# Tagged Questions

Diagnostic measures (such as residuals or some summary statistics calculated from residuals) are used to evaluate some aspect of quality of model fit to data.

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### Why does my bootstrap interval have terrible coverage?

I wanted to do a class demonstration where I compare a t-interval to a bootstrap interval and calculate the coverage probability of both. I wanted the data to come from a skewed distribution so I ...
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### Interpreting residual diagnostic plots for glm models?

I am looking for guidelines on how to interpret residual plots of glm models. Especially poisson, negative binomial, binomial models. What can we expect from these plots when the models are "correct"...
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### How to read Cook's distance plots?

Does anyone know how to work out whether points 7, 16 and 29 are influential points or not? I read somewhere that because Cook's distance is lower than 1, they are not. Am, I right?
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### Likelihood ratio test in R

Suppose I am going to do a univariate logistic regression on several independent variables, like this: ...
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### 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 (...
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### 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 ...
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### Why are diagnostics based on residuals?

In simple linear regression one often wants to verify if certain assumptions are met to be able to do inference (e.g. residuals are normally distributed). Is it reasonable to check the assumptions ...
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### 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 ...
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### What are some good exploratory analysis and diagnostic plots for count data?

Does anyone know of good reference material on exploratory analysis and diagnostic plots for count data?
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### MCMC Geweke diagnostic

I'm running a Metropolis sampler (C++) and want to use the previous samples to estimate the convergence rate. One easy to implement diagnostic I found is the Geweke diagnostic, which computes the ...
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### Diagonal lines in residuals vs fitted values plot for multiple regression

I am observing strange patterns in residuals for my data: [EDIT] Here are the partial regression plots for the two variables: [EDIT2] Added the PP Plot The distribution seems to be doing ...
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### Residual Diagnostics and Homogeneity of variances in linear mixed model

Before asking this question, I did search our site and found a lot of similar questions, (like here, here, and here). But I feel those related questions were not well responded or discussed, thus ...
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### 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 ...
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### Residuals for logistic regression and Cook's distance

Are there any particular assumptions regarding the errors for logistic regression such as the constant variance of the error terms and the normality of the residuals? Also typically when you have ...
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### Explanation of R diagnostic plot for logistic regression

I'm hoping someone can explain this bit of R code for me related to glm(). I don't understand the diagnostic plot that has been suggested. It seems a more ...
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### When is it justified to “peek” at the outcome variable in model-building process?

I am referring to the following comment made in a 1996 paper by Dr Frank Harrell et al in Statistics in Medicine: Unless a formal penalized estimation technique is used, multiple comparisons ...
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### Troublesome residual plot from linear mixed model

I have fitted the following linear mixed model based on the results of an economic game: lmer(TotalScore~perOOgivenP+Game+(1|Subject),REML=T,data=mdl1table)->m1 ...
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### Communicating Regression Model Results

I am concerned about how unequipped most people are (both within and without academia) to properly employ standard model building methods such as linear regression and to interpret the results of ...
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### How to validate & diagnose a gamma GLM in R?

I am fitting a generalized linear model in R with the log link and I need to validate and diagnose my model. I have never worked with the GLM in the past. Is there an article or any references I ...
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### Which is the best method for meta-analysis of diagnostic test accuracy studies?

I am conducting a meta-analysis of diagnostic test accuracy studies focusing on myocardial perfusion imaging. I have used first Meta-Disc, but only for descriptive purposes, as it is clear that ...
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### Geweke diagnostic of a Markov chain: why does the first window have to cover the burn-in?

I read the following statement in this document$^{[1]}$, at the bottom of page 11: Too wide A will some times āhideā the burn in part within the converged part of the chain and the difference in ...
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### What diagnostics for random effects logistic regression?

I'm wondering what checks/diagnostics you usually calculate and report if you do a random effects logistic regression. C-statistic/ROC curve Check multicollinearity? Check heteroscedasticity? ...
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### Diagnostic plots for lmer

I am trying to produce a glmm using the lme4 package in R. To validate my model I would like to produce some diagnostic plots ...
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### what to do with ridiculous but valid leverage points

So I'm having some difficulty fitting a linear model to the data (see other post here glm model fit - can't find a family/link combination that produces good fit). In particular, I'm worried ...
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### Diagnostics for GEE in R

I have been checking out which diagnostics to use for a GEE analysis. It seem that influence measures are appropriate (Preisser, 1996). Does anyone know of a package that can be used in R to examine ...
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### Fitting a zero-inflated negative binomial regression with R

In this thread, I laid out a problem involving fitting a model that attempts to use minor league baseball statistics to predict success at the major league level (explained in full in the thread). ...
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### How to interpret model diagnostics when doing linear regression in R?

I ran lm() on my data with models selected by individual lm's of each characteristic and then combined the top $R^2$ based on $p$...
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### How to treat this OLS based on residual diagnostics

I am struggling already a couple of days with this simple OLS, can you help? Outcome years in function of predictor score, very simple linear model. The residual plot does absolutely not look good ...
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### Standardized residuals in R's lm output

I have a quick question: if I plot the diagnostic plots to an R regression, a couple of them have "Standardized Residuals" as their y-axis such as in this plot: My question is this: what are the ...
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### Tilted rectangle in residuals vs fitted plot

When performing diagnostics on an OLS model, what can make a plot of the predicted responses vs the residuals. Ideally we want a horizontal rectangle shape. But what does it mean when the plot is a ...
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### How can we have non-random patterns in the plot of simple linear regression residuals vs the predictor variable?

A) When considering a simple linear regression model, it is important to check the linearity assumption. Graphing the residuals vs the predictor variable can often give a good idea of whether or not ...
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### Mixed model or ANOVA on differences in pre-post design

I want to analyse the effect of different treatment types (control, treatment1, ..., treatment4) on the surface of specimens made of certain materials (...
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### What are the three forms of the Park test for heteroskedasticity?

I understand the Park test for heteroskedasticity has three different forms. The best known one is in a log form: LN(Residual^2) = intercept + slope (LN(X)). The second one is in a linear form: ...
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### What resolution should I be using for residuals vs fitted values plot from a linear regression?

I made this linear regression that shows how well estimated animal locations (longitude) predict actual animal locations. ...
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### Interpreting case influence statistics (leverage, studentized residuals, and Cook's distance)

I just wanted to clarify some things about leverage, studentized residuals, and Cook's distance: Does a large (in absolute value) studentized residual mean that a case is an outlier? Does a large ...
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### How to interpret the direction of the Harvey-Collier test and Rainbow test for linearity?

I implemented both those tests with R, using the lmtest package. Both tests directionally say the same thing (I think) with a very similar p-value of very close to 0. But, are those tests saying ...
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### Too many predictors to manually check linearity

Say I have 1000 potential predictors in a logistic regression. I don't have time to check each predictor manually for linearity. I could wait till after variable selection, but in that case I wonder ...
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### Confidence interval of AUC with Reitsma model in mada R package

I am conducting a meta-analysis of diagnostic test accuracy studies comparing myocardial perfusion scintigraphy vs coronary angiography using the mada R package. I ...