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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Simulation for model checks for sample size

In the book Bayesian and Frequentist Regression Methods, Wakefield notes that estimators for coefficients in a linear model will be normal if the error terms are normal or if the sample size is ...
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1answer
184 views

Visually inspecting normality of variables

I'm using R to plot some graphs for visually inspecting the normality of variables that will go into a linear regression model. Except for a histogram and a QQ plot, what other graphics could I use?
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1answer
454 views

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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366 views

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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156 views

Has anyone written a package in R to calculate diagnostic plots after clogit (conditional logistic regression)? e.g. leverage

Has anyone written a package in R to calculate diagnostic plots after clogit, conditional logistic regression? e.g. leverage. Or ...
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411 views

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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703 views

does rstandard standardize in z?

I'm new to R, so please be gentle. I was under the impression that rstandard(model) returns the z-scores of the residuals in ...
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298 views

How to compute sample size to compare two diagnostic tests

I will be performing two diagnostic tests (one is the gold standard, one is novel) on the same subject aiming to establish sensitivity, specificity, PPV and NPV. What formula may be used to compute ...
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1k views

Please help me refine this zero-inflated negative binomial model

I have been working on a baseball model to predict success at the major league level using minor league statistics. After posting multiple threads on this site (1, 2, 3) and receiving valuable ...
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3k views

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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3k views

How to calculate the confidence intervals for likelihood ratios from a 2x2 table in the presence of cells with zeroes

I am analysing a diagnostic test (against a gold standard, using a 2x2 table). I want to calculate likelihood ratios (sensitivity / (1-specificity) etc) however I have several sets of data with 0 ...
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3k views

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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1answer
107 views

Explanation of a step in derivation of residuals for R lm diagnostic?

I'm reading Faraway's book (http://cran.r-project.org/doc/contrib/Faraway-PRA.pdf) to try to understand R's lm diagnostic plots. On page 72 of the book is this: I have been trying to understand a ...
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How do I compute a cutoff based on sensitivity/specificity when the characteristics of my sample is different from the population?

I have a dataset containing the performance of a novel instrument to screen for disease A. The novel instrument uses a scoring system to score the subject to determine if they have disease A. I then ...
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3answers
487 views

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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2k views

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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2k views

How to test outliers, normality, homoscedasticity? [closed]

With the Data Analysis command in Excel I made a plot, which I can't post, because this is my first post ever. ...
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382 views

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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848 views

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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1answer
2k views

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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How to verify linearity assumption in linear regression with categorical predictors?

I have used simple linear regression, and I'm now checking that the model meets the assumption of linearity. The model used a continuous response variable and categorical explanatory variables. How ...
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947 views

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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4k views

Collinearity diagnostics disagree - VIF, condition index, and correlation matrix

I'm working with a large dataset consisting of just over 1 million cases. The data are longitudinal covering 14 years and hierarchical with about 500 of the level 2 units. Each case is a criminal ...
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191 views

Test for convergence within Gibbs sampler

I am running a Gibbs sampler for Multivariate Normal times Inverse Wishart posterior distribution with missing data imputation step. I am trying to check if my step of simulating covariance matrices ...
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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 ...
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5k views

How to interpret model diagnostics graphics after R linear regression? [closed]

I am interested in understanding the graph plots we get after running lm() command (for linear regression) in R like, for example ...
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1answer
14k views

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 ...
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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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381 views

Logistic regression and complementary log log model

is there like a diagnostic checking(like those in the time series) done for logistic regression and complementary loglog model?
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564 views

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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2k views

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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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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843 views

How to test the randomness of residual plot?

Let's say in linear regression, I got a fit and I can plot residuals to see whether there is any systematic trend in such a plot. How to quantitatively determine whether the residues are really ...
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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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936 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 ...
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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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498 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 ...
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553 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 ...
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633 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 ...
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101 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 ...
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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 ...
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31k 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 ...
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3answers
684 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 ...
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616 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 ...