Podcast
Questions and Answers
What does statistical power refer to in hypothesis testing?
What does statistical power refer to in hypothesis testing?
- The likelihood of detecting a true effect (correct)
- The chance of rejecting a true null hypothesis
- The ability to produce false negatives
- The probability of obtaining a p-value greater than 0.05
Which of the following is an example of statistical significance?
Which of the following is an example of statistical significance?
- A p-value of 0.10
- A p-value of 0.06
- A p-value of 0.20
- A p-value of 0.03 (correct)
What is the purpose of a power analysis?
What is the purpose of a power analysis?
- To calculate the likelihood of a Type I error
- To analyze the validity of the research question
- To determine the minimum sample size for a study (correct)
- To find the statistical significance of the results
How can statistical power be improved in a study?
How can statistical power be improved in a study?
What is typically the most common threshold for statistical significance?
What is typically the most common threshold for statistical significance?
What does high statistical power indicate?
What does high statistical power indicate?
What is the main factor influencing statistical power?
What is the main factor influencing statistical power?
What happens if a study lacks sufficient power?
What happens if a study lacks sufficient power?
What type of error is a power analysis designed to minimize?
What type of error is a power analysis designed to minimize?
If the statistical power is set at 80%, how many studies would likely detect true effects out of 100 studies?
If the statistical power is set at 80%, how many studies would likely detect true effects out of 100 studies?
Which of the following correctly describes a power analysis?
Which of the following correctly describes a power analysis?
What could be a consequence of having too much statistical power?
What could be a consequence of having too much statistical power?
Which of the following statements about hypothesis testing is accurate?
Which of the following statements about hypothesis testing is accurate?
What is the significance level of a study typically set to?
What is the significance level of a study typically set to?
How does sample size affect the power of a study?
How does sample size affect the power of a study?
What does a higher significance level increase the risk of?
What does a higher significance level increase the risk of?
What might indicate the practical significance of a finding in a study?
What might indicate the practical significance of a finding in a study?
Which design is generally more powerful and requires fewer participants?
Which design is generally more powerful and requires fewer participants?
Which factor does NOT contribute to increasing the power of a statistical test?
Which factor does NOT contribute to increasing the power of a statistical test?
What complicates the interpretation of observed effect sizes in low-powered studies?
What complicates the interpretation of observed effect sizes in low-powered studies?
What is a consequence of high population variance on statistical tests?
What is a consequence of high population variance on statistical tests?
What is the relationship between effect size and sample size in a study?
What is the relationship between effect size and sample size in a study?
What strategy can improve power by reducing variability in your measurements?
What strategy can improve power by reducing variability in your measurements?
Which approach should only be used when there is a strong theoretical reason to expect a directional effect?
Which approach should only be used when there is a strong theoretical reason to expect a directional effect?
What could potentially inflate the observed effect size in low-powered studies?
What could potentially inflate the observed effect size in low-powered studies?
What is generally the consequence of utilizing a conservative significance level?
What is generally the consequence of utilizing a conservative significance level?
What is the main purpose of sample size calculations in a study?
What is the main purpose of sample size calculations in a study?
Which of the following factors does NOT determine the required sample size for a study?
Which of the following factors does NOT determine the required sample size for a study?
Which of the following best describes a Type I error?
Which of the following best describes a Type I error?
What consequence can arise from conducting small studies?
What consequence can arise from conducting small studies?
What does the term 'confidence interval' (CI) refer to in the context of sample size?
What does the term 'confidence interval' (CI) refer to in the context of sample size?
How can loss to follow-up impact the required sample size for a study?
How can loss to follow-up impact the required sample size for a study?
Why is it considered unethical to conduct a study with a very small sample size?
Why is it considered unethical to conduct a study with a very small sample size?
What is a potential drawback of conducting a study with a large sample size?
What is a potential drawback of conducting a study with a large sample size?
Which of the following describes a Type II error?
Which of the following describes a Type II error?
What key factor does NOT determine the required sample size for a study?
What key factor does NOT determine the required sample size for a study?
What is a potential consequence of conducting small studies?
What is a potential consequence of conducting small studies?
Which statement best explains imprecision in estimates from small studies?
Which statement best explains imprecision in estimates from small studies?
What approach to sample size considers the number of available patients?
What approach to sample size considers the number of available patients?
What is the main ethical consideration in determining sample size?
What is the main ethical consideration in determining sample size?
Why might a very small study be considered unreliable?
Why might a very small study be considered unreliable?
What is likely to happen if a sample size is too small?
What is likely to happen if a sample size is too small?
What minimum difference in BDI-II score between groups is considered significant enough to recommend CBT?
What minimum difference in BDI-II score between groups is considered significant enough to recommend CBT?
Which factor is NOT likely to affect the power of the study?
Which factor is NOT likely to affect the power of the study?
What is the standard deviation of BDI-II scores estimated for cancer patients in this study?
What is the standard deviation of BDI-II scores estimated for cancer patients in this study?
What is the primary outcome measure used to assess depression in this clinical trial?
What is the primary outcome measure used to assess depression in this clinical trial?
How can power be increased in the study described?
How can power be increased in the study described?
What is the primary outcome measure in the cognitive behavioural therapy study?
What is the primary outcome measure in the cognitive behavioural therapy study?
What degree of certainty is expected for detecting a treatment difference in the study?
What degree of certainty is expected for detecting a treatment difference in the study?
What minimum difference in BDI-II scores needs to be detected to recommend CBT for clinical practice?
What minimum difference in BDI-II scores needs to be detected to recommend CBT for clinical practice?
What is the expected mean BDI-II score for the control group in the study?
What is the expected mean BDI-II score for the control group in the study?
Which statistical test will be used to compare the mean scores at the 12-week follow-up?
Which statistical test will be used to compare the mean scores at the 12-week follow-up?
What is the expected standard deviation of BDI-II scores in cancer patients participating in the trial?
What is the expected standard deviation of BDI-II scores in cancer patients participating in the trial?
What type of treatment will the control group receive in the study?
What type of treatment will the control group receive in the study?
What is the maximum score on the Beck Depression Inventory II indicating severe depressive symptoms?
What is the maximum score on the Beck Depression Inventory II indicating severe depressive symptoms?
What percentage of participants remain after 20% attrition from a sample size of 125?
What percentage of participants remain after 20% attrition from a sample size of 125?
What is the adjusted sample size if the original sample size is 100 and the attrition is 20%?
What is the adjusted sample size if the original sample size is 100 and the attrition is 20%?
Which of the following reasons could lead to a p-value greater than 0.05?
Which of the following reasons could lead to a p-value greater than 0.05?
Why is it advised to avoid post hoc power calculations?
Why is it advised to avoid post hoc power calculations?
How is the adjusted sample size affected by a higher attrition rate of 25% compared to 20%?
How is the adjusted sample size affected by a higher attrition rate of 25% compared to 20%?
What effect does a Type II error have on research findings?
What effect does a Type II error have on research findings?
When is it necessary to adjust sample sizes for loss to follow-up?
When is it necessary to adjust sample sizes for loss to follow-up?
For which situation is performing a power analysis most crucial?
For which situation is performing a power analysis most crucial?
What effect does a smaller detectable difference have on the required sample size?
What effect does a smaller detectable difference have on the required sample size?
How does increased variability in an outcome affect the sample size requirement?
How does increased variability in an outcome affect the sample size requirement?
What is a consequence of expecting a loss to follow-up of 25% in a study with an initial required sample size of 126?
What is a consequence of expecting a loss to follow-up of 25% in a study with an initial required sample size of 126?
In calculating sample size, what does a significance level of 5% imply?
In calculating sample size, what does a significance level of 5% imply?
What happens to the sample size requirement when using a 1% significance level instead of a 5% significance level?
What happens to the sample size requirement when using a 1% significance level instead of a 5% significance level?
How does adjustment for baseline measurements typically affect required sample size?
How does adjustment for baseline measurements typically affect required sample size?
What can be concluded about hierarchical data structures in relation to sample size?
What can be concluded about hierarchical data structures in relation to sample size?
What is the impact of a 20% loss to follow-up on the sample size recruitment process?
What is the impact of a 20% loss to follow-up on the sample size recruitment process?
What is the effect of adjusting for a high intraclass correlation in clustered samples?
What is the effect of adjusting for a high intraclass correlation in clustered samples?
Which factor directly increases the required sample size to detect a specified effect size?
Which factor directly increases the required sample size to detect a specified effect size?
What must typically be determined from prior studies or consultations when assessing sample size?
What must typically be determined from prior studies or consultations when assessing sample size?
In the formula for sample size comparison of two means, what does $σ$ represent?
In the formula for sample size comparison of two means, what does $σ$ represent?
Which of the following factors is typically NOT specified when determining sample size?
Which of the following factors is typically NOT specified when determining sample size?
What is the typical significance level set in studies when calculating required sample size?
What is the typical significance level set in studies when calculating required sample size?
What does a higher Z score indicate in the context of determining sample size?
What does a higher Z score indicate in the context of determining sample size?
Which formula is used for calculating required sample size for binary outcomes?
Which formula is used for calculating required sample size for binary outcomes?
When assessing sample size, which of the following is true about statistical power?
When assessing sample size, which of the following is true about statistical power?
What is one of the main characteristics shared between the formula for comparing two means and two proportions?
What is one of the main characteristics shared between the formula for comparing two means and two proportions?
Flashcards
Statistical Power
Statistical Power
The likelihood of a statistical test detecting a true effect when it actually exists.
True Effect
True Effect
A real, non-zero relationship between variables in a population.
Power Analysis
Power Analysis
A calculation used to determine the minimum sample size needed for a study to have sufficient power.
Null Hypothesis
Null Hypothesis
Signup and view all the flashcards
Alternative Hypothesis
Alternative Hypothesis
Signup and view all the flashcards
Type II Error
Type II Error
Signup and view all the flashcards
Power Level
Power Level
Signup and view all the flashcards
Effect Size
Effect Size
Signup and view all the flashcards
Power
Power
Signup and view all the flashcards
Sample Size
Sample Size
Signup and view all the flashcards
Significance Level
Significance Level
Signup and view all the flashcards
Population Variance
Population Variance
Signup and view all the flashcards
Measurement Error
Measurement Error
Signup and view all the flashcards
Within-Subjects Design
Within-Subjects Design
Signup and view all the flashcards
Between-Subjects Design
Between-Subjects Design
Signup and view all the flashcards
Two-tailed Test
Two-tailed Test
Signup and view all the flashcards
One-tailed Test
One-tailed Test
Signup and view all the flashcards
Meta-analysis
Meta-analysis
Signup and view all the flashcards
Triangulation
Triangulation
Signup and view all the flashcards
Literature Review
Literature Review
Signup and view all the flashcards
Statistical Significance
Statistical Significance
Signup and view all the flashcards
Why is sample size important?
Why is sample size important?
Signup and view all the flashcards
What is a Type I error?
What is a Type I error?
Signup and view all the flashcards
What is a Type II error?
What is a Type II error?
Signup and view all the flashcards
What are the key factors that determine sample size?
What are the key factors that determine sample size?
Signup and view all the flashcards
Define statistical power.
Define statistical power.
Signup and view all the flashcards
What are the limitations of small studies?
What are the limitations of small studies?
Signup and view all the flashcards
How does sample size affect the precision of research findings?
How does sample size affect the precision of research findings?
Signup and view all the flashcards
How can a small sample size lead to publication bias?
How can a small sample size lead to publication bias?
Signup and view all the flashcards
Alpha Criterion
Alpha Criterion
Signup and view all the flashcards
What is the primary outcome measure?
What is the primary outcome measure?
Signup and view all the flashcards
How will the data be analysed?
How will the data be analysed?
Signup and view all the flashcards
What results are expected in the control group?
What results are expected in the control group?
Signup and view all the flashcards
How small a treatment difference needs to be detected?
How small a treatment difference needs to be detected?
Signup and view all the flashcards
With what degree of certainty?
With what degree of certainty?
Signup and view all the flashcards
What is the sample size formula for this study?
What is the sample size formula for this study?
Signup and view all the flashcards
Why is the sample size important?
Why is the sample size important?
Signup and view all the flashcards
What is the estimated standard deviation of the BDI-II score?
What is the estimated standard deviation of the BDI-II score?
Signup and view all the flashcards
Clinically Important Effect
Clinically Important Effect
Signup and view all the flashcards
Standard Deviation (SD) of the Outcome
Standard Deviation (SD) of the Outcome
Signup and view all the flashcards
Level of Statistical Significance
Level of Statistical Significance
Signup and view all the flashcards
Sample Size Formula for Two Means
Sample Size Formula for Two Means
Signup and view all the flashcards
Sample Size Formula for Two Proportions
Sample Size Formula for Two Proportions
Signup and view all the flashcards
Effect of Standard Deviation on Sample Size
Effect of Standard Deviation on Sample Size
Signup and view all the flashcards
Effect of Effect Size on Sample Size
Effect of Effect Size on Sample Size
Signup and view all the flashcards
Statistical Power (1-β)
Statistical Power (1-β)
Signup and view all the flashcards
Type II Error (β)
Type II Error (β)
Signup and view all the flashcards
Adjustment for Loss to Follow Up
Adjustment for Loss to Follow Up
Signup and view all the flashcards
Why is p>0.05?
Why is p>0.05?
Signup and view all the flashcards
Post Hoc Power Calculations
Post Hoc Power Calculations
Signup and view all the flashcards
Study Notes
Statistical Power and Significance
- Statistical power (sensitivity) is the probability of detecting a true effect if one exists in a study
- A true effect is a real, non-zero relationship or difference between variables in a population
- High power increases the chance of detecting a true effect
- Low power means a small chance of detecting a true effect, often due to random or systematic errors
- Power depends on sample size, effect size, and significance level
- Power analysis determines necessary sample size for a study
- Adequate power is crucial for accurate population conclusions from sample data
Hypothesis Testing
- Hypothesis testing involves null (no effect) and alternative (true effect) hypotheses
- The goal is to gather sufficient data to potentially reject the null hypothesis in favor of the alternative
Type I and Type II Errors
- A Type II error is failing to detect a true effect
- High power reduces the risk of a Type II error
- Power is usually set at 80%
- This means in 80 out of 100 studies with true effects, an effect will be detected
Power Analysis Components
- Power analysis involves four main components:
- Sample size
- Effect size
- Significance level
- Statistical power
- Knowing any three allows calculation of the fourth
- Traditional values for significance level and power are 5% and 80%.
Sample Size and Power
- Sample size is positively correlated with power
- Small samples (under 30) typically have low power; large samples have high power
- Increasing sample size enhances power, but marginal gains occur with very large samples
- Within-subjects designs are more powerful than between-subjects designs, requiring fewer participants
Significance Level
- Significance level is the probability of a Type I error (false positive)
- This is typically set at 5% (p<0.05)
- Increasing significance level (e.g., to 10%) increases power but increases Type I error risk
- Decreasing significance level (e.g., to 1%) increases the conservativeness of the test and reduces power
Effect Size
- Effect size is the magnitude of difference or relationship between variables.
- It indicates practical significance
- High-powered studies detect medium and large effects, low-powered studies typically, large ones less likely
Determining Effect Size
- Estimating effect size involves systematic literature reviews.
- Mean effect size from similar studies with similar manipulations and measures is utilized
Factors Affecting Power
- Population variability: high variability reduces power
- Measurement error: higher error reduces power
- Research design also influences power
- Sample size and variability influence the results
- An example is the different results of two studies using the drug streptokinase after a heart attack. The first Australian trial with a small sample size (517 participants) found no significant effect, while the ISIS-2 trial (17,187 participants) found a statistically significant effect. Different sample sizes can lead to conflicting conclusions.
Improving Power
- Increase effect size (e.g., stronger manipulations)
- Increase sample size (but diminishing returns)
- Increase significance level
- Reduce measurement error (improve precision and accuracy)
- Use a one-tailed test (if appropriate)
Statistical Significance
- Statistical significance means the observation is unlikely under the null hypothesis
- Significance is indicated by a p-value (probability value)
- Common threshold is p < 0.05
Additional Considerations
- Sampling error exists between observed and true effect sizes
- Observed effects in low-powered studies may be exaggerated by unrelated factors
- Various other research aspects influence power
- Too small of a sample size can lead to a lack of precision with results
- Ethical considerations need to be included when deciding how big the sample size should be for a study, and potential waste of resources (time and funding should be taken into account).
- Small studies with p<0.05 are more likely accepted for publication than small studies with p>0.05
- Sample size that is too large can lead to wasted resources.
- Different approaches to sample size determination exist, including statistical/scientific, economic, and ethical considerations for establishing sample size, along with credibility factors. Small studies may not yield reliable results, as they are more likely to result in publication bias.
Studying That Suits You
Use AI to generate personalized quizzes and flashcards to suit your learning preferences.
Related Documents
Description
This quiz covers key concepts related to statistical power, hypothesis testing, and types of errors in research studies. Understand how power influences the detection of true effects and the implications of Type I and Type II errors. Test your knowledge on the importance of adequate sample size and power analysis in drawing accurate conclusions.
