Linked Questions

6
votes
2answers
3k views

Find out pseudo R square value for a Logistic Regression analysis [closed]

My name is Tuhin. I came up with a couple of questions when I was doing an analysis in R. I did a logistic regression analysis in R and tried to check how good the model fits the data. But, I got ...
4
votes
2answers
5k views

Measuring the performance of Logistic Regression

Being quite new to the field, it occurs to me that there are multiple and fundamentally different ways of assessing the quality of a logistic regression: One can evaluate it by looking at the ...
9
votes
1answer
4k views

Measure of explained variance for Poisson GLM (log-link function)

I am looking for an appropriate measure of the "explained variance" of a Poisson GLM (using a log-link function). I have found a number of different resources (both on this site and elsewhere) that ...
2
votes
1answer
3k views

Variation explained in ordinal logistic regression models

I have made these three ordinal logistic regression models: ...
0
votes
3answers
7k views

how to calculate R-squared in glm?

I came up with below for my glm analysis but I need to calculate R-squared to cite in the paper? anyone can help me with this please? summary(lrfit) Call: ...
5
votes
1answer
1k views

Fewer variables have higher R-squared value in logistic regression

I am testing out 3 modeling approaches for malnutrition in children. Theoretically, distal determinants (education,poverty) operate through proximal determinants (water, sanitation) in determining ...
4
votes
2answers
2k views

Goodness of fit in GLMs

I am searching for a good criterion to measure the "goodness of fit" in generalized linear models. To make clear: I am not searching for a criterion which gives me an answer to the question "does ...
4
votes
1answer
2k views

Pseudo-$R^2$: what are the null models for linear and non-linear regressions?

I have data from an experiment. The independent variable is time, the dependent variable is mass loss of organic matter. Now I want to compare whether a linear or a non-linear model fits better. From ...
5
votes
2answers
1k views

Which measure of model fit to report when performing likelihood based regression: AIC, BIC, Pseudo R-square?

I'd like to hear your opinions on the following: What parameters would you report when estimating different likelihood based regression? AIC, BIC, Pseudo $R^2$? What is the standard to report? It ...
1
vote
1answer
2k views

Regression model for ordinal dependent variable and categorical independent variables

If I'm using R, which regression model should I use for my dataset? (I need to get the R-squared value.) I have 1 dependent variable and 6 independent variables as follows: 1 dependent variable: ...
3
votes
2answers
605 views

Are the $1-SSe/SSt$ and $cor^2$ calculations of $R^2$ always equivalent?

I am trying to calculate the $R^2$ value for a production constrained spatial interaction model, using Fotheringham and O'Kelly (1989) as my guide. I get dramatically different values for R-Square, ...
2
votes
0answers
3k views

Nagelkerke $R^2$ interpretation

I used logistic regression and found that my model fits well: ...
3
votes
1answer
1k views

How to assess GLMM performance on a new data set?

I built a generalized linear mixed-effects model (GLMM) using glmer function from the lme4 package in ...
1
vote
0answers
2k views

pseudo R-squared for model estimated with maximum likelihood

I want to compute a pseudo-$R^2$ for a model whose parameter estimation was based on maximum likelihood (function likfit(), package ...
5
votes
1answer
826 views

Why is it futile to use the deviance as a goodness-of-fit measure for Bernoulli data?

In Ordinal Data Modelling by Johson & Albert, page 102-103: For Bernoulli observations [...] the asymptotic chi-squared distribution of the deviance statistic may not pertain. Indeed, for ...

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