Data Collection: Sampling Methods

• Tools for Data Collection are covered in Module 6.
• The learning objective is to construct appropriate tools and methods for data collection

Sub-topics

• Sampling

• Types of Sampling Methods

• Methods of Data Collection

• The data collection procedure includes: setting boundaries (sampling), data collection, and establishing data management protocol

Sampling

• Sampling is how a researcher identifies the representative of a population to be used in a study.
• Flick (2009) outlined areas of the research process where sampling decisions are applied:
• Case Sampling
• Sampling groups of cases
• Material Sampling
• Sampling within the material
• Presentational sampling

Case Sampling

• Identifies the target participants.

Sampling Groups of Cases

• Determines where to get the participants.

Material Sampling

• Identifies which tools to use on the participants to collect data.

Sampling within the Material

• Determines what collected data will be used or analyzed.

Presentational Sampling

• Chooses which data should be used to represent the outcomes of the study.

Sampling Methods

• Probability Sampling
• Relies on a researcher's selection of respondents on pure chance, thus everybody in the population participates.
• Includes:
  • Simple Random Sampling
  • Systematic Sampling
  • Stratified Sampling
  • Cluster Sampling
• Non-Probability Sampling
• This technique is prone to bias because of pre-selection of respondents.
• Includes:
• Quota Sampling
• Voluntary Sampling
• Purposive Sampling
• Availability Sampling
• Snowball Sampling

Probability Sampling Methods

• Simple Random Sampling
• Samples are identified randomly, with the help of statistical and mathematical computations.
• Stratified Sampling
• The population is divided into different groups or strata based on criteria set by the researcher.
• The researcher then randomly identifies individuals from these groups.
• Cluster Sampling
• Similar to stratified random sampling, but instead of grouping based on the criteria of the researchers, individuals are randomly selected from naturally occurring groups, like sections in school.
• Multi-Stage Sampling
• A combination of stratified random and cluster sampling that consists of multiple stages of grouping.
• Grouping first from naturally occurring groups and then groups based on criteria set by the researcher.
• Systematic Sampling
• Easiest method of sampling since a researcher sets a fixed interval to determine the sample.
• Example: In a population of 100 individuals, select every 5th member until reaching 50 representatives.

Non-Probability Sampling Methods

• Purposive Sampling
• Samples are targeted and selected based on a criterion set by the researcher.
• These criteria are based on the research objectives and questions to answer.
• Example: A study that wants to study smoking habits would only select individuals who smoke.
• Convenience/Availability Sampling
• The sampling group is identified by the convenience of the researcher.
• Groups are determined based on their availability rather than randomness from the population.
• Does not guarantee an accurate representation of the population but can be useful.
• Snowball Sampling
• The identification of the sample group is accumulative and can come from populations not initially known by the researcher.
• Example: a researcher wants to study the impact of Alzheimer's on family members, but they don't know a lot of patients, they can ask the patients they know for others like them.
• Quota Sampling
• Similar to purposive sampling wherein the population is filtered based on a criterion set by a researcher.
• However, looks for specific characteristics in individuals that may or may not directly link to the research question/objective (e.g. age, sex, religion)
• Voluntary Sampling
  • Chooses samples of people who are willing to participate as respondents.

Methods of Data Collection

• Observation / Fieldwork
• Interviews
• Analysis of Documents and Audio-visual Materials

Observation / Fieldwork

• Is used when a participant can be observed directly.
• Advantages:
  • Researcher has first-hand experience with the participant.
  • Researcher is able to record information as it occurs.
  • Unusual aspects are noticeable during the observation.
  • Useful in exploring topics that are difficult or uncomfortable for the participants to discuss
• Disadvantages:
  • Researcher may be seen as intrusive (annoying/unpleasant)
  • Private information may be observed, that the researcher cannot report
  • Researcher may not have good attending and observing skills
  • Certain information (e.g., children) may present special problems in gaining rapport

Types of Observation

• Participant

• Non-participant

• Systematic/Structured

• Unstructured

• Simple/Contrived Observations

• Participant Observation

  • Researcher is immersed for prolonged periods of time in the setting where the participants/phenomenon is to be observed.

• Non-Participant Observation

  • Similar to participant observation except that the researcher is NOT immersed in the setting, or the participants are not aware of the researcher's presence

• Structured / Systematic Observation

  • Researcher establishes specific rules for the observation and schedule
  • The participant is informed ahead of time of these rules

• Unstructured Observation

  • Complete opposite of structured observation where there are no rules or guidelines set for the observation.
  • Allows a more freeform or narrative means of data collection

• Simple & Contrived Observation

  • In both methods, the participant is unaware of the researcher and the researcher interacts or involves themselves in the setting
  • Simple observations: The researcher cannot change any factors in the setting
  • Contrived observations: The researcher can change or has control over some factors in the setting. This is useful when the goal is to see how participants react to specified situations

Observation Guide

• Determine the venue
• Is the setting be based on who, what, when the observation will take place?
• Is the venue within the researcher's limitations (e.g. logistical and financial consideration)?
• Prepare how to enter the field
• How the researcher will present them self (researcher, observer, participant)?
• How to handle issues that arise due to the venue?
• Identify the things to observe
• (People who stand out, number of people entering/exiting the setting, personal space, behaviors, verbal/non-verbal interactions, or appearance)
• Prepare means of data collection & what type of data to collect (notes, videos, audio, formal and informal interviews, counts/frequency, process flows, or lists)
• Organize data (can it be captured quickly and accurately?)
• What devices can be used?
• When will you analyze the data?
• Define how long the observation is
• How long will the researcher need to get the data?, and will this span multiple days?
• Determine when to exit.
• Does the researcher need to revisit? Is the data complete?
• Did you thank the participants?
• Did you get a contact file of the participants?

Interviews

• A method that is used when a participant can be interviewed directly.
• Advantages:
  • Useful when the participant cannot be directly observed.
  • Historical information can be collected.
  • Allows research "control" over the line of questioning.
• Disadvantages:
  • Provides "indirect” information filtered through the views of interviewees.
  • Provides information in a designated "place” rather than the natural setting.
  • Researcher's presence may bias responses.
  • Not all people are equally articulate (well-spoken) and perceptive (sensitive/responsive).

Types of Interviews

• Structured

• Unstructured

• Semi-structured

• Structured Interview

  • “Oral questionnaires”
  • The researcher asks a list of predefined questions that only permits limited participant responses

• Unstructured Interview

  • Opposite of structured interviews.
  • Participants will be asked one general question and can explain their responses in depth and further questions are based on the answers.

• Semi-Structured Interview

  • Researcher begins with a set of key questions, however the participant is given more freedom to explain certain topics.

Interview Guide

• Develop an interview framework by reviewing research objectives and questions, and answer the following:

• What are the main research questions that the interviewees are intended to answer?

• What are the primary domains of content that should be covered in the interview?

• What types of data are needed to

• Develop a guidepost in preparing interview guide by creating:

• A flow of topic areas to be discussed

• Questions which answer research questions/objectives, but are not too specific

• Use language that is easy to understand for the participant

• DO NOT ask leading questions

• Ask for a database of personal information, or face sheet, for general and specific information

• Prepare different types of questions such as: introducing, follow-up, probing, specifying, direct, indirect, and interpreting questions. The questions can be arranged in a varying order and should allow time for silence and thinking.

• Consider the setting, technical requirements, logistics, and practice interviews

• Identify a successful interviewee; someone knowledgeable, structured, clear, gentle yet assertive, open, critical, remembering, and able to interpret

• Plan what to do after an interview, and make notes on how it went, where it took place, researchers/participants feelings, and the setting of the interview.

• Consider final tips for the interview, such as:

• Prepare for unexpected interviewee behavior or issues with the setting

• Be aware and avoid intrusion of biases or expectations

• Maintain focus in asking questions

• Be careful when talking about sensitive issues

• Always transcribe information as accurately as possible

Analysis of Documents and Audio-visual Materials

• Often used to validate data collected through other methods.
• Is the analysis of documents or materials to give meaning around an assessment/topic.
• Documents and materials can be 1) public records, 2) personal documents, 3) artifacts, 4) video, 5) drawings/pictures
• Advantages
  • Written documents are manageable and practical resources that are “non-reactive", which allows the researcher to review it multiple times
  • Documents are common and highly accessible since it comes in a variety of forms
  • Cost and time-efficient method of data
• Disadvantages
• Analyzing documents and audio-visual materials while valuable, has limitations, including potential bias, incomplete information, subjective interpretation, and ethical considerations such as privacy and confidentiality.

Process of Document Analysis (O'Leary, 2014)

1. Create a list of texts to explore
2. Consider how texts will be accessed with attention to linguistics or cultural barriers
3. Acknowledge and address biases
4. Develop appropriate skills for research
5. Consider strategies for ensuring credibility
6. Know the data to look for
7. Consider ethical issues such as confidentiality and copyright.