Meta-analysis is the quantitative pooling of data from multiple studies. Meta-analysis done well has many strengths, including statistical power,
precision in effect size estimates, and providing a summary of individual studies.
Most analysts would respond, “a mixed model,” but have you ever heard of latent growth curves? How about latent trajectories, latent curves, growth curves, or time paths, which are other names for the same approach?
Most of us know that binary logistic regression is appropriate when the outcome variable has two possible outcomes: success and failure.
There are two more situations that are also appropriate for binary logistic regression, but they don’t always look like they should be.
Statistics is, to a large extent, a science of comparison. You are trying to test whether one group is bigger, faster, or smarter than another.