zkurtz
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Figure 7 in the paper seems to most-directly address the question of bias in the predictions. I don't fully understand the figure (specifically, the interpretation "estimated event probabilities are ...

I don't really understand this, but see here: Structural equation models and Bayesian networks appear so intimately connected that it could be easy to forget the differences. The structural ...

Yes, it should fail with a warning. The reasons cited in the OP are correct; here I'll simply derive an upper bound for kappa that proves the point. Define several "true" population level parameters:...

In this data, your two raters agreed 100% of the time (the function excludes all rows that include an NA). They both individually have a 100% estimated chance of selecting category "1". Thus, the ...

When n is large (like 300, even far less than 3000), the t-test is essentially the same as the z-test. That is, the t-test becomes nothing more than an application of the central limit theorem, which ...

Nonparametric quantile regression gives a very general approach that allows for both heteroscedasticity and nonlinearity. See section 9: http://www.econ.uiuc.edu/~roger/research/rq/vig.pdf UPDATE: ...

Equation 7 in Hersbach inspires me to notice that the RPS (as a discrete version of the continuous RPS, or CRPS) is a sum of several Brier quadratic probability scores (BS) evaluated over several ...

The OP appears to be seeking a high-quality survey of high-quality statisticians to help assess whether one particular book is of high quality particularly with regards to the AIC versus AICc debate. ...

This answer will likely be an iterative process, because you may want to rephrase your question as things become more clear. 1) In your usage, the first argument to crossbasis is a vector. According ...

Just sample pairs (X,Y) with replacement. You should not be permuting anything.

You seem to be aware that the marginal effect of $X_3$ is $\delta_1 + \delta_2 X_1 + \delta_3 X_2$, which is just the derivative of the response with respect to $X_3$. Replacing $X_1$ with $E(X_1)$ ...

The answer is 11. Given that the size of the first group is 10 times the size of the second, 11 is the smallest possible sample size that includes at least one observation. Now, you might say that ...

The short answer is that you seem to be on the right track. If you are on the wrong track in some way, it is because you seem to be searching for a precise definition for data mining, when in fact ...

Taking the question at face value, the answer is zero. The area under the standard normal density curve at any single point is the area of a line segment, which is always zero.

Pick a reference date, say 1/1/2010, and make a new variable time that is the difference between the date and the reference date, where the difference is computed in, say, days. Now run a linear ...

Rate A is 4/20 = 0.2. Rate B is 6/10 = 0.6. By "Is this statistically significant" I presume you mean, "is the difference between rate A and rate B statistically significant?" (And not "is the ...

Yes. A non-time series method that I have used (as a "hack") to model time series is a generalized additive model (GAM) with a nonparametrically-smoothed time effect. For example, using the mgcv ...

No. According to Gelman and Stern (2012), "even large changes in significance levels can correspond to small, nonsignificant changes in the underlying quantities." In plain English, differences ...

The short answer is that there is no particular reason to be surprised at what you are seeing. The use of p-values to decide which variables to include in a model is rather outdated, and most ...

You have identified most of the important issues. As you stated, direct measures of "CrossValidated usage" or "team productivity" may be difficult. Perhaps an even deeper issue is this: even if you ...

The canonical example of a distribution with no mean (and hence no variance) is the Cauchy distribution. True, you could compute the sample mean for a sample of data from a Cauchy distribution, but ...

Of course you are correct that the Poisson distribution technically is defined only for integers. However, statistical modeling is the art of good approximations ("all models are wrong"), and there ...

The first thing to understand is that the assumption of normality when using the t-test can never be proven. One can only say that the data look approximately normal, and if this is the case, the t-...

According to an informal document by Burnham, who I regard as one of the leading experts on the AIC, the notion that models need to be nested to use the AIC for model comparison is a myth. Here is ...