Sample Size and Power Question and Answer Flashcards

What is the goal when determining sample size in a study?

To recruit just the right number of participants—not too many and not too few.

What is a consequence of having too many participants in a study?

It wastes resources like time and money.

What risk does having too few participants pose?

It can lead to insufficient data to answer the study question.

What does sample size typically refer to in health sciences?

The number of individuals in the study population.

How does a larger sample size affect the sample estimates?

It provides estimates closer to the true population mean.

What is a census in the context of sample size?

An attempt to gather information about every individual in a population.

What is a Confidence Interval (CI)?

A statistical range that estimates likely values of a parameter in a source population.

What does a narrow Confidence Interval indicate?

More certainty about the value of the statistic.

What effect does small sample size have on Confidence Intervals?

It results in wider CI, leading to more uncertainty.

What is a 95% Confidence Interval?

A range where researchers can be 95% confident that the true mean falls within.

What does random error refer to in research?

Random differences between study results and true population values that occur by chance.

How can you reduce the impact of random error?

By increasing the sample size.

Define systematic error or bias.

A systematic flaw in study design or conduct that leads to inaccurate results.

What is the implication of a Type 1 Error?

A study shows a statistically significant result when there is no real difference.

What does a Type 2 Error represent?

A failure to detect a significant result when a real difference exists.

How is statistical power defined?

The ability of a statistical test to detect significant differences when they actually exist.

What is the typical power level aimed for in studies?

80% or greater.

What happens with studies that have too few participants?

They often lack the power to detect meaningful differences.

How does larger sample size impact statistical tests?

It increases the power of statistical tests.

What is the formula for calculating power?

Power is defined as 1 – β, where β is the probability of a Type 2 error.

What can be done if power estimates fall below desired levels?

Increase the sample size.

What does a sample size estimator do?

Identifies the appropriate number of participants for a quantitative study.

Why must the number of people sampled exceed the required number of participants?

Due to less than 100% participation rates.

What is random sampling?

A method to ensure a fair selection of participants.

What is the difference between a sample population and study population?

Sample population includes individuals invited to participate; study population includes actual participants.

What does the Greek letter alpha (α) represent?

Type 1 Error, typically set at 5%.

What is the implication of α = 5% in testing?

About 1 in 20 tests may show a statistically significant result purely by chance.

What happens if a study fails to detect true differences?

It represents a Type 2 Error.

What is meant by the term 'random differences' in research?

Unpredictable variations occurring by chance in measuring or sampling.

What is a confidence level typically set at?

95% in many studies.

How does sample size affect confidence intervals?

Larger sample sizes yield narrower confidence intervals.

What is systematic error also known as?

Bias.

How can one address bias in research?

By using random sampling and ensuring accurate measurement tools.

What does a power of 80% indicate?

There's an 80% chance of detecting a true effect or association.

What is the expected sample size used for?

To determine adequate power for the study.

What does it mean when CI is wide?

There is less certainty about the value of the statistic.

What happens to the sample mean with a larger sample?

It becomes closer to the true population mean.

What role do online calculators play in sample size estimation?

They provide sample size estimates based on study parameters.

What does the term 'confidence for anticipated exposure percentage' refer to?

It relates to the expected accuracy of estimates within the study.

In case-control studies, what is being compared?

Cases versus controls to find exposure likelihood.

What is implied when samples show non-significant results?

There may be substantial differences that are not detected due to small sample size.

What is the consequence of extreme values in a sample?

They can lead to random error affecting conclusions.

How does sample size impact the likelihood of statistically significant results?

Larger sample sizes increase the likelihood of obtaining significant results.

What should researchers consider regarding the number of participants contacted?

It should exceed the number needed due to anticipated low volunteer rates.

What is an example of a statistical power calculation from the lecture?

A study may require 500 participants to detect the anticipated outcomes.

Why might a researcher need to revise study design?

If the anticipated number of participants cannot be met.

What do effect size estimations rely on?

They rely on best guesses about expected findings.