Sampling Flashcards
Sampling
The process of selecting groups of people, events, behaviors, or other elements for study in a research investigation
Population
A well defined set that has certain properties or characteristics from which data can be gathered and analyzed
Target population
The entire population of interest
Accessible population
The population the researcher has access to
Inclusion criteria
Sampling criteria identified by the researcher that must be present for the subject to be included in the study
Exclusion criteria
Sampling requirements identified by the researcher that eliminate a subject from being in the sample
Homogenous sample
A group with limited variation in attributes or characteristics, helps the researcher to limit the impact of extraneous variables
Heterogeneity
A sample group with a wider variety of characteristics and fewer similarities; reduces bias in the study, but increases chances of extraneous variables
Representative sample
The sample reflects characteristics of the population to allow for generalizability
Non-probability sampling
Not every participant in the population has an opportunity for selection in the sample which limits eligibility and uses a non-random selection process
Probability sampling
Random selection of participants from the population which ensures that each participant has an equal an independent chance of being included in the study
Convenience sample
A technique in which subjects are included in the study because they happen to be in the right place at the right time
Quota sample
Convenient sample with an added strategy to ensure the inclusion of subject types likely to be underrepresented in a convenience sample
Purposive sample
Process that involves conscious selection of participants by the researcher to ensure certain subjects with specific criteria are chosen for the project
Snowball sampling
Subjects that meet the sample criteria are asked to assist in locating others with similar characteristics to join the study
Simple random sampling
The researcher lists all the possible participants from a population who made the inclusion criteria, and then a random sample is chosen for the study
Stratified random sampling
The population is divided in homogenous sub groups, then an appropriate number of subjects is randomly chosen from the subgroups.
Stratified sampling
A type of sampling method in which you split a population into groups and randomly select some members from each group to be in the sample
Multi stage (cluster) sampling
The random selection of the sample which meets inclusion criteria goes through several stages from a large to a small sample
Cluster sampling
A type of sampling method in which we split a population to clusters, then randomly select some of the clusters, and include all members from those clusters in the sample
Systematic sampling
Selection of every nth case drawn from a population list at fixed intervals, such as every fifth member of a cohort
Theoretical sampling
The researcher selects experiences that will help test ideas and gather complete information about developing concepts
Effect size
Estimation of how large of a difference will be observed between the groups
Power analysis
The procedure conducted by the researcher to determine the minimum sample size for the study
