Question 1

If too many participants are recruited, the whole study will be almost worthless because the sample will not have enough statistical power to answer the study question.

Accepted Answer

Recruiting too many participants does not decrease statistical power; it increases it. However, it may lead to unnecessary costs and complexity.

Question 2

If the power estimates for a study are lower than desired, the easiest way to improve the power is to increase the sample size.

Accepted Answer

Increasing the sample size reduces the standard error, leading to a more precise estimate of the effect size, which in turn increases the power of the study.

Question 3

The standard expectation is that a study's analyses should have a power of what value or greater?&#10;A) 60%&#10;B) 70%&#10;C) 80%&#10;D) 90%

Accepted Answer

A study's analyses are typically expected to have a power of 80% or greater to ensure a high probability of detecting a true effect if it exists.

Question 4

Which of the following is a statistical estimate of how close to the population value a sample of a particular size is expected to be?&#10;A) Chi-square statistic&#10;B) Confidence interval&#10;C) Study power&#10;D) p-Value

Accepted Answer

A confidence interval is a statistical estimate of how close to the population value a sample of a particular size is expected to be.

Question 5

What type of error occurs when a study population yields a significant statistical test result even though a significant difference or association does not actually exist in the source population?&#10;A) Type 1 error&#10;B) Type 2 error&#10;C) Type 3 error&#10;D) Type 4 error

Accepted Answer

A Type 1 error occurs when a study finds a statistically significant result when there is no actual effect or association in the population, leading to a false positive.

Deck 20: Sample Size and Power