Podcast
Questions and Answers
What is the primary purpose of using probability-based sampling in research studies?
What is the primary purpose of using probability-based sampling in research studies?
- To ensure equal chances of selection for all individuals in the source population (correct)
- To focus exclusively on specific subgroups of a population
- To reduce the overall sample size required for the study
- To include only the most willing participants
Which sampling method involves selecting every $10^{th}$ or $100^{th}$ individual from a list?
Which sampling method involves selecting every $10^{th}$ or $100^{th}$ individual from a list?
- Stratified random sampling
- Simple random sampling
- Systematic sampling (correct)
- Cluster sampling
What type of bias is present when individuals in the source population do not have an equal chance of being selected for a study?
What type of bias is present when individuals in the source population do not have an equal chance of being selected for a study?
- Random sampling bias
- Measurement bias
- Non-random-sampling bias (correct)
- Sampling bias
In stratified random sampling, what is done before selection occurs?
In stratified random sampling, what is done before selection occurs?
What is cluster sampling commonly based on?
What is cluster sampling commonly based on?
What is generalizability in research commonly referred to as?
What is generalizability in research commonly referred to as?
Why must convenience sampling be used with caution?
Why must convenience sampling be used with caution?
Which method combines snowball sampling with a mathematical model for weighting the sample?
Which method combines snowball sampling with a mathematical model for weighting the sample?
What is defined as a convenience population?
What is defined as a convenience population?
What does generalizability allow researchers to do with their findings?
What does generalizability allow researchers to do with their findings?
Why is it essential to include vulnerable populations in research studies?
Why is it essential to include vulnerable populations in research studies?
What is a key aspect of community-based participatory research (CBPR)?
What is a key aspect of community-based participatory research (CBPR)?
What is a negative consequence of recruiting too few participants in a research study?
What is a negative consequence of recruiting too few participants in a research study?
What is the role of community leaders in the research process?
What is the role of community leaders in the research process?
What factor is critical in determining the appropriate sample size for a research study?
What factor is critical in determining the appropriate sample size for a research study?
What is a Type 1 error in statistical testing?
What is a Type 1 error in statistical testing?
Which statement best describes Type 2 error?
Which statement best describes Type 2 error?
How can researchers minimize the likelihood of Type 2 errors?
How can researchers minimize the likelihood of Type 2 errors?
What is the relationship between Type 2 error rate (β) and statistical power?
What is the relationship between Type 2 error rate (β) and statistical power?
Why do sample size estimates typically refer to the study population instead of the sample population?
Why do sample size estimates typically refer to the study population instead of the sample population?
What is the primary purpose of determining an appropriate sample size in a quantitative study?
What is the primary purpose of determining an appropriate sample size in a quantitative study?
Which of the following statements about confidence intervals is true?
Which of the following statements about confidence intervals is true?
What is the impact of larger sample sizes on confidence intervals?
What is the impact of larger sample sizes on confidence intervals?
How is 'power' defined in the context of statistical tests?
How is 'power' defined in the context of statistical tests?
Which factor is important when using a sample size calculator?
Which factor is important when using a sample size calculator?
If the level of certainty about the inputs is low, what is the recommended course of action regarding sample size?
If the level of certainty about the inputs is low, what is the recommended course of action regarding sample size?
Which of the following is not a consequence of larger sample sizes in statistical studies?
Which of the following is not a consequence of larger sample sizes in statistical studies?
What is the formula for calculating power in statistical analysis?
What is the formula for calculating power in statistical analysis?
Study Notes
Sample Populations
- A sample population is a subset of a source population who are invited to participate in a research project.
- Probability-based sampling is used when a sample population is representative of the source population.
- Non-random-sampling bias occurs when each individual does not have an equal chance of being selected for the sample population.
Probability-Based Sampling
- Simple random sampling: Every person has an equal probability of being selected.
- Systematic sampling: Individuals are selected from a list or inventory, for example, every 10th or 100th person.
- Stratified random sampling: The population is divided into groups based on a characteristic before selection.
- Cluster sampling: A sample is divided into clusters, typically based on naturally-occurring groups.
Study Populations
- Study population: Eligible members of the sample population who consent to participate in the study and complete required study activities
Generalizability
- Generalizability refers to the applicability of study findings to a broader population.
- Also known as "external validity" or "representativeness."
Convenience Samples
- Convenience populations are nonprobability-based source populations selected due to ease of access.
- Convenience sampling must be used with caution as results may not be representative of the target population.
Non-Probability Sampling
- Chain/snowball/referral sampling: Participants are encouraged to invite others to participate.
- Respondent-driven sampling: Combines "snowball sampling" with a mathematical model to weight the sample.
Community Involvement
- Community-based participatory research (CBPR): Partnerships in which community members identify research priorities and are involved in every stage of the research process.
Importance of Sample Size
- Recruiting too many participants: Wastes resources.
- Recruiting too few participants: Makes the study invalid.
- Sample size and certainty levels: The desired sample size is based on statistical estimations about how many data points are required to answer the study question with a specified level of certainty.
Mean
- The mean is the average value of a variable, calculated by adding up all values and dividing by the total number of individuals.
Confidence Interval
- A confidence interval is a statistical estimate of the range of likely values of a parameter in a source population based on the value of that statistic in a study population.
Sample Size Estimation
- Sample size calculators: Tools used to identify an appropriate number of participants for a quantitative study.
- Power estimation: The ability of a statistical test to detect significant differences between subgroups of a population when differences really do exist.
Type 1 and Type 2 Errors
- Type 1 (alpha) error: A statistically significant test result is obtained when no significant difference or association actually exists.
- Type 2 (beta) error: A statistically insignificant test result is obtained when a significant difference or association actually exists.
Refining the Study Approach
- If the estimated number of available participants is not sufficient, the study approach may need to be rethought.
- The number of people sampled for a study must be larger than the required number of participants because the participation rate is unlikely to be 100%.
Next Class
- October 23, 2024
- Topics: Questionnaire Development, Surveys/Questionnaires, Collecting Quantitative Data
- Chapters 21, 22
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Description
This quiz covers essential concepts related to sample populations and probability-based sampling methods. You will explore different sampling techniques including simple random sampling, systematic sampling, stratified random sampling, and cluster sampling. Test your understanding of biases and the study population involved in research.
