Eli Kravitz

Medical statistician and obsessive dog owner. I use twitter to follow specific trustworthy news sources and scientific research. I'm boring, but well informed.

[Eli Kravitz @KravitzEl]

@RealMattKuhn @SickosCommittee Joey Chestnut was robbed

[Eli Kravitz @KravitzEl]

@rmkubinec It looks like the meta analysis was done on the log-odds scale then exponentiated. That’s why the regression line is curved.

[Eli Kravitz @KravitzEl]

@RitchieVink Pandas is so bad that people paid $4M to make something new.

[Eli Kravitz @KravitzEl]

@Ais4Action @rustymk2 Jelly Roll Morton wasn’t obese either.

[Eli Kravitz @KravitzEl]

@Lach_cribb It’s not strictly necessary. Each model term does something different. Intercept is average at t=0. Time is the overall trend. Everyone starts in a different place (random slope) and deviates slightly from the trend over time (random intercept), The remaining difference is error.

[Eli Kravitz @KravitzEl]

@Lach_cribb @matloff The idea of “de-correlating errors” might come from different, simpler models where you can’t include time as a covariate. In an analysis with two time points, random effects are the only way to induce correlation (that I’m aware of at least).

[Eli Kravitz @KravitzEl]

@sharoz @Lach_cribb This is a really nice illustration. Thanks for sharing.

[Eli Kravitz @KravitzEl]

@JamieLarsH @jimthommo Normal priors with large variances are standard for regression coefficients. The unknown precision parameters (inverse variance) for the random effects can be modeled with gamma distribution or uniform distribution.

[Eli Kravitz @KravitzEl]

@jimthommo @JamieLarsH Frequentist mixed models pool information across groups as well. This blog shows an example of that: https://t.co/AakXfYIbaR

[Eli Kravitz @KravitzEl]

@JamieLarsH Hierarchical models are the Bayesian analogue of Frequentist mixed models.

[Eli Kravitz @KravitzEl]

@AllisonLCarter Past Lives is great too!

[Eli Kravitz @KravitzEl]

@DeandaSharone @BariAWilliams @RobWPowell @theziturs @ProfMMurray That’s the Supreme Court’s interpretation. Bari’s suggestion would use the same logic the Supreme Court just rejected. If Biden did that, it would be rejected by the court for the same reason. They probably wouldn’t even take the case.

[Eli Kravitz @KravitzEl]

@Hornofplenty05 @PFF_College He’s focused. He’s having fun. I wouldn’t be surprised if he’s a dark horse for the Heisman.

[Eli Kravitz @KravitzEl]

@ShoarinejadA That’s not really a fair question. Those programming languages exist to do the MCMC sampling for you. There’s no Frequentist equivalent because you don’t need to draw samples when you fit Frequentist models.

[Eli Kravitz @KravitzEl]

@noah_greifer Germán Rodríguez has very detailed course notes that are easy to follow. I really recommend his notes over a specific textbook. https://t.co/3XWcJg5fHx

[Eli Kravitz @KravitzEl]

@super_jrub There might be some theory from functional data analysis. The abstract of this paper looks promising. If nothing else, it might have some good references. https://t.co/VIvbjcr3Cj

[Eli Kravitz @KravitzEl]

@jcomndz @super_jrub @ShenRaphael How would you bootstrap thag? Under the null, only two points (the value on each curve at the time point time point) are exchangeable.

[Eli Kravitz @KravitzEl]

@ChelseaParlett I’ve seen people check if their experimental data varies with time with this method. You would plot the principle components against the time axis to see if they’re correlated. You could do the same thing to see if the PCs vary by batch? https://t.co/Gb78688Gha

[Eli Kravitz @KravitzEl]

@SolomonKurz More dogs