How Do You Handle Missing Values in Panel Data Analysis? or What Are the Best Practices for Modeling

"Fixed Effects vs. Random Effects: Which Works Better for Your Panel Data?"

Hey everyone!

I’m kinda new to panel data analysis and keep getting stuck on this one thing—when should I use fixed effects vs. random effects? Like, I get the basics, but how do you *actually* decide which one fits your data better?

Some folks say fixed effects are safer ‘cause they control for unobserved heterogeneity, but others swear by random effects for efficiency. What’s your go-to approach?

Also, any tips on running Hausman tests without pulling your hair out? 😅

Thanks in advance!

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*P.S. If you’ve got favorite resources or gotchas to watch for, drop ‘em below!*