Linked Questions

11
votes
2answers
2k views

What are some good exploratory analysis and diagnostic plots for count data? [duplicate]

Does anyone know of good reference material on exploratory analysis and diagnostic plots for count data?
3
votes
0answers
2k views

Diagnostics for a negative binomial model [duplicate]

I would like to know what model diagnostics I should be checking to ensure that a negative binomial (NB) regression for overdispersed data has meet all of the required assumptions. There is a very ...
1
vote
0answers
1k views

Residuals in Poisson regression in R [duplicate]

While performing Poisson regression in R, I realized that the residuals, as given in the object slot (model$residuals), differ both from the values returned by the <...
1
vote
0answers
595 views

Assumptions of poisson regression model [duplicate]

I am going to use Poisson regression in my model, but I don't know what assumptions I need to check to verify adequacy of the model. In a normal regression, I had to check Gauss Markov assumptions for ...
2
votes
0answers
413 views

Plotting a quasi-poisson regression [duplicate]

I have a quasi-poisson regression model for analysing the correlation between academic prestige and bulic visibility. I have a set of independent variables - continuous and dummies in this model. I ...
1
vote
0answers
55 views

Which kind of diagnostic plots for count data? [duplicate]

I know that for an lm model is enough to run plot(model_lm) to get diagnostic plots. I am dealing with high-dimensional count ...
50
votes
4answers
77k views

Is there a test to determine whether GLM overdispersion is significant?

I'm creating Poisson GLMs in R. To check for overdispersion I'm looking at the ratio of residual deviance to degrees of freedom provided by summary(model.name). ...
34
votes
2answers
52k views

Interpretation of plot (glm.model)

Can anyone tell me how to interpret the 'residuals vs fitted', 'normal q-q', 'scale-location', and 'residuals vs leverage' plots? I am fitting a binomial GLM, saving it and then plotting it.
36
votes
3answers
29k views

Interpreting residual diagnostic plots for glm models?

I am looking for guidelines on how to interpret residual plots of glm models. Especially poisson, negative binomial, binomial models. What can we expect from these plots when the models are "correct"...
28
votes
2answers
23k views

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) ...
20
votes
2answers
9k views

Which diagnostics can validate the use of a particular family of GLM?

This seems so elementary, but I always get stuck at this point… Most of the data I deal with are non-normal, and most of the analyses based on a GLM structure. For my current analysis, I have a ...
19
votes
2answers
9k views

Is there i.i.d. assumption on logistic regression?

Is there i.i.d. assumption on the response variable of logistic regression? For example, suppose we have $1000$ data points. It seems the response $Y_i$ is coming from a Bernoulli distribution with $...
12
votes
2answers
19k views

Checking residuals for normality in generalised linear models

This paper uses generalised linear models (both binomial and negative binomial error distributions) to analyse data. But then in the statistical analysis section of the methods, there is this ...
9
votes
2answers
3k views

Assumptions of generalized linear models

On page 232 of "An R companion to applied regression" Fox and Weisberg note Only the Gaussian family has constant variance, and in all other GLMs the conditional variance of y at $\bf{x}$ depends ...
2
votes
1answer
4k views

Interpreting QQ plot of poisson regression

This is the QQ plot resulting after fitting a poisson regression. I found in a book saying that central line corresponds to zero cases in the response. I can imagine that for zero response cases ...

15 30 50 per page