Sampling Methods in Quantitative and Qualitative Research

1. Sampling Methods in Quantitative and Qualitative Research

2. Sampling • Sampling in Quantitative Research

3. Sampling in Quantitative Research • Population • The entire aggregation of cases that meets a specified set of criteria • Eligibility criteria determines the attributes of the target population • Sampling • The process of selecting a portion of the population to represent the entire population

4. Sampling in Quantitative Research • Accessible population • The population of people available for a study • Target population • The entire population in which the researcher is interested and to which he/she wants to generalize the results

5. Sampling Plans • A sample is a subset of the population • A sample should be representative and similar to the population to be studied

6. Sampling Plans • Strata • Subdivisions of the population based on specific characteristics

7. Samples vs. the Population • More economical • More efficient • More practical

8. Problems Using Samples • Sampling bias • Over-representation or under-representation of some characteristic of the population • Not representative of the population being studied

9. Sampling Plans • Types of sampling plans • Nonprobability sample • Convenience sampling • Purposive sampling • Quota sampling • Probability sample • Random sampling • Cluster sampling • Systematic sampling

10. Sampling Plans • Nonprobability sample • The selection of the sample from a population using non-random procedures • Convenience sampling • Purposive sampling • Quota sampling

11. Sampling Plans • Nonprobability sample • Convenience sampling (accidental sampling) • Selection of the most readily available people as participants in a study • Risk of bias and errors as sample may be atypical of the population • Weakest form of sampling • Snowball sampling (network sampling) • The selection of participants by means of referrals from earlier participants

12. Sampling Plans • Nonprobability sample • Quota sampling • Researcher pre-specifies characteristics of the sample to increase its representativeness • This is used so sample includes an appropriate number of cases from each stratum (subpopulation) • Usually use age, gender, ethnicity, socioeconomic status, and medical diagnosis

13. Sampling Plans • Nonprobability sample • Purposive sampling (judgmental sampling) • Researcher selects study participants on the basis of personal judgement about which ones will be most representative or productive • Handpick cases, very subjective

14. Sampling Plans • Nonprobability Sample Problems • Are rarely representative of the target population • But are convenient and economical

15. Sampling Plans • Probability sample • The selection of the sample from a population using random procedures • Random selection – each element in the population has an equal, independent chance of being selected • Should be representative of the population • Random sampling • Cluster sampling • Systematic sampling

16. Sampling Plans • Probability sample • Simple Random sampling • Listing the population elements • Elements are assigned a number • Table of random numbers is used to draw at random a sample

17. Sampling Plans • Probability sample • Stratified Random sampling • Population divided into homogenous subsets • Elements are selected at random • Increases representativeness of the final sample

18. Sampling Plans • Probability sample • Stratified Random sampling • Proportionate sample • a sample that results when the researcher samples from different strata of a population in direct proportion to their representation in the population

19. Sampling Plans • Probability sample • Stratified Random sampling • Disproportionate sample • a sample that results when the researcher samples differing proportions of study participants from different strata that are comparatively smaller • Used when comparison between strata of unequal membership size are desired

20. Sampling Plans • Probability sample • Cluster sampling (multistage sampling) • A form of sampling in which large groupings are selected first, with successive subsampling of smaller units • Used for large scale sampling where it is impossible to have a listing of all elements

21. Sampling Plans • Probability sample • Systematic sampling • The selection of study participants such that every Xth person or element in a sampling frame or list is chosen • Population is divided by the size of desired sample to obtain a sampling interval • Sampling interval is the standard distance between the selected elements

22. Sampling Plans • Sample Size (Quantitative Studies) • Sample size • The number of participants in a sample • Use the largest sample possible • The larger the sample, the more representative it is likely to be • The larger the sample, the smaller the sampling error • Large samples counter balance atypical values

23. Critiquing the Sampling Plan • Did the researcher adequately describe the sampling plan • Type of sampling used • The population under study • Number of participants • Main characteristics of participants • Number and characteristics of potential subjects • Were good sampling decisions made • Was the sample representative of the population

24. Critiquing the Sampling Plan • Response rates • The number of people participating in a study relative to the number of people sampled • Nonresponse bias • Differences between participants and those who declined to participate • A bias that can result when a nonrandom subset of people invited to participate in a study fail to do so

25. Sampling in Qualitative Studies

26. Sampling in Qualitative Studies • Uses small samples • Non-random samples • Sample design is emergent

27. Sampling in Qualitative Studies • Types of Qualitative Sampling • Convenience sampling (volunteer sample) • Snowball sampling • Purposive sampling (theoretical sampling, purposeful sampling) • Researcher selects sample based on information needs which emerged from earlier findings

28. Sampling in Qualitative Studies • Sample Size • Sample size is based on informational needs • Data saturation is sought • Sampling to the point at which no new information is obtained and redundancy is achieved

29. Sampling in Qualitative Studies • Evaluating Sampling Plans Based on: • Adequacy • Sufficiency and quality of the data the sample yielded • Appropriateness • Using the best informants for the sample, those who will provide the best information

30. Reference • Loiselle, C. G., Profetto-McGrath, J., Polit, D. F., & Beck, C. T. (2011). Canadian essentials of nursing research. (Third Edition). Philadelphia: Lippincott, Williams & Wilkins.