CRIM 430 Sampling & Data Collection

Simple Random List of elements in sampling frame Number each element Select a number from the random numbers table arbitrarily The number selected indicates which element should be selected first Move in constant direction on the random number tables until all sample spots are filled

Simple Random Example Sampling FrameRandom Numbers 1. Frank Blue Dana Boots David Heinz Jane DearIf you wanted a sample of 3, who would you pick given the random numbers above? 5. John Doe 6. John Smith 7. Sara White

Systematic Sampling List of elements from sampling frame Put in order (alphabetical, chronological, etc.) Calculate the n th element for selection by dividing the number desired by the total number in the sampling frame Start a random point and go down the list, selecting every n th element until you’ve reached your sample size

Stratified Sampling Modification to previous methods Ensures a degree of representativeness First, population is organized into homogeneous subsets (all males, all females) Sample elements are selected using the simple random or systematic method Once appropriate sizes for each group is me, the sample elements are placed back together to create the whole sample. Sample distributions of stratified variable equals the population distribution

Disproportionate Stratified Used when members of a population vary widely in size (e.g., 90% Male & 10% White)—it ensures that you receive an appropriate number of “rare” cases Same methods as stratified sampling except the distribution of the stratified variable is greater in the sample than it is in the population (I.e., the sample may=50/50 males and females) The “rare” cases are over-sampled To compensate for this, data can be weighted during analysis to reflect population distributions

Multi-Stage Cluster Sampling Used when there are many “layers” to the target population (e.g., police officers from all metropolitan departments across the United States) First, apply sampling to select departments Next, apply sampling to select police officers Sampling is done in stages or clusters More clustering results in potentially less representativeness

Non-Probability Sampling Probability sampling designs are not possible in many situations Non-probability sampling is an alternative; however, the samples are not representative of the population from which they are drawn Non-probability sampling designs are prone to selection bias Non-Probability sampling designs are, therefore, weaker than probability sampling designs

Non-Probability Sampling Designs Purposive or Judgmental Sampling: Identifying a sample based on the presence of a particular characteristic Quota Sampling: Identifying a sample using a matrix to represent the characteristics of the population Convenience Sampling: Sample is selected because access is easy and convenient Snowball Sampling: Using one respondent to provide contact to 2-3 additional respondents—continuous process to identify a larger sample

Types of Data Collection Self-Report Data Data derived from the respondent him/herself Key=Ask questions to subjects Example: National Crime Victimization Survey Official Data Data derived from agency records or databases Key=Examine written records Example: Uniform Crime Reports Observation Data Data derived from watching the activities of people or events; information is coded by observer Key=Watching behavior Example: Coding the behavior of detention officers and offenders at a correctional institution

Data Collection: Asking Questions Asking questions provides an indirect measure or substitute for making observations—Used to capture things such as experiences with crime, attitudes and beliefs Self-administered surveys Mailed surveys In-person structured interviews Telephone interviews Focus groups

Asking Questions, Cont’d. Types of questions included in surveys Open-ended Close-ended Statements with levels of agreement Contingency questions (if yes, proceed; if no, skip to) Presentation of questions in a survey Should be clear—avoid ambiguity & confusion Keep items short and to the point Keep items neutral and unbiased Add disclaimers/introductions to provide respondent with direction

Assessment Strengths Useful in describing large populations Standardized surveys improve strength of measurement Flexible during planning Provides opportunity to capture a lot of information Weaknesses Limited in the information it can capture Does not capture the context of the situation Not flexible during implementation Relies on the truthfulness & memory of respondent

Data Collection: Written Records Published Statistics Compiled statistics produced and distributed for public consumption Example: UCR Nonpublic Agency Records Records kept by agency for processing purposes Not available for public consumption Example: Probation case files New Data Collected by Agency Staff New information collected as part of the agency process in order to investigate a research question Example: Use of a new screening tool

Written Records, Continued Other Related Sources: Content Analysis  Reviewing narratives, usually written, to identify patterns and themes  Example: Newspaper reports of crime over time Secondary Data Analysis  Data are originally collected one set of researchers and then made available to other researchers for analysis  Example: Arrestee Drug Abuse Monitoring Data

Assessment Strengths In general, the availability of these data is much easier than self-report The cost can be significantly less than self-report Conducive to large numbers Weaknesses Access is sometimes limited especially with regard to cj information Information is limited by agency priorities Data are rarely flexible and are defined by agency not the research question Quality of data is sometimes questionable due to missing and inconsistent reporting of information

Data Collection: Observation Structured observation=quantitative List of items that an observer will code while observing behavior Observers use a standard code sheet that contains items and close-ended responses Items are completed during or immediately after the observation occurs Unstructured observation=qualitative General descriptions recorded in a narrative Transcripts of taped descriptions or written notes used to to identify themes and patterns

Assessment Strengths Flexible to the needs of the research question Allows for more thorough investigation of certain situations Weaknesses Time consuming and expensive Collection of data is potentially impacted by data collector’s bias Analysis of data can be subjective and open to bias, especially in the case of unstructured observations Limited sample size unless extremely well-funded

Multiple Measures Many studies utilize different types of data to answer research questions For example, using both official and self-report data to measure variables Using multiple methods of data collection builds on the strengths of each method individually and minimizes their weaknesses Multiple methods can increase the reliability and validity of the data you collect Multiple methods, however, are often expensive and time-consuming

Deciding Which Method to Use Decide on your method based on: Research Question: What type of information does your research question require? Availability/access to the sample: How available is a sample and what is your access? Size of the sample: How large of a sample do you need? Time and resources: How much time and money do you have at your disposal?

Ethical Issues All research is bounded and defined by professional code of ethics Social science research is particularly subject to ethical codes because it almost always includes humans subjects When conducting research, it is necessary to balance the potential benefits from doing the research against the possibility of psychological, emotional, and physical harm

IRB All human subject research conducted at a University must be reviewed and approved by the Institutional Review Board The IRB ensures that federally defined safeguards are applied in all types of research with humans Code of Federal Regulations Title 45, Chapter 46, U.S. Department of Health & Human Services Additional rules apply to two populations considered particularly vulnerable: Prisoners Children

IRB Safeguards Safeguards include: Written consent form must be used to request participation in the study Written list of benefits and costs of participation Subject must voluntarily participate Subject must be guaranteed anonymity or confidentiality Analysis of data in the aggregate Protection from deceit by researchers