- A review of basic concepts of statistical power and effect size
- A simulation-based approach to power analysis
- An overview of how to implement simulations in various popular software programs.
Here’s a common situation.
Your grant application or committee requires sample size estimates. It’s not the calculations that are hard (though they can be), it’s getting the information to fill into the calculations.
Every article you read on it says you need to either use pilot data or another similar study as a basis for the values to enter into the software.
You have neither.
No similar studies have ever used the scale you’re using for the dependent variable.
And while you’d love to run a pilot study, it’s just not possible. There are too many practical constraints — time, money, distance, ethics.
What do you do?
If you learned much about calculating power or sample sizes in your statistics classes, chances are, it was on something very, very simple, like a z-test.
But there are many design issues that affect power in a study that go way beyond a z-test. Like:
- repeated measures
- clustering of individuals
- including covariates in a model
Regular sample size software can accommodate some of these issues, but not all. And there is just something wonderful about finding a tool that does just what you need it to.
Especially when it’s free.
Enter Optimal Design Plus Empirical Evidence software. [Read more…] about Sample Size Estimates for Multilevel Randomized Trials