1. In the Falutz et al. (2010) tesamorelin trials, what was randomized 2:1?

Trial sites vs. control sites
Participants receiving tesamorelin vs. placebo
Researchers vs. reviewers
Countries participating in the trial

2. Why do most research compounds have far more in-vitro and animal-model literature than human trial data?

Animal studies are required by law before any publication
Human trials are slower, more expensive, and harder to run than earlier-stage research
Human data is never published
In-vitro studies are always more accurate than human trials

3. What does a p-value actually measure?

How large or clinically meaningful an effect is
How likely a result is to have occurred by chance if there were truly no effect
The exact percentage improvement a treatment provides
Whether a study was published in a reputable journal

4. Why can a very large study find a “statistically significant” result for an effect that is practically trivial?

Large studies always exaggerate effect sizes
A larger sample size makes it easier to distinguish even a small real effect from chance
Statistical significance is unrelated to sample size
Large studies are exempt from needing a control group

5. What is the “file-drawer problem”?

Researchers losing physical copies of their data
Studies with null or negative results being less likely to get published than positive ones
A rule requiring all trials to be registered before starting
A statistical method for combining multiple studies