Linked Questions
10 questions linked to/from McFadden's Pseudo-$R^2$ Interpretation
6
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1
answer
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Why McFadden's pseudo-R^2?
Why can't we simply use ordinary $R^2$ in logistic regression, as we do in linear regression? Domencich and McFadden seem to imply that heteroskedasticity is an issue:
but I don't understand why. In ...
- 8,448
6
votes
1
answer
1k
views
Maximum number of alternatives in a discrete choice model
We are modeling a discrete choice scenario, with alternative-specific coefficients. We also break the assumption of independence of irrelevant alternatives. To model this, we are using an alternative-...
- 459
1
vote
0
answers
5k
views
How to report Logistic Regression Pseudo-R^2 in publication or reports?
I have a Logisitc Regression model with a McFadden Pseudo-$R^2=0.7113$. Based on the answers to this question: McFadden's Pseudo-R2 Interpretation, it seems my model has a good fit. However if I ...
- 153
1
vote
1
answer
2k
views
Model Quasipoisson interpretation and validation
I am currently doing my Master thesis with evaluating my results in R. I am stuck on my analysis of my glm with quasipoisson. I am analysing influencing variables on the dormouse abundance in 2 types ...
- 11
6
votes
1
answer
1k
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Is a logit model with a pseudo-R^2 of less than 0.5 a worse model than a coin toss?
I have recently encountered the remark that if a logit model's pseudo $R^2$ is lower than $0.5$ the result is completely worthless because a coin toss is a better model. Is this interpretation correct?...
- 1,317
3
votes
2
answers
838
views
Presenting Logistic Regression Results (Imbalanced Data, Small Sample Size)
I have an imbalanced data set of 300 observations with an adverse event rate of 8%. I have 4 features that I believe to be relevant based on expertise in the field. I am interested only in inference (...
- 777
2
votes
1
answer
1k
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How to get the proportion variance explained by each predictor in an lmer() model?
Is there a way to get the proportion of variance explained by individual fixed effects in a mixed effects model?
I thought that the partR2 package could do this, ...
- 2,441
1
vote
1
answer
207
views
Why R is not significant (and very low), while all predictors are significant? [duplicate]
I used a network logistic regression to regress five predictors against a dependent. They are all significant, instead the R is not significant and it's even very low. I can understand that it may be ...
- 41
0
votes
0
answers
190
views
Understanding differences between binomial and multinomial models
I'm attempting to model how 2 predictor variables affect the relative proportions of 3 different categorical groups. I started off by running a binomial model for the proportion of each individual ...
- 685
0
votes
0
answers
39
views
Correlation Range Misconception (-1; +1)
Mathematically, a correlation coefficient can range from –1.0 to 1.0.
The book 'statistical misconceptions' by S. W. Huck says this is a misconception people have.
... What is the parallel frame of ...
- 247