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*Sampling Methods in Quantitative and Qualitative Research

*Sampling

Sampling in Quantitative Research

*Sampling in Quantitative Research

PopulationThe entire aggregation of cases that meets a specified set of criteriaEligibility criteria determines the attributes of the target population

SamplingThe process of selecting a portion of the population to represent the entire population

*Sampling in Quantitative ResearchAccessible populationThe population of people available for a study

Target populationThe entire population in which the researcher is interested and to which he/she wants to generalize the results

*Sampling PlansA sample is a subset of the population

A sample should be representative and similar to the population to be studied

*Sampling PlansStrata

Subdivisions of the population based on specific characteristics

*Samples vs. the Population

More economicalMore efficientMore practical

*Problems Using SamplesSampling bias

Over-representation or under-representation of some characteristic of the population

Not representative of the population being studied

*Sampling PlansTypes of sampling plans

Nonprobability sampleConvenience samplingPurposive samplingQuota sampling

Probability sampleRandom samplingCluster samplingSystematic sampling

*Sampling PlansNonprobability sample

The selection of the sample from a population using non-random procedures

Convenience samplingPurposive samplingQuota sampling

*Sampling PlansNonprobability sample

Convenience sampling (accidental sampling)Selection of the most readily available people as participants in a studyRisk of bias and errors as sample may be atypical of the populationWeakest form of sampling

Snowball sampling (network sampling)The selection of participants by means of referrals from earlier participants

*Sampling PlansNonprobability sample

Quota samplingResearcher 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

*Sampling PlansNonprobability 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

*Sampling PlansNonprobability Sample Problems

Are rarely representative of the target populationBut are convenient and economical

*Sampling PlansProbability 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 samplingCluster samplingSystematic sampling

*Sampling PlansProbability 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

*Sampling PlansProbability sample

Stratified Random sampling

Population divided into homogenous subsets Elements are selected at random Increases representativeness of the final sample

*Sampling PlansProbability 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

*Sampling PlansProbability 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

*Sampling PlansProbability 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

*Sampling PlansProbability 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

*Sampling PlansSample 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

*Critiquing the Sampling PlanDid the researcher adequately describe the sampling planType of sampling usedThe population under studyNumber of participantsMain characteristics of participantsNumber and characteristics of potential subjects

Were good sampling decisions made

Was the sample representative of the population

*Critiquing the Sampling PlanResponse ratesThe number of people participating in a study relative to the number of people sampled

Nonresponse biasDifferences between participants and those who declined to participateA bias that can result when a nonrandom subset of people invited to participate in a study fail to do so

*Sampling in Qualitative Studies

*Sampling in Qualitative StudiesUses small samplesNon-random samplesSample design is emergent

*Sampling in Qualitative StudiesTypes of Qualitative Sampling

Convenience sampling (volunteer sample)Snowball samplingPurposive sampling (theoretical sampling, purposeful sampling)Researcher selects sample based on information needs which emerged from earlier findings

*Sampling in Qualitative StudiesSample SizeSample size is based on informational needsData saturation is soughtSampling to the point at which no new information is obtained and redundancy is achieved

*Sampling in Qualitative StudiesEvaluating Sampling Plans Based on:AdequacySufficiency and quality of the data the sample yielded

AppropriatenessUsing the best informants for the sample, those who will provide the best information

*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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