1 / 30

Sampling Methods in Quantitative and Qualitative Research

Sampling Methods in Quantitative and Qualitative Research. Sampling. Sampling in Quantitative Research. 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

mkrohn
Download Presentation

Sampling Methods in Quantitative and Qualitative Research

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  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.

More Related