Sampling Methods in
Quantitative and Qualitative
Research
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Sampling
• Sampling in Quantitative Research
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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
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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
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Sampling Plans
• A sample is a subset of the population
– A sample should be representative and similar to the
population to be studied
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Sampling Plans
• Strata
– Subdivisions of the population based on specific
characteristics
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Samples vs. the Population
• More economical
• More efficient
• More practical
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Problems Using Samples
• Sampling bias
– Over-representation or under-representation of some
characteristic of the population
– Not representative of the population being studied
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Sampling Plans
• Types of sampling plans
– Nonprobability sample
• Convenience sampling
• Purposive sampling
• Quota sampling
– Probability sample
• Random sampling
• Cluster sampling
• Systematic sampling
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Sampling Plans
• Nonprobability sample
– The selection of the sample from a population using
non-random procedures
• Convenience sampling
• Purposive sampling
• Quota sampling
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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
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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
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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
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Sampling Plans
• Nonprobability Sample Problems
– Are rarely representative of the target population
– But are convenient and economical
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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
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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
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Sampling Plans
• Probability sample
• Stratified Random sampling
– Population divided into homogenous subsets
– Elements are selected at random
– Increases representativeness of the final sample
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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
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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
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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
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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
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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
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Critiquing the Sampling Plan
• Did the researcher adequately describe the sampling plan
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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
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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
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• Sampling in Qualitative Studies
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Sampling in Qualitative Studies
• Uses small samples
• Non-random samples
• Sample design is emergent
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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
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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
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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
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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.
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