So assuming MAR a missing response doesn't mean bias in our slope estimates, but it does mean bias in our intercept estimates. This could be especially a problem in estimating the uncertainty we have in the intercepts. We are underestimating our uncertainty of them right now. Maybe.
Datetime is when the ride starts. I just learned that they also have ride end... That would have been useful.
I had a thought. what if I randomly assigned riders to rides. Would models perform similarly well if I added a random intercept then? How do I test if those gains were were due to the riders... and not just because I let the model give different sets of observations different values????
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