6
votes
Is there a non-parametric form of a 3-way ANOVA?
ANOVA, even a 3-way ANOVA, is a special case of linear regression.
For one-way ANOVA, the typical "nonparametric" flavor is the Kruskal-Wallis test, so it seems like you would want some kind ...
5
votes
What is the distribution of the error term in the Poisson Regression model?
@whuber's comment is the answer. Typically we don't assume an independent error term with non-normal generalized linear models. The response distribution already contains the theorized stochastic ...
4
votes
Accepted
In a normal GLM is the dispersion parameter equal to the marginal variance?
Yes, in a normal generalized linear model (GLM) the dispersion parameter and the variance are the same thing.
If you are fitting a normal GLM with identity link (which is the default) then you may as ...
3
votes
Accepted
Models for testing non-linear dynamics (e.g., threshold effects), where threshold is not necessarily known
You could model this with probit or logistic regression. Then you model the probability
$$\mathbb{P}(Y_i = y) = \begin{cases} p & \qquad \text{if $y=1$}\\
1-p & \qquad \text{if $y=0$}
\end{...
2
votes
Help in understanding zero inflated neg binomial model summary
See my comment.
To interpret the estimated coefficients, apply the inverse link. In this case you've used a log link so you would need to exponentiate the coefficients. So people in the ...
2
votes
Models for testing non-linear dynamics (e.g., threshold effects), where threshold is not necessarily known
I think you're describing change point detection, and you can find an enormous amount of information on that topic once armed with the right term to search for. By the way, this kind of thresholding ...
2
votes
Linear model with constraints in R
Once you understand how linear constraints can be incorporated in linear models, you will be able to figure out how any software represents them.
1. Representing linear constraints
Your model appears ...
1
vote
Accepted
Glm with all explanatory variables included gives same probability for all coefficients. Why?
Isn't it more concerning that the standard errors are rather large?
I suspect that you are running into (at least one) numerical issue. Update: A bigger issue might be (near) perfect separation ...
1
vote
Accepted
How to calculate Bayesian marginal credible interval?
Good question, with a few approaches depending on who you ask.
Let's set the stage for clarity. Suppose you are fitting a model that looks like
$$ y_{i,j} = \alpha_{j} + \beta_{j}x_i$$
Here, $\...
1
vote
Why does Poisson regression not have a closed form solution?
You could use a linearized form of the equation and apply ordinary linear regression. But, this makes two errors:
You ignore non-homogeneity of the error distribution. The variance in $Y$, and also ...
1
vote
Accepted
Post-hoc tests for unexpected outcome of binomial models
The extra "significant" predictor in the second model, utt_IKI, is involved in an interaction with utt_speed. It can ...
1
vote
R - glm - how to deal with missing values
Yes, your model omits the first category of the categorical variable ("AS") and that's what Intercept is for; the other categories are compared to the first one, as you correctly guessed.
...
1
vote
Meaning of weights in output of glm (logistic regression) - vector of weights
You may be even more confused than you previously thought.
The weights function, extracts one of two types of weights, specified by the ...
1
vote
Accepted
Is it possible that GEE and mixed effect GLM give contradicting answers? If so, which one should be trusted?
Do you mean inference rather than "answer", in terms of the supposed contradictions? Then yes for a number of reasons. A non-comprehensive list:
There is not a perfect 1-1 correspondence ...
1
vote
Is there a non-parametric form of a 3-way ANOVA?
The exchange in comments now makes this clearer. The OP has three species of shark, two level of maturity, and two sexes of shark. This forms a $3\times2\times2$ design. There will be 2 degrees of ...
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