Unanswered Questions
71,464 questions with no upvoted or accepted answers
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What techniques are there to measure goodness of fit of Deming (orthogonal) regression?
Questions:
Even if there is no "widely accepted" technique, is there a useful-and-above-average technique for estimating goodness of fit in orthogonal regressions?
What are the pros/cons of this ...
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Errors-in-Variables model for logistic regression
Simple question: I am familiar (though don't have tons of experience) with errors-in-variables regression. From what I have seen, this mostly is used with continuous outcomes in a linear model.
A) Is ...
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"weight" input in glm.nb function in R. How exactly does the weight affect the likelihood?
I would like to understand how the weight argument of glm.nb is affecting the likelihood function.
I understand that glm.nb find ...
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Propensity Score Matching – How do the mechanics lead to a different result than unmatched?
The gist of propensity score matching, as I understand it, is as follows:
You want to estimate the average treatment effect (ATE) of a treatment on some outcome. However, if you simply calculate the ...
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Rationale behind Good–Turing frequency estimation?
Good–Turing frequency estimation is a smoothing estimator for estimating a multinomial distribution. It seems very convoluted.
From mathematical statistics point of view, what is the rationale
behind ...
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Difference-in-difference in panel data
Under which conditions should we expect the difference-in-difference estimate to be equal to the equivalent panel data model?
Strictly speaking, whenever we have a experiment that offers a well ...
CommunityBot
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Very different scale parameter estimates in Poisson regression
The background: I'm analysing survival data using a Poisson model. I've splitted the data on 2 time-scales (attained age and calendar year). Attained age is modelled using flexible parametric ...
CommunityBot
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"Brute force" expected deviance for logistic regression?
A commonly used goodness of fit statistic for logistic regression is the deviance. This is also known as the likelihood ratio chi-square statistic. It is defined as:
$$D=\sum_{i=1}^{N}d_i^2$$
$$d_i^...
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Random Forest: Class specific feature importance
I'm using the bigrf R-package to analyse a dataset with ca. 50.000 observations x 120 variables, classified into two groups.
After growing a forest of 1000 trees, ...
CommunityBot
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Calculating standard deviation from log-normal distribution confidence intervals
I have the results of a meta-analysis of 10 studies that reports a combined random effects odds ratio (computed using Woolf's method) and 95% confidence interval of an event happening in one group ...
CommunityBot
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CDC says median number of sexual partners a woman has is 4.3. How can this be?
https://www.cdc.gov/nchs/nsfg/key_statistics/n-keystat.htm
According to the CDC, the median of the number of sexual partners a woman has is 4.3. But how can this be? The median can be 4, or 5, or ...
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Why don't we typically worry about stationarity in panel data models with fixed effects?
Why don't we typically worry about stationarity in panel data models with fixed effects?
In time series analysis, stationarity is often a crucial assumption. However, I've noticed that in applied ...
CommunityBot
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Name for Generalized Generalized Linear Models
Consider the class of models given by $y\sim F(g^{-1}(\beta^\top\mathbf{x}))$ with $\mathbb{E}[Y]=g^{-1}(\beta^\top\mathbf{x})$.
Most authors I've come across call this a GLM only if F is in the ...
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Intuitively, why do flushes overtake straights as the number of cards in hand increases?
A 5-card poker hand is more likely to be a straight than a flush.
But a 13-card bridge hand is more likely to contain a 5-card flush than a 5-card straight (source: I read it online somewhere).
What ...
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Any Insights on the adoption and use of the Healthy Akaike Information Criterion (hAIC)?
Recently, I came across the Healthy Akaike Information Criterion (hAIC), introduced by Demidenko in his 2004 book "Mixed Models: Theory and Applications with R." Despite its (potential) ...
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