# Questions tagged [pseudo-r-squared]

a measure of how well variables of the model explain some phenomenon

14 questions
Filter by
Sorted by
Tagged with
0answers
9 views

### Nagelkerke pseudo R^2 interpretation in spatial regression

Could anyone explain to me the interpretation of Nagelkerke pseudo R^2 in spatial regression models? Definitions say it is computed using some conditonal probability, but I didn't quite get what they ...
0answers
29 views

### Pseudo R squared for the negative binomial regression

I am confused with the Pseudo $R^2$ computation of the negative binomial regression model. For the logistic regression, we can compute the Pseudo $R^2$ as ...
0answers
55 views

### Nagelkerke Pseudo-R-squared for proportional odds model and the effect size

I have computed the Nagelkerke Pseudo-R-Squared for the proportional odds model with two variables. I report ORs with p-values and confidence intervals and would like to quantify the strength of the ...
0answers
21 views

### Can we create confidence intervals around pseudo-R-squared Random Forest based on the forest?

For linear regression it is possible to place confidence intervals around the R-squared, either by formula or bootstrapping. Random Forest models, as regression model, return the "explained ...
1answer
78 views

### AIC, pseudo-R2, or log likelihood to compare models?

I am comparing the effect of climate, across three different time brackets, on a variable. I am interested in choosing the model that best predicts the variable to answer across which timescale the ...
1answer
33 views

### Calculate change in odds and Pseudo-R-Squared with R

I have a question that touches on both technical solutions in R and statistics. I have a huge dataset with 2,400 respondents in total. I performed a logistic regression in order to analyze views on ...
1answer
124 views

### Nakagawa's R2: what does it tell practice?

I am having a hard time figuring what Nakagawa's R² really "means". I understand that in simple linear regressions, R² indicates the amount of variance in the dependent variable explained by ...
0answers
46 views

### $R^2$ of Logistic Regression Without Intercept?

I am calibrating a logistic regression for a survey data which comes from a binary stated choice experiment. The stated choice experiment was an unlabeled one, which means that all the variables ...
0answers
10 views

### Will the R-Squared be lower if I run the same model on a dataset with all the data vs a dataset with the quarterly averages?

Let's assume I have a dataset with quarterly data on loans. Let's say I have 100,000 of these loans, spread out in 20 quarters. If I run a regression on all the loans, I will have 100,000 data points. ...
0answers
157 views

### Logistic regression with high McFadden pseudo-R-squared value and high p-value

I performed a logistic regression of an outcome variable (whether a patient is re-admitted to a hospital within a year) against a continuous index that measures a patient's access to healthcare. I ...
2answers
1k views

### Basic R-Squared in Poisson Regression

I have read one cannot/should not calculate the basic R-Squared used in linear regression for a Poisson generalized linear regression model. It is logical to me that one cannot determine the basic R-...
0answers
63 views

### When AIC and pseudo-R2 give opposite conclusions in beta regression models

I conducted an experiment to quantify the effect of two factors on a response variable: the response variable (Y) is a proportion (percentage cover) factor A is represented by the continuous ...
1answer
52 views

### Develop granularity-invariant criteria for comparison of logistic (binomial) models

I have a model with logistic (binomial) likelihood, with number of successes and failures as a response variable. I am comparing various models, which can be of different granularity. Different ...
0answers
382 views

### Interpreting pseudo-R² in GLMM

Different approaches to pseudo-R² naturally yield different results. For example, Nagelkerkes pseudo-R² tends to yield higher results than McFaddens pseudo-R². As I am not a statistician, it thus can ...