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  1. Jake

    R squared and correlation in R

    In your own example, r = 0.53 and R^2 = 0.28....so clearly they're not the same.
  2. Jake

    SAS v R

    Feel free to explain the methodological problems you spotted.
  3. Jake

    SAS v R

    There is data. There is data. There is data. There is data. There is data. There is data. http://r4stats.com/articles/popularity/ You cannot keep ignoring this and spewing this unfounded **** about SAS being more popular than R in general. Are there specific pockets of industry where SAS is more...
  4. Jake

    What podcasts do you enjoy or listen to?

    I enjoy Very Bad Wizards
  5. Jake

    Unobserved heterogeneity in logistic regression

    Yes, I agree. We discussed that in the chatbox starting with the following two chats:
  6. Jake

    Unobserved heterogeneity in logistic regression

    Thanks, yes, this is an excerpt from Pearl's book, which I own and have read. I've definitely re-read that section several times while working on my blog post.
  7. Jake

    Bayesian Posterior: SD = SE?

    Technically the answer to this is always no, since these two quantities have totally different conceptual meanings -- one is the SD of the marginal posterior distribution for a parameter, one is the SD of the sampling distribution of the estimate of the parameter. With that said, we might still...
  8. Jake

    Unobserved heterogeneity in logistic regression

    spunky: And this only works when you have like a continuous covariate and a categorical predictor? spunky: Or is it irrespective of the type of data? Jake: so now we can imagine that for any logistic regression equation that we estimate, there's almost certainly lots of variables we omitted that...
  9. Jake

    Unobserved heterogeneity in logistic regression

    Pasted from the TS chatbox: Jake: i'm working on a blog post about the whole unobserved-heteogeneity-in-logistic-regression thing Jake: it's like 1/3rd written spunky: I was curious of what was going on with that blog. I'm writing one post myself about a little surprising result within linear...