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Questions tagged [pseudo-r-squared]

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

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GLS combined with Random Effect

My data consists of repeated measurements (duration) per individual (ID). The fixed effect is habitat, the goal is to see if duration depends on habitat. However, the variance seems to differ quite a ...
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2 answers
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R squared in logistic regression adjusted for number of predictors

For OLS we have an adjusted R squared which adjusts for the number of predictors included in the model. For logistic regression there are some R squared analogues (Tjur’s R squared, McFadden’s R ...
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GLMMs with crossed random effects: How do I quantify the reduction in random effects variance of including fixed effects? Or, indeed, should I?

I am modelling test score outcomes (0/1) using a GLMM with crossed random effects for persons and items. As I add significant fixed effects estimates for person and item, the variance estimate for the ...
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Why does variance decomposition not exist in logistic regression?

I'm quite confused when reading some materials, it says the reason we use pseudo R-square in logistic regression is that the variance decomposition cannot hold. I get the idea that the variance of $y$ ...
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Equivalent of R-squared in negative binomial regression

In my study, I experiment with fixed and mixed effects negative binomial regression to my data (in R) as the response variable is a count variable. I have read somewhere that unlike in the case of ...
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How can we justfify the assumption of equal scale/variance in the definition of R-squared from Deviances in GLMs?

If we take the R-squared to be the comparison of Deviances between models (the model of interest, the saturated model, and the constant model), we can write it as (see this answer CC BY-SA 4.0): $$R_{...
Firebug's user avatar
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3 votes
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Pseudo $R^2$ for probit model: In-sample or out-of-sample?

I have a dataset test_data that measures mortality in response to dosage of a pesticide. I used a probit model that evaluates the efficacy of a single pesticide. ...
scott.pilgrim.vs.r's user avatar
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Mixed effects model for repeated measures approach in R

I'm using mixed effects models for repeated measures (MMRM) in R with the nlme package for the first time as part of a research project and have read lots of posts ...
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Nagelkerke's Pseudo-R² is negative? How to fix this?

I am working on my Master's Thesis and I was fitting various glms on my data; and since I can't calculate adjusted R² values for my models, I opted for Nagelkerke's pseudo R². I used the rcompanion ...
Pauline's user avatar
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Relative importance in hurdle model: which metric to use?

I want to calculate the relative importance of predictors of a hurdle model, my first choice is dominance analysis. For that I would need a suitable metric of model quality. My first thought is to use ...
M. Riera's user avatar
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Easy goodness of fit tests when using svyolr package (ordered logit regression on complex survey data)?

for a uni project I am running an ordered logit regression on survey data, using the svyolr package in R. I am looking to report some sort of goodness of fit for the model but am struggling to find ...
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statistics linking McFadden's $R^2$ to the relationship between two binary variables, akin to correlation (Copula with Bernoulli margins?)

My goal is to create a visualization of the strength of the McFadden's $R^2$ of a (multinomial) logistic regression, where McFadden's $R^2$ is $1-\dfrac{LL(M_1)}{LL(M_0)}$, involving the ratio of the ...
Dave's user avatar
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How to interpret the UCLA "adjusted count" logistic regression pseudo $R^2?$

Here, UCLA gives a number of pseudo $R^2$ values for evaluating logistic regression models. Despite the issues with doing this, the last two deal with hard classifications rather than the ...
Dave's user avatar
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Bootstrap difference in R2 between two models

I apologise beforehand if this is already answered elsewhere, but I have searched for this particular question and didn’t find a post that matched it. I have two logistic regression models: a base ...
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How to confirm the correlation between independent variables and dependent variable when Pseudo-R² is low?

I have a logistic regression with 10 independent variables. I want that one of these independent variables is correlated with the dependent variable, others are covariants. In this regression model, p ...
you lin's user avatar
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Quantile Regression Pseudo R-Squared

When computing the Pseudo R-squared value in quantreg in R or statsmodel in Python, what is an acceptable range to justify goodness of fit? Also, what is the functional form of Pseudo R-Squared ...
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Logistic regression: How to improve the pseudo-$R^2?$

Firstly, I would like to ask you opinion about my model: I have a logistic regression model where the dependent variable is late payments (1=late/0=not late) and diesel prices and interest rates as ...
user373185's user avatar
6 votes
1 answer
443 views

Confused by the pseudo R2 for my zero-inflated regression

Data Here is the data I am using, which records my coffee consumption and productivity habits by day: ...
Shawn Hemelstrand's user avatar
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0 answers
280 views

McKelvey and Zavoina's pseudo-$R^2$ score range

I am trying to build a probit regression model. Looking for some proper goodness of fit indicator for my model I read that McKelvey and Zavoina's pseudo-$R^2$ could be the best index for this purpose. ...
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How to calculate a r-squared for a zero-truncated poisson mixed model (glmmTMB)

I am interested to calculate the pseudo-r-squuared for a zero-truncated poisson mixel model (using glmmTMB). The r.squaredglmm (package MuMin) gives a message that it can not calculate pseudo-r2 for ...
Wil Tamis's user avatar
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31 views

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?
Aslı's user avatar
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6 votes
2 answers
1k views

Are consistently negative Efron's pseudo-r2 in logistic regression possible?

I am conducting logistic regression and looking to calculate pseudo-R2 values alongside AIC and BIC for model evaluation. I selected Efron's pseudo-R2 because of its simple calculation and the ...
stat_is_quo's user avatar
2 votes
1 answer
178 views

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 <...
Kryštof Chytrý's user avatar
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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 ...
Thomas_9210's user avatar
3 votes
1 answer
126 views

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 ...
cdalitz's user avatar
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3 votes
1 answer
787 views

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 ...
Roni Gafni's user avatar
1 vote
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182 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 ...
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1k 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 ...
lvh's user avatar
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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 ...
Nicosc's user avatar
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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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6 votes
1 answer
220 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 ...
Gabriel Souza's user avatar
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14 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. ...
adrCoder's user avatar
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590 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 ...
Max's user avatar
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5 votes
2 answers
7k 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-...
Benykō-Zamurai's user avatar
2 votes
1 answer
65 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 ...
Tomas's user avatar
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4 votes
0 answers
564 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 ...
yenats's user avatar
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5 votes
0 answers
1k views

Is it possible to calculate a pseudo-R squared for a binomial GLMM with a cauchit link?

I'm modeling some repeated-measures presence-absence data using a binomial GLMM in lme4. I've been using the method suggested by Nakagawa and Schielzeth (2013) to calculate a marginal and conditional ...
yeticrab's user avatar
65 votes
5 answers
137k views

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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72 votes
9 answers
89k views

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 ...
Henrik's user avatar
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