7-13 (Final) Flashcards
Experimentation
-an approach to research best suited for explanation and evaluation.
-a process of observation to be carried out in a situation expressly brought about for that purpose
Experiments involve:
-Taking action
-Observing Consequences
(Especially suited for hypothesis testing)
Central Features of the Classical Experiment
-Variables, Time Order, Measures, and Groups
Three Pairs of Components of classical experiments
-Independent and dependent variables
-Pretesting and post testing
-experimental and control groups
The outcome, or the effect we expect to see depends on
the independent variable
The Independent Variable
Takes the form of a stimulus that is either present or absent. “The Cause”
The Dependent Variable
The outcome, the effect we expect to see. Depends on the independent variable.
Pretested
Subjects are initially measured in terms of the dependent variable prior to association with the independent variable
Posttesting
Subjects are remeasured in terms of the dependent variable. Differences noted attributed to influence of independent variable
Experimental Group
Exposed to whatever treatment, policy, or initiative we are testing
Control Group
Very similar to experimental group, except that they are NOT exposed.
Hawthorne Effect
Pointed to necessity of control groups
Independent: improved working conditions (better lighting)
Dependent: improvement of employee satisfaction and productivity
Workers were responding more to the attention than to the improved working conditions
Placebo
Ensures that changes in the Dependent Variable actually result from the Independent Variable and are not psychologically based
Double-Blind Experiment
Neither the subjects nor the experimenters know which is the experiment group and which is the control group
Cardinal Rule
Ensure that Experimental and Control groups are as similar as possible
Selecting Subjects
- Decide on target population
- How to select particular members from that group for your experiment
(Randomization)
Randomization
Central Feature of the classical experiment to get statistically equivalent groups
Threats to Internal Validity
Conclusions drawn from experimental results may not reflect what went on in the experiment
History
External events may occur during the course of the experiment
Maturation
People constantly are growing
Testing
The process of testing and retesting
Instrumentation
Changes in the measurement process
Statistical Regression
Extreme scores regress to the mean
Selection biases
The way in which subjects are chosen (use random assignment)
Experimental Morality
Subjects may drop out prior to completion of experiment
Causal Time Order
Ambiguity about order of stimulus and Dependent Variable (which caused which)
Diffusion/Imitation of Treatment
Experimental group may pass on elements to Control group when communicating
Compensatory Treatment
Control group is deprived of something considered to be of value
Compensatory Rivalry
Control Group deprived of the stimulus may try to compensate by working harder
Demoralization
Feelings of deprivation among control group result in subjects giving up
Generalizability
generalize from experimental findings to the real world
Two dimension of generalizability
Construct Validity and External Validity
Threats to Construct Validity
Concerned with generalizing from experiment to actual causal processes in real world. Link structure and measures to theory. Clearly indicate what constructs are represented by what measures. Decide how much treatment is required to produce change in dependent variable
Threats to external validity
Significant for experiments conducted under carefully controlled conditions rather than more natural conditions (reduces internal validity)
Explanatory Studies
Internal Validity
Applied Studies
External Validity
Quasi-Experimental Designs
When randomization isnt possible for legal/ethical reasons. (Internal Validity threat)
Two categories of Quasi Experimental Designs
Nonequivalent-group designs
Time - series designs
Cohort
Group of subjects who enter or leave an institution at the same time
Longitudinal Studies
Examine a series of observations over time
Interrupted
Observations compared before and after some intervention (cause and effect studies)
Sampling
The process of selecting observations (allows researcher to make a small subset of observations and then generalize the rest of the population)
Logic of Probability Sampling
Enables us to generalize findings from observing cases to a larger unobserved population
Representative
Each member of the population has a known and equal chance of being selected into the sample
Sample Element
Who or what are we studying
Population
Whole Group
Population Parameter
The value for a given variable in a population
Sample Statistic
The summary description of a given variable in the sample; we use sample statistics to make estimates or inferences of population parameter
Purpose of Sampling
To select a set of elements from a population in such a way that descriptions of those elements accurately portray the parameters of the total population from which the elements are selected
Sampling Distribution
The range of sample statistics we will obtain if we select many samples
Sampling Frame
List of elements in our population
Probability Theory
Gives us a formula for estimating how closely the sample statistics are clustered around the true sample
Standard Error
A measure of sampling error that tells us how sample statistics will be dispersed or clustered around a population parameter
Two Key Components of Sampling Error
Confidence Levels and Confidence Intervals
Simple Random Sampling
Each element in a sampling frame is assigned a number, choices are then made through random number generation as to which elements will be included in your sample
Systematic Sampling
Elements in the total list are chosen systematically for inclusion in the sample
Stratified Sampling
Ensures that appropriate numbers are drawn from homogeneous subsets of that population
Disproportionate stratified sampling
way of obtaining a sufficient number of rare cases by selecting a disproportionate number
Multistage Cluster Sampling
Involves the repetition of listing and sampling
Nonprobability Sampling
Sampling in which the probability that an element will be included in the sample is not known
Purposive Sampling
Selecting a sample on the basis of your judgement and the purpose of the study
Quota Sampling
Units are selected so that total sample has the same distribution of characteristics as are assumed to exist in the population being studied
Snowball Sampling
You interview some individuals and then ask them to identify others who will participate in the study, who ask others, etc.
Three Types of nonprobability sampling
Purposive, Quota, Snowball
Counting Crime
Asking people about victimization counters problems of data collected by police
Self-Reports
Dominant method for studying the etiology of crime
Perceptions and Attitudes
To learn how people feel about crime and CJ policy
Targeted Victim Surveys
Used to Evaluate policy innovations and program successes
Open-Ended
Respondent is asked to provide his or her own answer
Closed-Ended
Respondent selects an answer from a list
Make items clear
Avoid ambiguous questions; do not ask double barreled questions
Short Items are Best
Respondents like to read and answer a question quickly
Avoid Negative Items
Leads to misinterpretation
Avoid Biased Items and Terms
Do not ask questions that encourage a certain answer
Designing Self-Report Items
Use of computer-assisted interviewing techniques
Contingency Questions
Relevant only to some respondents-answered only based on the previous response
Matrix Questions
Same set of answer categories used in multiple questions
Warning Mailings
Address correction requested card sent out to determine incorrect addresses and to warn residents to expect questionnaire in the mail
Cover Letters
Detail why survey is being conducted, why respondent was selected, why it is important
Strengths of Survey Research
useful for large populations
standardized questionnaires ensure uniform responses and measurement
protects against respondents interpreting concepts differently
Weaknesses of Survey Research
Superficial coverage of complex topics
Cannot readily deal with specific contexts
Some populations hard to contact
Often represent the least common denominator for assessment
Qualitative Interview
An interaction between an interviewer and a respondent where the interviewer has a general plan of inquiry, including topics to be covered
Interview Schedule
The structure of the interview that may have predetermined questions or topical areas to be discussed
Structured interviews
Create standardized responses so respondents are given the same stimulus, allowing for responses to be compared
semi-structured interview
Has standardized questions but allows the interviewer to explore themes that emerge during the interview
Two Main Approaches to Unstructured Interviews
Conversations and Interview Guide
Focus Groups can be:
Natural groups with an existing connection or artificial groups selected by criteria and brought together
Focus Groups
6-12 People brought together to engage in guided group discussion
Focus groups can
Generate hypotheses or be combined with other types of data gathering
Diachronic
A diachronic delivery of material starts at the beginning and progresses chronologically
Synchronic
A synchronic framework does not depend on time
Two Types of Qualitative Interview Questions
Branch Approach and River-and-Channel approach
Reflexivity
Refers to your subjectivity and the meaning you give to information
Memoing
Involves writing about your research process and is important to recognize subjectivity
Field Research
Gives comprehensive perspective, enhances validity, especially appropriate for topics best understood in their natural setting.
Ethnography
Focuses on detailed and accurate description rather than an explanation.
Complete participant
Participate fully; true identity and purpose not known to subjects
Participant-as-observer
Make known your position as researcher and participate with the group
Observer-as-participant
Make known your position as a researcher; do not actually participate
Complete Observer
Observe without becoming a participant
Field Notes
Observations are recorded as written notes; often in a field journal; first take sketchy notes and then rewrite in detail
Structured Observations
Observers mark closed-ended forms, which produce numeric measures
Flexibility
No need to prepare much in advance
Field Observations - Strengths and Weaknesses
-Great depth of understanding
-Flexibility
-High Validity
-Low Reliability
-Generalizability
-Precise probability samples can’t normally be drawn
High Validity
Quantitative measures-incomplete picture
Low reliability
Often very personal
Generalizability
Personal nature may produce findings that may not be replicated by another
Data from Agency Records
Agencies collect a vast amount of crime and criminal justice data
Secondary Analysis
Analyzing data previously collected
Content Analysis
Researchers examine a class of social artifacts (typically written docs)
Gov Orgs that routinely collect and publish compilations of data
FBI, Census, BJS, Federal Bureau of Prisons, Admin Office of Courts
Ted Robert Gurr (1989)
Used published statistics on violent crime dating back to thirteenth-century England to examine how social and political events affected pattens of homicide through 1984
Collecting New Data
-Specific Research Purposes
-“Hybrid” source (observation, interview, CJ agency activity)
-Needs cooperation of orgs and staff
Content Analysis
Systemic study of messages through any form of communication
Coding in Content Analysis
-Establish universe, units of analysis, sampling frame, then sample
-Conceptual Framework
-Manifest Content or Latent Content
Manifest Content
Visible, surface content-similar to using closed-ended survey questions
Latent Content
Underlying meaning
Secondary Analysis
Data collected by other researchers used to address new research questions
Advantages of Secondary Analysis
Cheaper, faster, benefit from work of skilled researchers
Disadvantages of Secondary Analysis
Data may not be appropriate to your research question; least useful for evaluation studies (specific questions/programs), validity
Evaluation Research
Refers to research purpose rather than a specific method; seeks to evaluate the impact of interventions
Problem Analysis
Designed to help public officials choose from alternative future actions
Policy Intervention
An action taken for the purpose of producing some intended result
Evidence-Based Policy
The actions of justice agencies are linked to evidence used for planning and evaluation
Policy Process
-Demand for new action or policy
-Policymakers consider ultimate goals
-Outputs
-Impacts
-Result
Outputs
The means to achieve desired goals
Impacts
Refer to basic questions about what a policy seeks to achieve
Problem Formation and Measurement
Different stakeholders have different views and goals. Must clearly specify outcomes; create objectives, define and measure
Chula Vista
Common area of auto thefts; increased police; reduced in those areas but not Chula Vista as a whole
