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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Definition of 'Model Diagnostics'

Can anyone help me out with explaining what the term 'model diagnostics' refers to when applied to multiple regression please? In particular, what tests are necessary to check whether your estimated ...
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329 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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2k 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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257 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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237 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: $$D=\sum_{i=1}^{N}d_i^2$$ ...
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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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How to proceed with nonstationary variables in panels?

In most of the emprical papers using panel data, authors do not seem to "worry" too much aboout the non-stationarity of the individual variables. Yes, there is asymptotic theory for N and T going to ...
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Refining “good” mixing time estimate

Fix a Markov chain $\{ X_{t} \}_{t \in \mathbb{N}}$ with mixing time $\tau_{\mathrm{mix}}$. Assume that I know some finite bound on the mixing time $\tau_{\mathrm{mix}} < \tau < \infty$, and ...
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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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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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How to distinguish suspicious leverages?

Given a linear model and the following hatvalues and influence.measures, how can I say which measurements are suspicious? I mean ...
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I want to compare two calibrations with R… But cannot find the right answer

I first want to precise that I spent 2 hours searching for an answer, couldn't find something that was answering my question. So basically, I ran two calibration with my diagnostic test, so I ...
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How do you approach transformations when modeling?

I'm working with a simple univariate dataset and I've built several models for it. Some I think are fairly decent given that datas structure. In order to get a decent model I had to do some ...
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What convergence diagnostics are appropriate for a Bayesian hierarchical logistic regression model?

Using WinBUGS, I fit several Bayesian hierarchical logistic regression models for the mean of a binary response variable conditional on a set of criteria. I am now using CODA in R to determine if my ...
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R lmer Model Diagnosis qqnorm

I fitted this lmer model: m1 <- lmer(logR ~ N_g.m.2 * Year + (1|Wh/N_g.m.2), data = CO2_Ratio) Rendering the attached qqplot. ...
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Model assumptions and diagnostics for proportional hazard regression model with frailty in R

I am wondering are there any assumptions that must be met in the proportional hazard regression model with frailty? I remember that in regular proportional hazard model without frailty all variables ...
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98 views

VECM Diagnostic Test

I have got few questions about VECM and cointegration test. Basically I conducted a cointegration test on two time series (spot vs forward price) by using the Johansen procedure. The results suggest ...
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76 views

What plots should be used for diagnostics for linear mixed model?

Before fitting a linear mixed model, can any plots be used to show a random intercept/slope is justifiable in the model? I.e. these plots may indicate a different pattern for each individual over ...
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Help in interpreting AUC values from ordinal variables

I would appreciate if someone could explain to me the benefit of using area under ROC for evaluating agreements between two raters. Here is an example from two raters on, let's say, clinical time ...
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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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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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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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Model diagnostic tests for local linear regression

What are some of the model diagnostic tests which are used/ would be suitable to use for a local linear regression model? Note that this is not the least squares linear model, but rather a special ...
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How to apply diagnostics to regression model from FactoMineR

Many diagnostics to assess regression models are listed on this page: http://www.statmethods.net/stats/rdiagnostics.html ...
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Combining LR+ and LR- in naive Bayes

I've come across a colleagues who advocates combining both the positive likehood ratios and negative likelihood ratios in the calculation of posterior probability of the likelihood of a ...
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Arima Models Diagnostics

I'm doing a forecasting using seasonal ARIMA method. I'm using astsa package in r and I'm testing two models that I can't decide which one is better to use than the other The ACf and PACF for the ...
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How to compare diagnostic accuracy of two tests in unpaired data?

I am wondering whether I can compare diagnostic accuracy, sensitivity, specificity, positive and negative predictive values, and likelihood ratios, between two diagnostic procedures employed in two ...
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273 views

How to use the Glejser test?

Glejser tests for heteroskedasticity of a single independent variable within a multiple regression model. And, it tests it by conduction a basic regression: ABS(Residual) = intercept + slope(X). In ...
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How can I combine positive likelihood ratios?

I only have the positive and negative likelihood ratio, sensitivity and specificity for four diagnostic tests. How can I add them or combine them to obtain likelihood ratios? I do not have the ...
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How to combine diagnostic tests with only sensitivity spec, PLR and NLR

Hi ive looked at the other questions but this ones seems to be different as i only have the test results from different clinical exams in the way of sensitivity, specificity, PLR and NLR ex: facial ...
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346 views

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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Diagnostics for the analysis of variance model

I have problem with the diagnostic of the one way analysis of variance model (fitted in R). I've checked all the assumptions of the analysis of variance 1) "For each level of the within-subjects ...
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182 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 ...