Linked Questions
16 questions linked to/from Checking residuals for normality in generalised linear models
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What's the difference between error distribution and residual distribution in generalized linear models? [duplicate]
I have met with generalized linear model, but I'm confused with the errors and residuals? Can anyone help me out? I have got three questions.
(1)what's the difference between error and residual?
(2)...
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Interpretation of two residual QQ plots from poisson regression [duplicate]
I have what I believe are an interesting QQ plot of the residuals of some sports data fitted using Poisson regression. My model is actually a live model to predict the number of remaining events in ...
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Is normality testing 'essentially useless'?
A former colleague once argued to me as follows:
We usually apply normality tests to the results of processes that,
under the null, generate random variables that are only
asymptotically or ...
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Diagnostic plots for count regression
What diagnostic plots (and perhaps formal tests) do you find most informative for regressions where the outcome is a count variable?
I'm especially interested in Poisson and negative binomial models, ...
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Statistics published in academic papers
I read a lot of evolutionary/ecological academic papers, sometimes with the specific aim of seeing how statistics are being used 'in the real world' outside of the textbook. I normally take the ...
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Diagnostics for generalized linear (mixed) models (specifically residuals)
I am currently struggling with finding the right model for difficult count data (dependent variable). I have tried various different models (mixed effects models are necessary for my kind of data) ...
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How does logistic regression use the binomial distribution?
I'm trying to understand how logistic regression uses the binomial distribution.
Let's say I'm studying nest success in birds. The probability of a nest being successful is 0.6. Using the binomial ...
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Can Tree-based regression perform worse than plain linear regression?
Hi I'm studying regression techniques.
My data has 15 features and 60 million examples (regression task).
When I tried many known regression techniques (gradient boosted tree, Decision tree ...
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Diagnostics for General Linear Models
Pearson residuals follow normal distribution. We plot them against predicted values to see if the model is good.
Why would we plot deviance residuals against predicted values? Deviance residuals don'...
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Should I use a linear mixed model or a generalized mixed model?
I have a test dataset with repeated measures, different individuals sampled at different time points, here measured in days. I want to know if I should use a GLMM or a LMM to see how well, if at all, ...
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Half-normal distributed DV in generalized linear model
My dependent variable is, by origin, absolute residual* left after some regression; it is distributed half-normally. Now I plan to use Generalized linear model in SPSS (GENLIN) to regress it on some ...
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Diagnostics and residual analysis for Poisson regression
Recently, I was asked to check for serial correlation after doing a panel Poisson regression. I haven't seen such a test and in general, researchers (at least in the econom(etr)ics literature) don't ...
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Back Transforming Rates in Poisson GLM with Box and Cox Transformation
Suppose I have fitted a Poisson GLM to model rates as follows:
> fit.1=glm(response~X1+X2+ offset(log(population)),family=poisson,data=...)
I can get the ...
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Residual diagnostics after a logistic regression model [duplicate]
I wonder about how the residuals of a logistic regression model should be distributed.
Of course, running a linear regression model and by assuming the Normal distribution assumption, the residuals ...
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How do you get quantile normalized residuals for a t-distribution fit?
I've fitted a non-exponential family GLM regression model with the response distributed as a t-distribution with $\nu$ degrees of freedom, scale $\theta$ and mean $\mu = X\beta$.
We estimate $\beta,\...
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