introduction to research methodology, Slides of Qualitative research

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Sampling:

Probability, Nonprobability and

Determination of Sample Size

Objectives

• By the end of this lesson, you will be prepared to:

1. Differentiate between probability and nonprobability sampling.
2. Describe types of probability and nonprobability sampling.
3. Discuss how quantitative sample size is determined.
4. Describe information about recruitment and retention that should be considered when appraising quantitative studies.

Probability Sampling

• (^) Every element (subject) in the accessible population has an equal chance of being selected for inclusion in the study. - (^) Also referred to as RANDOM sampling.

Conditions of Probability Sampling

• (^) Accessible population identification
• (^) Sampling frame determination
  • (^) list of all possible elements in accessible population
• (^) Randomization
  • (^) Selection, assignment, or arrangement of elements by chance

• (^) Stratified Random Sampling
  • (^) Selects elements from accessible population divided into strata

• (^) Cluster Sampling
  • (^) Selects elements from larger or smaller subsets of accessible population

Nonprobability Sampling

• (^) Sampling method that does not require random selection of elements.

Types of Nonprobability Sampling

• (^) Convenience Sampling (accidental sampling)
  • (^) Selection of subjects due to ease of access
    • (^) Example: Survey in a shopping mall
  • (^) Findings of an intervention study with a convenience study should be replicated before being applied to a wider population.
• (^) Quota Sampling
  • (^) Selection of elements from accessible population divided into groups - (^) Similar to stratified, but no randomization of selection

Sample Size Determination

• Power analysis - (^) Statistical method to determine sample size to detect effect of independent variable
• (^) Significance Level
  • (^) Alpha level established prior to study (usually 0.05)
• Effect Size - (^) Estimate of how large a difference will be observed between groups
• An adequate sample size is particularly important to detect differences when they do in fact exist.

Inclusion and Exclusion Criteria

• (^) Inclusion criteria are those characteristics that the subject or element must possess to be part of the target population. - (^) Example: Age of 18 years or older to participate in the study.
• (^) Exclusion criteria are characteristics that the subject or element cannot possess and be part of the target population.

References

• (^) White, A.H. (2015). Using samples to provide evidence. In N.A. Schmidt & J.M. Brown (Eds.), Evidence-based practice for nurses: Appraisal and application of research ( rd ed.), (pp. 295-312). Burlington, MA: Jones & Bartlett.