sampling nursing research ppt

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SAMPLING

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7/27/2019 Sampling Nursing Research Ppt

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SAMPLING

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 Population 

Definition:

The term population refers to theaggregate or totality of all the objects,

subjects, or members that conform to aset of specifications.

The Accessible Population 

• The aggregate of cases• Conform to the designated criteria

• Accessible to the researcher 

SAMPLING

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The Target Population

• The aggregate of cases

• The researcher would like to make

generalizationsCriteria

• Eligibility criteria or inclusion criteria

• Exclusion criteria

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Sample Definition: Sample is a subgroup of the population. It is

defined as a collection of individual observations from

the population about which inferences are to be made,

and is obtained by a specific method.

Sampling: It refers to the process of selecting a portion of 

the population to represent the entire population.

Sample and Sampling

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Aim of sampling:

• To draw valid inferences about the population parameters

using the sample statistics 

Theory of sampling

This is based on 

• The law of statistics regularity

• The law of inertia of large numbers

Some Terminology

• Element  – The most basic unit of a population from which asample will be drawn.

•Representative sample-A sample whose characteristics arehighly similar to those of the population from which it is drawn.

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• Strata -Subdivisions of the population according to some

characteristic.

• Sampling bias- Refers to the systematic over representation or under representation of some segmentof the population in terms of a characteristic relevant tothe research question.

• Sampling distribution -A theoretical distribution of astatistic using the valves of the statistic computed from

an infinite number of samples as the data points in thedistribution.

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 •

Sampling error -Refers to differences between populations valuesand sample values

• Sampling frame - A list of all the elements in the population, from

which the sample is drawn

• Sampling frame- A list of all the elements in the population, from

which the sample is drawn

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Sampling designs • Probability sampling

• Non probability sampling

Non probability sampling 

• It is less likely to produce accurate and

representative samples than probability

sampling.

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Methods 

• Convenience sampling.

• Snowball sampling or network sampling.

• Quota sampling.

• Purposive sampling or judgmental

sampling.

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Probability sampling 

Methods

• Simple random sampling

• Stratified random sampling

•Cluster sampling or multistage sampling

• Systematic sampling

Sample size 

• Estimated using a procedure known as power analysis

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Factors that Affect Sample Size

Decisions 

• Homogeneity of the population

• Effect size

 Attrition• Number of variables

• Subgroup analyses

• Sensitivity of the measures

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Steps in sampling 

• Identify the target population

• Identify the accessible population

• Specify the eligibility criteria

• Specify the sampling plan

• Recruit the sample

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Factors that Influence the Rate of 

Co-operation 

• Method of recruitment

• Pleasantness of the recruiters

• Persistence

• Payment of an incentive• Explanation of research benefits

• Offers of a research summary

Making participation convenient• Endorsements

•  Assurances of research integrity

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Tips for Sampling

Identify important extraneous variables• Select study participants from two or more sites

• Understand and document who the participants

are

•  As you recruit, document thoroughly

• Develop contingency plans for recruiting more

subjects.

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Sampling in qualitative researchTypes of qualitative sampling 

• Convenience sampling

• Snow ball sampling

• Theoretical sampling

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Sample size - Data saturation 

Sampling process

• Selection on the basis of convenience or snow-balling or bothmethods.

•  

• Sample selection serially ratter then up-front

• Informants are often used to facilitate the selection

• The sample is adjusted in an ongoing fashion

• Sampling continues until saturation is achieved

Final sampling includes a search for confirming and non-confirming cases.