# Tagged Questions

Deviance is twice the difference between the maximum achievable log likelihood and that attained under the fitted model.

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### How to calculate percent deviance explained on square-root-transformed dependent variable?

I have a multiple linear regression model with a square-root transformed dependent variable. I want to report % deviance explained for each parameter. I assume I need to back-transform in some way, ...
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### Measure of absolute goodness-of-fit and good reference measure for cross validation in ordinal regression

I am following up the question I asked here with a more general one, as the reason why I am seeking to calculate the accuracy of my ordinal regression models is to use it as a measure of absolute ...
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### Ordinal model comparison: lower deviance but lower accuracy, is this possible?

I am performing ordinal regression (6 response categories) on a large dataset (>15000 points) and comparing two models, one with one predictor X1 (Model 1) and the other with two predictors X1 and X2 ...
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### What does deviance represent: a number of points?

I read very carefully the answer to the question "what is deviance?" already asked here, and I understand how to calculate and use deviance for model comparison, for example. However, a question ...
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### Deviance vs Pearson goodness-of-fit

I am trying to come up with a model by using negative binomial regression (negative binomial GLM). I have a relatively small sample size (greater than 300), and the data are not scaled. I noticed that ...
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### The number 2 in Deviance

What is the additional coefficient 2 in AIC, or other deviance criteria? In the books or on the internet I keep reading "historical reasons". What the heck are those historical reasons? Is there a ...
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### Calculate goodness-of-fit (with deviance) to compare averaged models?

I need to compare the goodness of fit of several averaged logistic regression models by calculating the deviance explained. I'm using the MuMIn package in R to ...
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### Distribution of deviances from logistic regression

I would like to know what is the theoretical distribution of the vector of (signed) deviances $d_i$ from a logistic regression. Failing that, is there a way to to transform them unto approximately ...
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### For ungrouped binary data, can the deviance be approximated by a chi-squared distribution?

I heard that "for ungrouped binary data, the deviance cannot be approximated by a $\chi^2$-distribution." Is it true? Why? Thanks in advance!
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### Goodness of fit in a GLM with scaled deviance

On this page, I am interested in the section “goodness of fit”, which is near the bottom of the page and contains the table of deviance functions. The author states that the scaled deviance, i.e. ...
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### Manually evaluating the DIC: very big number of effective parameters?

My problem is the following: I'm evaluating the fit to a function $f(\mathbf{x},\theta)$ via MCMC (because I have some priors on the parameters), and I'm trying to evaluate the DIC, given by: ...
470 views

### R-squared in linear model verses deviance in generalized linear model?

Here's my context for this question: From what I can tell, we cannot run an ordinary least squares regression in R when using weighted data and the survey package. ...
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### Symmetric measure of variable contribution to a regression

Take a linear regression setup with two "blocks" of predictors. The typical measures for the contribution of each block over the other are asymmetric (say, likelihood change, RSS change etc.). Is ...
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### Analysis of Deviance in R - Which test?

I have two generalized linear models mod1 and mod2. ...
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### Negative number of parameters in hierarchical bayesian model

I'm using Deviance information criterion to assess the fitness in my Bayesian hierarchical model. The functional form of this criterion is as follows: $$DIC=p_{D}+\bar{D}$$ where ...
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### Confidence Interval of estimator for the exponential distribution

We have an exponential distribution $$f(x)=\frac{e^\frac{-x}{\theta}}{\theta}$$ We are told that $n=3$ and that the data are given as $x_1=1, x_2=2.5, x_3=5.5$ a.) Determine an ...
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### Good model vs. AIC

Suppose I run a bidirectional stepwise in R with the model: step(glm(y ~ a + b + c + d, poisson)) And the result may be: ...
1k views

### Can a -2 Log likelihood be calculated with only one model?

I am using the glmfit function in MATLAB. The function only returns the deviance and not the log likelihood. I understand that the deviance is basically twice the ...
1k views

### Is the percent of total deviance explained a useful model summary? [duplicate]

My question is regarding the interpretation of the percent of deviance explained (and other $R^2$ anaologs or pseudo $R^2$ values for GLMs. Is this a meaningful summary statistic for models other ...
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### “Brute force” expected deviance for logistic regression?

A commonly used goodness of fit statistic for logistic regression is the deviance. This is also known as the likelihood ratio chi-square statistic. It is defined as: $$D=\sum_{i=1}^{N}d_i^2$$ ...
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### Poisson deviance - and what about zero observed values?

According to Crawley *), the Poisson deviance is computed as $2 \sum{O \cdot \log ({O \over E})}$ But what if observed value $O$ is zero? *) Statistical Computing - An Introduction to Data Analysis ...
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### How to assess goodness of fit of a particular nonlinear model? [closed]

I have a nonlinear model $y=\Phi(f(x,a)) + \varepsilon$, where $\Phi$ is the cdf of the standard normal distribution and f is nonlinear (see below). I want to test the goodness of fit of this model ...
I want to calculate the hat matrix directly in R for a logit model. According to Long (1997) the hat matrix for logit models is defined as: $$H = VX(X'VX)^{-1} X'V$$ X is the vector of ...