Sampling
The goal of appropriate sampling in research is to:
a. accurately reflect the characteristics of the target population.
b. completely define the traits of the accessible population.
c. identify all attributes of the sample population.
d. study an entire population.
Correct answer (A)
A researcher wishes to evaluate the management of chemotherapy side effects in children with acute lymphocytic leukemia (ALL). Children with ALL in this study are an example of which of the following?
a. Accessible population
b. Element of the population
c. Sample population
d. Target population
Correct answer: D
A researcher enters a list of subjects from a sampling frame into a computer and the computer randomly assigns subjects to control or treatment groups. This is an example of
a. cluster sampling.
b. simple random sampling.
c. stratified random sampling.
d. systematic sampling.
B: Simple random sampling is the most basic of the probability sampling plans and is achieved by randomly selecting elements from the sampling frame. It can be done by computer, as in this case. Cluster sampling occurs when the researcher selects subjects from groups of subjects within the larger population, as with groups from specific regions or cities. Stratified random sampling occurs by ensuring that the proportions of characteristics among the population are represented in both the control and experimental groups. Systematic sampling is used when an ordered list of all members of the population is available and involves selecting every kth individual on the list.
A researcher conducts a pilot study using a convenience sample of children with seizure disorders. A reviewer of this study’s manuscript may conclude that the findings of this study
a. are generalizable to most children with seizures.
b. have little credibility; they are extremely biased.
c. provide no useful information.
d. should be replicated using a wider population.
D: Representativeness of the sample is a concern in convenience sampling, and generalizability is therefore limited. In a convenience sample, representativeness of the sample is a concern, and generalizability is therefore limited. Not all studies with a convenience sample are more biased than studies with other sampling methods. Intervention studies with a convenience sample can certainly provide useful information, even though further testing might be needed to be able to apply the findings to a large population.
A researcher tests a measurement tool in a pilot study and notes a wide variance in scores. To improve the significance of the study’s findings in subsequent studies, the researcher will
a. apply quota sampling techniques.
b. decrease the sample size.
c. increase the sample size.
d. use cluster sampling techniques.
C: As variance in instrument scores increases, the sample size needed to obtain significance increases, so the researcher should increase the sample size in subsequent studies. Quota and cluster sampling techniques help to increase the representativeness of the sample but do not affect the significance of the measurement findings.
The benefit to using a sample that utilizes narrow sampling criteria is that there is increased
a. control of extraneous variables.
b. generalizability.
c. heterogenicity.
d. range of values and scores.
A:A sample that is narrowly defined is more homogeneous and has greater control of extraneous variables. The narrower the sample, the less generalizable it is. A narrow sample is homogeneous, not heterogeneous. A narrow sample will have a smaller range of values and scores.
A researcher wishes to study the effects of a nursing intervention on children with cancer and obtains a sample of school-age children hospitalized for cancer treatment in a local hospital. This sample represents the
a. accessible population.
b. general population.
c. target population.
d. theoretical population.
A: An accessible population is the portion of the target population to which the researcher has reasonable access. The sample is obtained from the accessible population. A general population is the population, not just those meeting eligibility criteria. The target population is the entire set of individuals who meet the sampling criteria. The theoretical population is the same as the target population, which is the entire set of individuals who meet the sampling criteria.
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. A patient who is 65 years old meets
a. eligibility criteria.
b. exclusion criteria.
c. inclusion criteria.
d. sampling criteria.
B: Exclusion criteria are characteristics that the researcher does not want in the elements or subjects of the study. Inclusion criteria, eligibility criteria, and sampling criteria are those characteristics that the subject or element must possess to be part of the target population.
Which of these sampling techniques is least likely to produce findings that are generalizable to a larger population?
a. Cluster
b. Convenience
c. Quota
d. Systematic
B: There is little opportunity to control for bias in a convenience sample. Cluster sampling is a type of random sampling and is much stronger than convenience sampling. Quota provides for a more representative sample than convenience sampling, so it is stronger. Systematic sampling is a type of random sampling and is much stronger than convenience sampling.
Which statement is true about effect size?
a. There is one type of effect size measure used in research studies.
b. The effect size is the extent to which the null or statistical hypothesis is true.
c. The effect size is the extent to which the null or statistical hypothesis is false.
d. When the effect size is small, detecting it is easier and can be done with a smaller sample.
C: The effect size is the extent to which the null or statistical hypothesis is false. In other words, the strength of the expected relationship between two variables or differences between two groups. There are different types of effect size measures and each corresponds to the type of statistic computed. When the effect size is large, detecting it is easier and can be done with a smaller sample.
A researcher uses a sample whose members have characteristics like those of the population from which it is drawn. This is an example of a
a. cluster sample.
b. purposive sample.
c. random sample.
d. representative sample.
D: Representativeness means that the sample, accessible population, and target populations are alike in as many ways as possible. Knowing a sample as a cluster sample, purposive sample, or random sample tells how it was created but does not define a representative sample.
A pilot study reveals a wide variation in measurement values among subjects with an overall mean value that is higher than among the general population. By increasing the sample size in a subsequent study, the researcher expects to
a. decrease the variation of scores among subjects.
b. increase the variation of scores among subjects.
c. decrease the mean value of scores among subjects.
d. increase the mean value of scores among subjects.
A: The random variation of scores is the expected difference in values that occurs when different subjects from the same sample are examined. As sample size is increased, this variation decreases. The systematic variation is related to selecting subjects whose measurement values differ from those of the population. Increasing the sample size has no effect on mean scores.
A researcher who wishes to study the effects of a prenatal breastfeeding education program on the length of time African-American inner-city women breastfeed infants learns that 70% of women in the target population are unmarried. To achieve stratified random sampling in a sample of 50 subjects, the researcher will
a. conduct the study using unmarried subjects only.
b. randomly assign all subjects to control versus experimental groups.
c. select a random sample of 35 unmarried and 15 married subjects.
d. select 25 subjects who are married and 25 who are not married.
C: Stratified random sampling is used when the researcher knows some of the variables in the population that are critical for achieving representativeness, such as marital status. In this case, subjects are randomly selected, but stratification by marital status to match the target population proportions helps to improve generalizability of the findings. Using only married subjects makes the results ungeneralizable to unmarried subjects. Randomly assigning subjects without stratification does not make the groups representative. Having equal numbers from each group is possible if subjects are randomly assigned and not selected.
A nurse conducts a study to examine the effects of a new intervention on FEV1 levels in patients with COPD and uses all patients admitted to a hospital during a 2-month period. This is an example of which type of sampling method?
a. Convenience
b. Network
c. Quota
d. Random
A: In convenience sampling, the researcher uses subjects as they are available until the desired sample size is reached. Network sampling uses social networks to obtain subjects who might not be readily accessible otherwise. Quota sampling involves convenience sampling but adds techniques to ensure that certain subject types are represented. Random sampling attempts to ensure that all potential subjects have equal, random chances to participate.
A researcher will conduct a qualitative study about partners of patients diagnosed with sexually transmitted diseases. This researcher will use which sampling technique to achieve the best representation of this population?
a. Accidental sampling
b. Cluster sampling
c. Network sampling
d. Simple random sampling
C: Network sampling is useful for locating samples that are difficult or impossible to obtain in other ways. Network sampling takes advantage of social networks and the fact that friends tend to have characteristics in common. Accidental or convenience sampling would not be likely to yield an adequate sample of individuals with sexually transmitted diseases. Cluster sampling would not be the best method for finding the desired sample in this case. Simple random sampling would not work well because the researcher is looking for a specific subgroup of the general population.
A researcher begins a study with 250 subjects, and 50 subjects drop out before the study is concluded. The researcher will declare 20% as the sample
a. acceptance rate.
b. attrition rate.
c. refusal rate.
d. retention rate.
B: The sample attrition rate is the percentage of subjects who withdraw from a study after the study has begun. The acceptance rate is the percentage of subjects who meet eligibility requirements who consent to participate. The refusal rate is the percentage of subjects who meet eligibility requirements who refuse to participate. The retention rate is the percentage of subjects who remain in the study after the study has begun.
A researcher wishes to identify all school-age children who have type 2 diabetes mellitus in a local community to develop a sampling methodology for a study of this population. Which might serve as a barrier to obtaining this information?
a. Affordable Care Act (ACA)
b. Consolidated Omnibus Budget Reconciliation Act (COBRA)
c. Health Insurance Portability and Accountability Act (HIPAA)
d. Institutional Review Board (IRB)
C: HIPAA contains guidelines about sharing patient information and may serve as a barrier to obtaining names of potential subjects. The ACA does not address the sharing of patient information. COBRA is concerned with healthcare coverage after termination of coverage. IRBs govern the use of human subjects in research.
When using stratified random sampling, the researcher can
a. achieve greater control over subject selection.
b. avoid discussion of the effects of extraneous variables.
c. lower the costs associated with sampling.
d. use a smaller sample size.
D: With stratification, the researcher can use a smaller sample size and achieve the same degree of representativeness in relation to the stratified variable as a large sample acquired through simple random sampling. The researcher does not achieve greater control of subject selection, since random selection is still used. Discussion of extraneous variables should always occur, even with stratified random sampling techniques. There is no guarantee that costs will be less with this type of sampling technique.
A researcher wishes to examine whether a teaching program for parents increases adherence to a drug regimen among children with seizure disorders. A convenience sample of children in a large teaching hospital is proposed. To prevent confounding of the results by socioeconomic status and type of health insurance, the researcher will utilize which additional sampling technique?
a. Cluster
b. Network
c. Quota
d. Theoretical
C: Quota sampling involves convenience sampling but adds techniques to ensure that certain subject types are represented. Cluster sampling occurs when the researcher selects subjects from groups of subjects within the larger population, as with groups from specific regions or cities. Network sampling uses social networks to obtain subjects who might not be readily accessible otherwise. Theoretical sampling is used in qualitative research to develop a selected theory. Subjects are selected based on their ability to provide relevant, varied, and rich information for theory generation.
The type of nonprobability design that is most likely to yield a representative sample is
a. convenience sampling.
b. accidental sampling.
c. quota sampling.
d. network sampling.
C: Quota sampling involves convenience sampling but adds techniques to ensure that certain subject types are represented. Convenience sampling, also called accidental sampling, is a relatively weak approach because it provides little opportunity to control for biases. Network sampling uses social networks to obtain subjects who might not be readily accessible otherwise.
To decrease the probability of systematic variation in a study to evaluate the effects of a teaching program on disease management, the researcher will use which sampling process?
a. Cluster sampling
b. Convenience sampling
c. Random sampling
d. Systematic sampling
C: Random sampling decreases the probability of systematic bias. Cluster, convenience, and systematic sampling increase the risk that the sample population has attributes that differ from the general population.
A researcher plans to utilize a systematic random sampling method from a population of 5000 eligible subjects, using a sample of 200 subjects. Beginning at a randomly selected point on the list of subjects, what is the gap between elements?
a. 25
b. 50
c. 100
d. 200
A: In systematic sampling, the researcher selects every kth individual on a list, beginning at a randomly selected starting point. The population size is divided by the desired sample size to give the gap between elements. 5000/200 = 25. A gap of 50 between elements would be correct for a sample size of 100 subjects. A gap of 100 between elements would be correct for a sample size of 50 subjects. A gap of 200 between elements would be correct for a sample size of 25 subjects.
When conducting a study in which it is not possible to determine the true number of subjects who meet eligibility criteria and obtaining a random sample would be time consuming and expensive, the researcher will use which sampling method?
a. Cluster sampling
b. Simple random sampling
c. Stratified random sampling
d. Systematic sampling
A: Cluster sampling is often used when the researcher is unable to identify the individual elements making up the population and when obtaining a random sample is time consuming or expensive. Simple random sampling is the most basic random sampling technique and is usually used when the population is clearly identifiable. Stratified random sampling is used when the researcher knows some of the variables in the population that are critical for achieving representativeness. Systematic sampling is used when an ordered list of all members of the population is available and involves selecting every kth individual on the list.
Prior to initiating a research study, a researcher conducts a power analysis to determine the sample size necessary for a power level of 0.8 and an alpha of 0.05. The researcher will
a. apply a quota sampling technique to improve generalizability.
b. decrease the sample size to minimize costs.
c. increase the sample size to avoid a type II error.
d. use stratified random sampling to minimize error.
C: The minimum acceptable level of power for a study is 0.8, which results in a 20% chance of a type II error. This study has a 40% chance of such an error and is unacceptable. To increase the power, the researcher should increase the sample size. Quota sampling and stratified random sampling do not necessarily affect a study’s power.
In quantitative research, you need to evaluate representativeness in terms of the setting, characteristics of the subjects, and distribution of values on variables measured.
b. Representativeness means that the sample, accessible population, and target population are different in as many ways as possible.
c. The setting identified in a study does not influence the representativeness of the sample.
d. Researchers who gather data from subjects across a variety of settings have a more representative sample of the target population than those limiting the study to a single setting.
e. A sample must be representative in terms of characteristics such as age, gender, ethnicity, income, and education, which often influence study variables.
A,D,E: In quantitative research, you need to evaluate representativeness in terms of the setting, characteristics of the subjects, and distribution of values on variables measured. Researchers who gather data from subjects across a variety of settings have a more representative sample of the target population than those limiting the study to a single setting. A sample must be representative in terms of characteristics such as age, gender, ethnicity, income, and education, which often influence study variables. Representativeness means that the sample, accessible population, and target population are alike in as many ways as possible. The setting identified in a study does influence the representativeness of the sample. Studies that obtain data from large databases have more representative samples.