6
votes
Accepted
Model comparison for nested regression models that are not symbolically nested
For a linear model, say that the full model is $\mathbf{Y} = \mathbf{X} \boldsymbol\beta + \mathbf{e}_f$ and the reduced model is $\mathbf{Y} = \mathbf{R} \boldsymbol\alpha + \mathbf{e}_r$. $\mathbf{X}...
- 166
4
votes
Accepted
Negative Binomial Regression
Incidence-rate ratios (IRRs) are exponentiated coefficients, so $\exp(b)$ rather than $b$. Standard errors and confidence intervals are similarly transformed.
To predict deaths, you first need to ...
- 37.8k
3
votes
Accepted
p-values based on clustered se with glm
All you need to do is supply the output of glm() to lmtest::coeftest() and supply the VCOV matrix to get the statistics.
...
- 35.7k
2
votes
Accepted
How do I interpret the results of this glmer function?
summary() gives more information, including a table with Z-scores and p-values (if you want to print just this information, ...
- 45k
1
vote
Analyzing the effect of satisfaction on transport mode preference using mixed logistic regression in R
You are dealing with a type of analysis that falls under the category of discrete choice modeling. This has a set of related but not equivalent approaches to modeling binary data such as yours.
There ...
- 5,525
1
vote
Accepted
Test for effect of treatment for subjects of different origin?
Well overall, it's a bit of a study design issue. You can never be confident whether differences between locations are the result of your treatment, or a different, unmeasured variable that changes ...
- 343
1
vote
Regression model with (almost) non-negative residuals
Your response is non-negative and the estimate is non-negative.
But the difference, the residuals, can be negative.
See below an example for exponentially distributed data
...
- 82.8k
1
vote
How to derive formula from GLM coefficients?
Your formula would be
y = inv_logit(.9 + .5 * (OS = low) + .2 * (OS = medium) + ...)
when OS is high your prediction would be ...
- 315
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