Flashcards in Chapter 7 Selecting the Sample and Setting Deck (44)
Population that is *readily available* to the researcher and that represents the target population as closely as possible.
1. Type of sampling in which the researcher randomly selects *groups of subjects* rather than individual subjects; also called multistage sampling.
2. Used for convenience when the population is very large or spread over a wide geographic area.
1. Type of nonprobability sampling in which the researcher selects subjects or elements *readily available*; also called accidental sampling.
2. Subjects are not selected from a larger group; the researcher collects data from whomever is available and meets the study criteria.
3. Includes snowball sampling and network sampling.
Extent to which results of a study can be *generalized* from the study sample to other populations and settings.
1. Type of nonprobability sampling that takes advantage of *social networks*.
2. When the researcher has found a few subjects with the needed criteria, these individuals are asked to help the researcher get in touch with others having similar characteristics.
3. Biases: Subjects are not independent of each other; subjects volunteer to participate.
1. Type of sampling in which the sample is not selected using random selection.
2. Disadvantage: The sample chosen may not represent the larger population.
1. Entire set of subjects, objects, events, or elements being studied (not restricted to humans); also called the target population.
2. Tends to be inferred rather than directly stated.
Type of sampling in which every subject, object, or element in the population has an *equal* chance or probability of being chosen.
1. Type of nonprobability sampling in which the researcher selects only subjects that *satisfy prespecified characteristics*; also called judgmental or theoretical sampling.
2. Allows the researcher to handpick the sample, but sampling bias is a concern.
3. Commonly used in qualitative research.
1. Type of nonprobability sampling in which quotas are filled.
2. Similar to stratified random sampling except that subjects are *not* randomly selected for each stratum. Subjects are solicited via *convenience sampling*.
Allocation of subjects to either an experimental or a control group.
Type of selection in which each subject has an equal, independent chance of being selected.
A subset of a population; must *represent* the larger population.
1. The process of selecting a subset from a larger population. (No sampling technique *guarantees* a representative sample, however.)
2. When conducted properly, it allows the researcher to draw inferences and make generalizations about the population without examining every element in the population.
A *list of all elements* (subjects, objects, events, or units) in a population.
Simple random sampling
Method of selecting subjects for a sample, in which every subject has an *equal* chance of being chosen.
1. Type of nonprobability sampling that relies on *subjects identifying other subjects with similar characteristics*.
2. Useful when one cannot get a list of individuals who share a particular characteristic - studies in which the criteria for inclusion specify a trait that is ordinarily difficult to find (e.g., undocumented immigrants).
Stratified random sampling
1. Type of random sampling in which the population is divided into *subpopulations, or strata*, on the basis of one or more variables, and a *simple random sample is drawn from each stratum*.
2. Examples of stratifying populations: By age, gender, ethnicity, socioeconomic status, diagnosis, occupation, year of immigration, etc.
Type of sampling in which every 𝑘th (where "𝑘" is some convenient number) member of the population is selected into the sample.
1. Population for which study outcomes are intended. Although the intended (target) population is usually evident, having access to members of this population (accessible) can be difficult.
2. The *entire* set of elements about which the researcher would like to make generalizations.
Types of probability sampling
1. Simple random sample.
2. Stratified random sample.
5. Cluster (multistage) sample.
6. Systematic sample.
Types of nonprobability sampling
1. Convenience (accidental).
4. Quota sample.
5. Purposive sample.
𝑘 refers to the _
Sampling interval in *systematic sampling*.
Many nursing research studies use nonprobability sampling because of _
The difficulties in obtaining random access to populations.
Disadvantages of convenience sampling
1. The potential for sampling bias.
2. The use of a sample that may not represent the population.
3. Limited ability for results to be generalized.
_ is used when limiting a population is not possible.
In qualitative studies, the sample size should be _
Large enough to accomplish the goal of the study; the exact number of subjects may not be determined in advance and sampling may continue until the phenomenon under study becomes clear.
In quantitative studies, the sample size should be _
Linked to data collection and the type of analysis; researchers should consider the purpose of the study, research design, sampling method, and data analysis.
A statistical procedure that can calculate the exact number of subjects needed for a research study, based on the number of variables and study design.