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Schmidt & Brown (2021). Evidence-Based Practice for Nurses:
Chapter 11: Using Samples to Provide Evidence
Objectives
Objectives
Identify basic concepts and principles associated with sampling
Apply inclusion and exclusion criteria to identify potential study participants
Summarize the rationale for having an adequate sample size
Explain two ways to calculate sample size
Distinguish between homogeneous and heterogeneous samples
Differentiate between probability and nonprobability samples
Compare and contrast various sampling methods
Concepts and Principles of Sampling
Concepts and Principles of Sampling
Population
= The entire group of elements that meet the study inclusion criteria
Elements
= Basic units of the population such as individuals, events, experiences, or behaviors
Participants
= Individuals who participate in studies; subjects
Use this term over subjects with a focus on patient-centered care because the term subjects is perceived to dehumanize individuals
Subjects
= Individuals who participate in studies; participants
Sample
= A select group of elements that is representative of all eligible elements
Sampling
= The process of selecting a sample
Sampling plan
= Plan to determine how the sample will be selected and recruited
Target population
= All elements that meet the study inclusion criteria
Accessible population
= The group of elements to which the researcher has reasonable access
Representativeness
Representativeness
= The degree to which elements of the sample are like elements in the population
The sample should reflect, or represent, the target population (see figure)
External validity
= The degree to which the results of the study can be generalized to other participants, settings, and times
Generalizability
= The applicability of the results of a study to the target population; external validity
The more representative a sample is, the more confidence there is in the generalizability of the results
Internal validity
= The degree to which one can conclude that the independent variable produced changes in the dependent variable
Sampling bias
= A threat to internal validity when a sample includes elements that over- or underrepresent characteristics when compared to elements in the target population
Sampling error
= Error resulting when elements in the sample do not adequately represent the population
Sampling bias and sampling error, along with the resulting inadequate representation of the population, are also a threat to external validity or how the study can be generalized to the target population
Inclusion criteria
= Characteristics that each element must possess to be included in the sample
Exclusion criteria
Characteristics of elements that will not be included in the sample
Mindful Training.pdfWhy Sample Size is Important for Representativeness
Why Sample Size is Important for Representativeness
In general, the larger the sample, the more representative it will be (see Table 11-1)
Recruiting large samples is expensive and time consuming
Power Analysis
= A statistical method to determine the acceptable sample size that will best detect the true effect of the independent variable
To conduct a power analysis, two factors must be established
(1) Significance level
= The alpha level established before beginning a study
Type 1 error
= When the researcher rejects the null hypothesis when it should have been accepted
(2) Effect size
= An estimate of how large a difference will be observed between the groups
Helpful to think of effect size as the "dose" of the intervention
If the dose is large, it will take fewer participants for change to be seen compared to when a dose is small
When small effects are expected, larger samples are required to find such smaller, more subtle effects
Effect Size.pdf
An important distinction between the concepts of homogeneity/heterogeneity and representativeness
Within-group characteristics
Homogenous
= The degree to which elements are similar or homogenous
Heterogeneous
= The degree to which elements are diverse or not alike
Between-group characteristics
Representativeness is a word that describes between-group characteristics of a population and its sample
Homogenous Population
A homogeneous population with two homogenous samples:
The sample on the left is homogenous and representative of the population
The sample on the right is homogenous but not representative
Heterogeneous Population
A heterogeneous population and two possible samples:
The sample on the left is heterogenous and representative of the population
The sample on the right is not representative because it is homogenous
Factors that influence decisions about the sample size
Feasibility (e.g. cost, convenience, time)
Purpose of the study
Number of variables
Sampling method
Measurements precisions
Attrition rate
= Dropout rate; loss of participants before a study is completed; threat of mortality
Sampling Methods
Sampling Methods
Probability sampling
= Sampling method in which elements in the accessible population have an equal chance of being selected for inclusion in the study
Nonprobability sampling
= Sampling methods that do not require random selection of elements
Recorded Lectures by Professor Wade
Recorded Lectures by Professor Wade
Study Sample Selection Part 1 (16:09)
Study Sample Selection Part 1 Slides.pdfStudy Sample Selection Part 2 (21:23)
Study Sample Selection Part 2 Slides.pdfPage updated
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