- r - Effect size and GLM - Cross Validated
I use a GLM to find the best fit for my included explanatory variables I'm asked to estimate the effect size for this GLM and I can't find exactly what's about I founnd this R code: #Recent
- p value - Bonferonni versus FDR - Cross Validated
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- r - Beta distribution GLM with categorical independents and . . .
I suppose you could look at this two different ways: as true proportions; as binomial counts from a total; Option 2 would be a simple binomial GLM (binomial family, logit link [for starters]), but you need to have counts out of a total count; e g the number showing disease out of the total
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- HBO Max | If HBO Max is loading slowly, buffering, or pausing, find out . . .
HBO Max app: Press the Home button on your remote, then choose Apps > the Settings icon > Updates Samsung TV: Press the Home button on your remote, then navigate to the Settings icon Choose Support > Software Updates > Update Now Then, open HBO Max and try watching something
- Simulating data for repeated measures ANOVA - Cross Validated
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- machine learning - Is it ok to keep a very strong predictor and other . . .
This sort of thing often happens You don't give us much contest, but suppose you were predicting whether a person owned their own home Age would surely be a powerful predictor, bu I see no problem with adding other variables, whether weak or strong $\endgroup$ –
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