0
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0answers
24 views

Logistic regression diagnostics [duplicate]

In linear regression, we need to check which assumption is violated. But for logistic regression, what assumptions do we have for the model? I was attempting to wrap my head around this thing. But ...
3
votes
1answer
101 views

What diagnostics for random effects logistic regression?

I'm wondering what checks/diagnostics you usually calculate and report if you do a random effects logistic regression. C-statistic/ROC curve Check multicollinearity? Check heteroscedasticity? ...
1
vote
0answers
76 views

Has anyone written a package in R to calculate diagnostic plots after clogit (conditional logistic regression)? e.g. leverage

Has anyone written a package in R to calculate diagnostic plots after clogit, conditional logistic regression? e.g. leverage. Or ...
1
vote
1answer
360 views

How do I compute a cutoff based on sensitivity/specificity when the characteristics of my sample is different from the population?

I have a dataset containing the performance of a novel instrument to screen for disease A. The novel instrument uses a scoring system to score the subject to determine if they have disease A. I then ...
5
votes
2answers
880 views

Residuals for logistic regression and Cook's distance

Are there any particular assumptions regarding the errors for logistic regression such as the constant variance of the error terms and the normality of the residuals? Also typically when you have ...
2
votes
1answer
252 views

Logistic regression and complementary log log model

is there like a diagnostic checking(like those in the time series) done for logistic regression and complementary loglog model?
3
votes
1answer
1k views

Explanation of R diagnostic plot for logistic regression

I'm hoping someone can explain this bit of R code for me related to glm(). I don't understand the diagnostic plot that has been suggested. It seems a more ...
3
votes
0answers
192 views

“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: $$D=\sum_{i=1}^{N}d_i^2$$ ...
11
votes
2answers
13k views

Likelihood ratio test in R

I'm not sure if I'm asking something stupid or off topic here, but I can't think where can I ask this question. suppose I am going to do a univariate logistic regression on several independent ...