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14
votes
2answers
961 views

What diagnostic plots exists for quantile regression?

Following on my question for OLS, I wonder: what diagnostic plots exists for quantile regression? (and are there R implementation of them?) A quick google search already came up with the worm plot ...
6
votes
2answers
782 views

Possible extensions to the default diagnostic plots for lm (in R and in general)?

I started digging a bit into the plot.lm function, this function gives six plots for lm, they are: a plot of residuals against fitted values a Scale-Location plot of sqrt(| residuals |) against ...
3
votes
0answers
212 views

“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: $$D=\sum_{i=1}^{N}d_i^2$$ ...
2
votes
1answer
420 views

Functions for regression diagnostics on mer objects in R

I'm particularly interested in plotting residuals against fitted values, and residuals against predictors. Often times I need to make boxplots of the residuals conditional on predictors. I'd be ...
5
votes
3answers
455 views

In linear regression, is the $R^2$ value enough to assess whether the relationship between the independent and dependent variable is linear?

In linear regression, is the $R^2$ value enough to assess whether the relationship between the independent and dependent variable is linear? It gives the amount of variability in the dependent ...
6
votes
2answers
496 views

How to combine the results of several binary tests?

First off let me say that I had one stats course in engineering school 38 years ago. So I'm flying blind here. I've got the results of what are essentially 18 separate diagnostic tests for a ...
1
vote
0answers
97 views

How do I go about conducting model diagnostics on WLS?

I'm familiar with the diagnostics required for OLS, however I'm in new territory with a model I'm fitting to data in R, using Poisson regression with GLM. What are the standard methods in evaluating ...
1
vote
0answers
88 views

Failure detection method

I receive 1000 points per day from installations who produces electricity. Every installation must proportionally produce the same amount of energy. I have to spot failures in those data. The actual ...
11
votes
2answers
19k views

Likelihood ratio test in R

I'm not sure if I'm asking something stupid or off topic here, but I can't think where can I ask this question. suppose I am going to do a univariate logistic regression on several independent ...
13
votes
3answers
616 views

Is it valid to analyze signal detection data without employing metrics derived from signal detection theory?

A signal detection experiment typically presents the observer (or diagnostic system) with either a signal or a non-signal, and the observer is asked to report whether they think the presented item is ...
8
votes
1answer
523 views

What type of post-fit analysis of residuals do you use?

When carrying out OLS multiple linear regression, rather than plot the residuals against fitted values, I plot the (internal) Studentized residuals against fitted values (ditto for covariates). These ...