Flashcards in Chapter 7 Selecting the Sample and Setting Deck (44)

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## Accessible population

### Population that is *readily available* to the researcher and that represents the target population as closely as possible.

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## Cluster sampling

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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.

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## Convenience sampling

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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.

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## External validity

### Extent to which results of a study can be *generalized* from the study sample to other populations and settings.

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## Network sampling

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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.

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## Nonprobability sampling

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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.

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## Population

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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.

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## Probability sampling

### Type of sampling in which every subject, object, or element in the population has an *equal* chance or probability of being chosen.

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## Purposive sampling

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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.

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## Quota sampling

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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*.

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## Random assignment

### Allocation of subjects to either an experimental or a control group.

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## Random selection

### Type of selection in which each subject has an equal, independent chance of being selected.

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## Sample

### A subset of a population; must *represent* the larger population.

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## Sampling

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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.

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## Sampling frame

### A *list of all elements* (subjects, objects, events, or units) in a population.

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## Simple random sampling

### Method of selecting subjects for a sample, in which every subject has an *equal* chance of being chosen.

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## Snowball sampling

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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).

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## Stratified random sampling

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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.

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## Systematic sampling

### Type of sampling in which every πth (where "π" is some convenient number) member of the population is selected into the sample.

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## Target population

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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.

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## Types of probability sampling

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1. Simple random sample.

2. Stratified random sample.

3. Proportional.

4. Disproportional.

5. Cluster (multistage) sample.

6. Systematic sample.

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## Types of nonprobability sampling

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1. Convenience (accidental).

2. Snowball.

3. Network.

4. Quota sample.

5. Purposive sample.

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## π refers to the _

### Sampling interval in *systematic sampling*.

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## Many nursing research studies use nonprobability sampling because of _

### The difficulties in obtaining random access to populations.

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## Disadvantages of convenience sampling

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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.

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## _ is used when limiting a population is not possible.

### Snowball sampling.

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## 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.

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## 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.

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## Power 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.

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