Questions tagged [diagnostic]

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.

117 questions with no upvoted or accepted answers
Filter by
Sorted by
Tagged with
9
votes
0answers
251 views

When/why not to use studentized residuals for regression diagnostics?

Consider a linear regression $$ y=X\beta+\varepsilon. $$ Residuals $e:=y-X\hat\beta$ are often used as substitutes for the unobserved model errors $\varepsilon$ for validating assumptions such as ...
8
votes
0answers
341 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: $$D=\sum_{i=1}^{N}d_i^2$$ $$d_i^...
5
votes
0answers
2k 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 ...
4
votes
0answers
2k views

Influence plot for potential outlier detection from logistic regression in R

I am looking into identifying extreme values from their contribution to a binary outcome model. I have an unbalanced set and some extreme values which are part of the smaller set to predict (i.e ...
4
votes
0answers
76 views

Ill-behaved, nonnormal residuals of multiple regression: should I be concerned?

I have data on waist circumference (cm) (waist), gender, age and physical activity (vigorous MET minutes per week) (PA). I was trying to run linear regression in R on the model waist ~ gender + age + ...
4
votes
0answers
267 views

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 ...
4
votes
0answers
363 views

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 ...
4
votes
0answers
9k 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). ...
4
votes
0answers
6k 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 ...
3
votes
0answers
196 views

why Durbin Watson result could be so different from Ljung-box or Breusch–Godfrey test for OLS diagnostics

I have a residuals series from OLS regression (out.lm) where I do NOT have lagged dependent variable as a predictor. My residual series has about 1700 numbers. I ran ...
3
votes
0answers
308 views

Traceplots and gelman.rubin statistics for analysing convergence of mixtures of discrete and continuous distributions

I have a Bayesian hierarchical model which contains a number of distributions which are mixtures of a point-mass at zero and a continuous random variable. The model is fitted using a gibbs sampler. ...
3
votes
0answers
339 views

Observations aligned on PCA diagnostic plot: geometric interpretation?

The image below depicts the distance-distance plot for a (robust) PCA fit of a real data set. The distance-distance plot is described in greater detail on page 30-31 of (1) or page 2--3 of (0). It ...
3
votes
0answers
317 views

leverage.plot() R - CAR package

I'm trying to complete a homework regarding added-variables and leverage plots using the CAR package. In the documentation of the ...
3
votes
0answers
876 views

Identifying outliers in logistic regression model

I'm looking to identify outliers in a logistic regression model, e.g. ...
3
votes
0answers
516 views

How to interpret diagnostic plots for GEV distribution

I produced the following Diagnostic plots, from the following R Code: ...
3
votes
0answers
125 views

How should I interpret/follow-up on mixed logistic regression (GLMM) diagnostics?

I have experimental data (n subjects = 64) in which the response variable, accuracy (0 or 1), was measured 9 times within subjects. My predictor is Condition (A vs B) measured between subjects. I ...
3
votes
0answers
255 views

Can I compare different estimations approaches with AIC?

I'm running two different panel models. Model 1 is a Random Effects regression estimated using Maximum Likelihood and bootstrapped standard errors. Model 2 has the same main dependent variables and ...
3
votes
1answer
107 views

Check hazard proportional assuption in a large Cox regression model

I would like to check hazard proportional assuption in a large coxph. Usually I check it with cox.zph but with large coxph my p-values are very small whereas the $\...
3
votes
0answers
75 views

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 ...
3
votes
0answers
183 views

Verification of assumptions in TBATS model

I have a question about using BATS/TBATS models implemented in the forecast package for R. In De Liv­era, Hyndman & Snyder (2011) the models are used without any following analysis. Is it OK to ...
3
votes
0answers
1k 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 ...
2
votes
0answers
42 views

Check assumptions of linear regression before having the final model

There are usually four assumptions associated with a linear regression model: (1) linear relationship, (2) normal residuals, (3) homoscedastic residuals, and (4) i.i.d residuals. I think that it is ...
2
votes
0answers
31 views

Multiple linear regression and model build in light of regression diagnostics

I have a dataset of approx. 200 observations, consisting of Profit which is my dependent variable and is continuous, and the independent variables are Turnover (also continuous), and 3 additional ...
2
votes
0answers
104 views

Which method should be used for evaluating the linearity assumption of logistic models?

I’ve come across two methods for evaluating the linearity assumption for logistic regression (i.e., whether there is a linear relationship between continuous predictor variables and the logit of the ...
2
votes
0answers
151 views

OLRE's vs. Beta Binomial Model for Overdispersed Mixed Effect logistic regression with proportion data?

this is a long post, as I wanted to be sure to provide all relevant information regarding my data, model, the methods that I have tried so far, and my diagnostic plots. If there are ways I should ...
2
votes
0answers
602 views

Diagnostic testing of DCC-GARCH: implementation in R and interpretation

I am modelling the volatility spillover between SP500 and the USD/CNY from 2008 to 2018 with a DCC-GARCH(1,1) model as follows: ...
2
votes
0answers
791 views

Clusters of Residuals in Diagnostics Plot

I have a 1338x7 data set on which I am attempting to run a regression. The goal is to predict insurance charges based on the following predictors: age (cont), sex (0/1), BMI (cont), children (discrete)...
2
votes
0answers
338 views

What do people mean when they say dfbetas in glms

I will follow the notation in the following article in this question Williams, D. (1987). Generalized Linear Model Diagnostics Using the Deviance and Single Case Deletions. Journal of the Royal ...
2
votes
0answers
375 views

How do you get quantile normalized residuals for a t-distribution fit?

I've fitted a non-exponential family GLM regression model with the response distributed as a t-distribution with $\nu$ degrees of freedom, scale $\theta$ and mean $\mu = X\beta$. We estimate $\beta,\...
2
votes
0answers
55 views

How does one test for no autocorrelation between residuals and linearity in parameters?

I am using Stata and attempting to test for (1) no autocorrelation between residuals and (2) linearity in parameters. Attempts I've made for (1) The only test I've found so far for autocorrelation is ...
2
votes
0answers
66 views

MCMC diagnostics for EMC or SMC

Are diagnostics developed for MCMC (e.g. Gelman-Rubin, Geweke) suitable for output from Evolutionary Monte Carlo (EMC) or Sequential Monte Carlo (SMC)?
2
votes
0answers
352 views

Standardized residuals vs fitted values for Poisson regression

McCullagh and Nelder's book on glm suggest to plot standardized deviance residuals against either the linear predictor ($\hat{\eta}$) or the fitted values ($\hat{\mu}$) transformed to the constant ...
2
votes
0answers
199 views

When creating a multiple regression model for a subgroup, is it necessary to test all assumptions again?

My results section consists of a multiple regression analysis considering 3 factors, containing all of my participants. Following this, I have considered males and females separately, by construction ...
2
votes
0answers
222 views

How to decide between quasi-poisson and negative binomial?

I tried quasi-poisson and negative binomial glms on my counted data in R. The estimates are pretty much the same but p-value are different. Quasi-poisson gives insignificant result. NB give ...
2
votes
0answers
253 views

Problems in finding outliers and leverage points in non-linear regression

I'm implementing diagnostic of non-linear regression model $(y=ax^b)$. I'm trying to find out where outliers and leverage points in my model ...
2
votes
1answer
659 views

Statistical tests for comparing Positive/Negative likelihood ratios in two independent diagnostic tests

I have a problem regarding the comparison of the likelihood ratios in two diagnostic tests. The definition of positive likelihood ratio in screening tests is "the probability of a person who has the ...
2
votes
0answers
120 views

Independence of “residuals” in a Bayesian multilevel hierarchical model

So i'm having some problems realising what model checks I should do after fitting a bayesian model other than convergence diagnostics. Lets say i'm fitting a hierarchical bayesian regression model, I ...
2
votes
0answers
168 views

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 ...
2
votes
0answers
88 views

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 ...
2
votes
0answers
1k 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 ...
2
votes
0answers
73 views

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 ...
1
vote
0answers
27 views

Help understanding residual vs covariate plots in linear regression when covariate is transformed

I'm self-studying stats and in the books I've studying there usually aren't examples specifically dealing with residual plots for polynomial and spline fits. This has be thinking about residual vs ...
1
vote
0answers
19 views

How to find out about weird patterns in gam.check of a bam

I run a bam with timeseries data and a response variable defined as cbind(positive, negative), family = quasibinomial (because of overdispersion), a number of interactions, and some random effects. ...
1
vote
0answers
32 views

ARIMA Model Suitability Testing

I'm attempting to forecast 24-month hydroelectric generation at various river systems in the United States. Because river flows -- which is the primary driver behind hydro generation -- are mean-...
1
vote
1answer
25 views

Diagnostic Meta-Regression with mada in R

I am trying to figure out how to perform a meta-analysis of diagnostic test accuracy studies and I have a doubt that is driving me crazy. I am using the package mada written in R and following the ...
1
vote
0answers
28 views

Emergency Use Auth (EUA) for SARS-CoV-2 Tests

Problem: After the EUA for SARS-CoV-2 tests, we have a diagnostic test that passes both of the following criteria: All first five true-negative samples each produce a negative test result. All ...
1
vote
1answer
184 views

Diagnostic plot (residual vs. predicted) of a glmm using DHARMa

I used glmmTMB to fit a model with beta distributed errors, zero inflation, several nested random effects and temporal correlation. I then used the diagnostic plots available in DHARMa. My residual vs ...
1
vote
0answers
29 views

How to run a Sargan-Hansen test?

I'm estimating a model with a lagged dependent variable and fixed effects for panel units. I understand that this can result in Nickell Bias but I didn't think it would be a big problem because there ...
1
vote
0answers
42 views

Unusual DV Odds Ratio for multiple Binary Logistic Regression

I am attempting to diagnose issues with the DV odds ratio and resulting 95% CI for the final step of my logistic regression. As you can see in the below image, when the "Continuous F" variable is ...
1
vote
0answers
17 views

Biostatistics Advice: Comparing diagnostic / prognostic utility of 2 tests

I am a medical doctor not a statistician with some experience using STATA and SPSS. I am currently analysing a dataset looking at the prognostic value of two diagnostic tests at predicting clinical ...