Questions tagged [pseudo-r-squared]

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

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Confused by GLMM strange pseudo r square output

Someone from another lab is trying to run a GLMM model and estimate the pseudo R square of the model. So far this is the output from the anova and ...
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Why we do not use r squared for logistic regression? [duplicate]

Why we do not use R squared for logistic regression? What is the logic behind it?
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Why is R-squared Not Valid for Nonlinear Regression? [duplicate]

Why is R-squared Not Valid for Nonlinear Regression? Why we generally do not use it in nonlinear regression?
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Why do I get an R² Nagelkerke even though my response is numerical?

I just fitted a GLM with a Gamma distribution and somehow my output gives me a pseudo R². (Nagelkerke). As far as I know a pseudo R² is only used when the response is ordinal or nominal, but my ...
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Comparison of predictor performances in different models

My intention is to test the power of a single predictor x in predicting different responses: y1 that is presence/absence and <...
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What is the best way to compare fixed and random effects of a GLMM?

I am doing a research in which i am trying to measure the importance of the doctor that is in charge of a patient in a medical decision. For that (and others reasons) i have used a GLMM using lmer4 ...
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Why does McFadden's Pseudo-$R^2$ yield different values for the same model depending on data grouping?

Just stumbled accross the problem that McFaddens Pseudo-$R^2$ yields different values in logistic regression, depending on the grouping of the data. When predictor values occur more than once, there ...
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Calculating different pseudo-$R^2$ for a betareg model

Sorry if this is a bit long.. I've been trying to fit models predicting the % of area infested in a field (response between 0 and 100%, total of 61 fields), with four explanatory variables, two ...
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R2 for mixed-effects Conway-Maxwell Poisson using package glmmTMB

After running a mixed-effects Conway-Maxwell Poisson model using glmmTMB, I've printed the results using sjPlot's tab_model() but I don't know what R2 calculation is being used. Is it Nakagawa's R2 ...
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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 ...
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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 ...
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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 ...
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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 ...
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$R^2$ 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 ...
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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. ...
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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 ...
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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-...
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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 ...
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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 ...
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How to calculate pseudo-$R^2$ from R's logistic regression?

Christopher Manning's writeup on logistic regression in R shows a logistic regression in R as follows: ...
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69 votes
9 answers
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Which pseudo-$R^2$ measure is the one to report for logistic regression (Cox & Snell or Nagelkerke)?

I have SPSS output for a logistic regression model. The output reports two measures for the model fit, Cox & Snell and ...
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