Chapter 7 Selecting the Sample and Setting

Question 1

Accessible population

Answer 1

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

Question 2

Cluster sampling

Answer 2

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.

Question 3

Convenience sampling

Answer 3

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.

Question 4

External validity

Answer 4

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

Question 5

Network sampling

Answer 5

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.

Question 6

Nonprobability sampling

Answer 6

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.

Question 7

Population

Answer 7

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.

Question 8

Probability sampling

Answer 8

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

Question 9

Purposive sampling

Answer 9

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.

Question 10

Quota sampling

Answer 10

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.

Question 11

Random assignment

Answer 11

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

Question 12

Random selection

Answer 12

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

Question 13

Sample

Answer 13

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

Question 14

Sampling

Answer 14

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.

Question 15

Sampling frame

Answer 15

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

Question 16

Simple random sampling

Answer 16

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

Question 17

Snowball sampling

Answer 17

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).

Question 18

Stratified random sampling

Answer 18

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.

Question 19

Systematic sampling

Answer 19

Type of sampling in which every 𝑘th (where “𝑘” is some convenient number) member of the population is selected into the sample.

Question 20

Target population

Answer 20

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.

Question 21

Types of probability sampling

Answer 21

1. Simple random sample.
2. Stratified random sample.
3. Proportional.
4. Disproportional.
5. Cluster (multistage) sample.
6. Systematic sample.

Question 22

Types of nonprobability sampling

Answer 22

1. Convenience (accidental).
2. Snowball.
3. Network.
4. Quota sample.
5. Purposive sample.

Question 23

𝑘 refers to the _

Answer 23

Sampling interval in systematic sampling.

Question 24

Many nursing research studies use nonprobability sampling because of _

Answer 24

The difficulties in obtaining random access to populations.

Question 25

Disadvantages of convenience sampling

Answer 25

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.

Question 26

_ is used when limiting a population is not possible.

Answer 26

Snowball sampling.

Question 27

In qualitative studies, the sample size should be _

Answer 27

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.

Question 28

In quantitative studies, the sample size should be _

Answer 28

Linked to data collection and the type of analysis; researchers should consider the purpose of the study, research design, sampling method, and data analysis.

Question 29

Power analysis

Answer 29

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.

Question 30

The object of sampling is to _

Answer 30

Have a sample as representative as possible with as little sampling error as possible.

Question 31

Samples that are biased or too small threaten the _ of the design.

Answer 31

External validity.

Question 32

Three things that can threaten external validity

Answer 32

1. Sampling and selection - the more specific the criteria, the less generalizable the results will be. 2. Setting - when subjects are chosen who are themselves similar but who exist in different settings (e.g., rehabilitation hospitals vs. nursing homes), the setting itself may become a variable that limits generalizability. 3. History - it may be inappropriate or impossible to generalize results to different periods in the past or future.

Question 33

You decide to select a sample of 100 subjects of whom 10% will be African American, 10% Hispanic, and 80% white. Identify the appropriate sampling design.

Answer 33

Quota sampling.

Question 34

The population from which the researcher selects the research sample is commonly referred to as the _

Answer 34

Accessible population.

Question 35

The purpose of defining inclusion criteria and exclusion criteria is to _

Answer 35

Control for extraneous variability or bias that would limit the strength of evidence.

Question 36

Nonprobability sampling is appropriate for _

Answer 36

Qualitative methods.

Question 37

Disproportionate sampling in stratified random sampling is appropriate when _

Answer 37

There are under-represented groups; the researcher can then weight the statistical data accordingly so that legitimate comparisons can be made.

Question 38

_ is widely used in national surveys.

Answer 38

Cluster sampling.

Question 39

Type I error

Answer 39

A false positive (detecting something that was not actually there) - the researcher rejected a null hypothesis that was true.

Question 40

Type II error

Answer 40

1. A false negative (failing to detect something that was present) - the researcher accepted a null hypothesis that was false. 2. Occurs when a sample size *is not large enough* ("underpowered") - can minimize through the use of power analysis.

Question 41

Natural or field setting

Answer 41

When the researchers go where the participants are, in their environment. The researcher does not manipulate the setting in any way. Used in *qualitative research*.

Question 42

Partially controlled setting

Answer 42

The researcher manipulates/modifies the setting in some way, such as using an ICU to collect data. Commonly used with correlational, quasi-experimental and experimental studies.

Question 43

Highly controlled setting

Answer 43

An artificial environment created solely for purpose of research, such as research units/centers, and laboratories. Controls extraneous variables and allows the researcher to examine effect of the independent variable on the dependent variable.

Question 44

Internal validity

Answer 44

Whether the independent variable is really responsible for the change in the dependent variable - threatened when extraneous variables exist.