sampling

• Sampling strategies


  The process of selecting observations that will be analyzed for research purposes
• Population


  The cluster of people that you are most interested in
• Sample


  A subset of the accessible population, the individuals who actually take part in research
• Eligibility criteria


  Guidelines about who can and cannot participate, based on inclusion and exclusion criteria
• Sampling strategies


  • Probabilistic
  • Non-probabilistic
• Sampling errors


  The selection of research participants may be influenced by access to invitation, recruitment strategies, and personal interest from participants
• Target population


  The entire group that you want to study, justified and supported scientifically
• Accessible population


  The group that a researcher can actually measure, depending on context and resources
• Eligible sample: Inclusion criteria


  • Experience problematic substance use
  • Experience homelessness
  • Having been exposed to music at least once a week in the last 12 months
• Eligible sample: Exclusion criteria


  • Experience psychotic, non-stable symptoms
  • State of intoxication at the moment of the research interview
  • Experience music anhedonia
• Probabilistic sampling techniques


  • Representativity (resembles the target population)
  • Generalizability (results apply to the target population)
  • Random selection (equal chances of being invited)
• Probabilistic sampling techniques (Sheppard, 2020)

  1. Simple random samples

  2. Systematic sampling

  3. Stratified sampling

  4. Cluster sampling
• Probabilistic sampling techniques (Sheppard, 2020)

  • Simple random
  • Systematic
  • Stratified
  • Cluster
• Probabilistic sampling techniques


  • Strengths: Representative samples, generalizability of results, less likely to be biased

  Limitations: Resources needed may limit feasibility, requires high level of skill and experience, may not represent minority groups
• Non-probabilistic sampling techniques


  Used to describe, explore or examine small groups, explore unknown/misunderstood phenomena, understand perspectives of particular individuals, develop in-depth understanding of a phenomenon
• Non-probabilistic sampling techniques


  1. Purposive sampling

  2. Snowball sampling

  3. Quota sampling

  4. Convenience sampling
• Non-probabilistic sampling techniques


  • Strengths: Fast, simple, inexpensive, targets people with specific experiences

  Limitations: More at risk of sampling biases, lack of representativity with the target population, results cannot be generalized