There is a bit of art and experience to model building. You need to build a model to answer your research question but how do you build a statistical model when there are no instructions in the box?
Ratios are everywhere in statistics—coefficient of variation, hazard ratio, odds ratio, the list goes on. You see them reported in the literature and in your output.
You comment on them in your reports. You even (kinda) understand them. Or, maybe, not quite?
Please join Elaine Eisenbeisz as she presents an overview of the how and why of various ratios we use often in statistical practice.
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?