videos in research
Single-Subject Designs
Study of one person/unit
Validity
Measures what it should measure
Face Validity
Appears valid
Content Validity
Covers all aspects
Construct Validity
Measures theoretical concept
Pragmatic Validity
Predicts actual outcomes
Convergent-Discriminant Validation
Related measures correlate; unrelated do not
Reliability
Produces consistent results
Test-Related Method
Same test twice
Multiple Forms
Different versions of same test
Split-Half Reliability
Compare halves of a test
Triangulation
Use multiple methods/data sources to study same issues
DUF
Drug Use Forecasting Program
Reliability
CONSISTENCY
Validity
ACCURACY