Sampling Methods in Quantitative and Qualitative Research 1

Sampling Methods in Quantitative and Qualitative Research 1

Sampling • Sampling in Quantitative Research 2

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 3

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 4

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

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

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

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

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

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

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 11

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 12

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 13

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

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 15

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 16

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

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 18

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 19

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 20

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 21

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 22

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 23

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 24

• Sampling in Qualitative Studies 25

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

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 27

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 28

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 29

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