Chapter #9 Flashcards
Population: Target
An entire set of individuals or elements who meet the sampling criteria.
Population: Target (example)
Adult males, 18-years of age or older, diagnosed with type 2 diabetes.
Population: Accessible
The portion of the target population to which the researcher has reasonable access.
Population: Accessible (example)
Patients with diabetes who are in an acute care hospital in Dallas, Texas.
Sample:
The individual units of population.
Sampling:
Selection of a subset of a population to represent the whole population.
Inclusion:
Characteristics that the subject or element must possess to be part of the target population.
Inclusion: Example
In a study of patients who have dementia, a researcher wishes to examine the effects of moderate exercise on patients’ abilities to perform self-care. The researcher decides to use subjects between 70 and 80 years of age who have been diagnosed with dementia for less than 1 year.
Exclusion
Characteristics that can cause a person or element to be excluded from the target population.
Representativeness
A researcher uses a sample whose members have characteristics similar to those of the population from which it is drawn.
Representativeness means?
Means that the sample, access population, and target population are alike in as many ways as possible
Generalization
Extending the findings from the sample under study to the larger population. The extent is influenced by the quality of the study and consistency of the study’s findings.
The steps of data collection are______
specific to each study and depend on the research design and measurement techniques
Recruiting the number of subjects planned is______
critical because data analysis and interpretation depend on having an adequate sample size.
Probability (random) Sampling: Random=
equal chance
Probability (random) Sampling: Stratified Random
used in situations when the researcher knows some of the variables in the population that are critical for achieving representativeness.
Probability (random) Sampling: Cluster Random
researcher develops a sampling frame that includes all the states, cities, institutions, or clinicians with which elements of the identified population can be linked.
Probability (random) Sampling: Systematic Random
used when an ordered list of all members of the population is available.
Non-probability (non-random) Sampling: Convenience
It provides little opportunity to control for biases; participants are included in the study merely because they happen to be in the right place at the right time.
Non-probability (non-random) Sampling: Purposeful
The researcher consciously selects certain participants, elements, events, or incidents to include in the study.
Non-probability (non-random) Sampling: Theoretical
Researcher gathers data from any person or group who is able to provide relevant, varied, and rich information for theory generation. Most used in grounded theory.
Non-probability (non-random) Sampling: Network
Holds promise for locating participants who would be difficult or impossible to obtain in other ways or who had not been previously identified for the study.
Non-probability (non-random) Sampling: Quota
Goal is to replicate the proportions of the subgroups present in the target population. Used to ensure the inclusion of participant types likely to be underrepresented.
Sample Size Calculation in Qualitative Study: Saturation of study data occurs when?
Additional sampling provides no new information, only redundancy of previous collected data.
- Scope of the study.
- Nature of the topic.
- Quality of the data.
- Study design.
