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.

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Two diagnostics tests over time

I have the following problem. I want to compare a self-diagnostics tool (questionnaire based) with a gold standard diagnostic tool. However, I have the following issues: 1- The gold standard is not ...
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combine Accuracy of two diagnostic test

How can one calculate combine accuracy of two independent diagnostic test on the Same population to increase the diagnostic accuracy
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Diagnostic plots GLM [duplicate]

I done a binary regression,it's possible that the the plot of residual vs Predict has two different line? I never see before one like this
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problem with diagnostic plots for binary regression

I make a binary regression to study Italy's poverty/non poverty on R. mod1<-glm(status~CLETA5+cit+AREA3+Q+studio+ACOM5+godabit,data=total,family=binomial) I don't know if the diagnostic plots are ...
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rstandard vs stdres have different behaviour (the hat matrix)

To obtain the standardized residuals in R, the the residuals minus their mean are divided by their standard deviation (calculated with the model degrees of freedom). It is also calculated using the ...
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28 views

Why we do acf on residuals?

In the book "Time series analysis" by Shumway. He is doing fit = lm(chicken~time(chicken), na.action=NULL) acf(resid(fit), 48, main="detrended") What is the ...
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t-value of regression intercept

Consider a regression model $y = \beta_0 + \beta_1 x + \epsilon$, where $\epsilon$ is a standard normal random variable. The estimate of the intercept is $\hat{\beta}_0 = \bar{y} - \hat{\beta}_1\bar{x}...
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Using the DHARMa package to test for temporal autocorrelation when time values are not unique?

I have fit a glmm using the glmer function from the lme4 package. I have found the DHARMa package very helpful for evaluating the fit of my model but am stuck as to what to do to evaluate temporal ...
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52 views

Diagnostics in DHARMa for glmmTMB model

I am fitting models to a data set with 370 observations. It is ecological data with overdispersed counts as a response variable. I have used the DHARMa package to show this overdispersion from a ...
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24 views

Finding the Case with the Highest Influence

I'm new to regression and diagnostics so if this seems a bit basic/unnecessarily long-winded that's why. I perform a multiple regression of a response variable on four predictor variables. There are ...
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39 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 ...
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Samle size calculation for paired comparative diagnostic accuracy study

I would like to estimate an appropriate sample size for a medical imaging study. I prefer to use R. A standard thest testS will be compared to a modified standard ...
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1answer
125 views

Regression diagnostics for ordered logistic regression

I am doing a regression with an ordinal dependent variable (answers ranging from very good to very bad) for the first time. The model itself seems to be working fine. I have no idea however which ...
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44 views

I tested serial correlation and got a p-value of 0.13, can I accept that there is no serial correlation?

My data are 6 variables × 68 data. Null hypothesis is there is no serial correlation. Is p=0.13 too small? it is very close to 0.1. The significance level I choose is 0.05 though.
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How do I analyze this linear regression residual plot?

I need help interpreting the residual plot and model diagnostics. I built a model for number of ticket sales for an event. so the dependent variable is a continuous variable. Below is how the ...
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19 views

Simulate multivariate outliers

Considering a multivariate linear model $\boldsymbol{Y = XB + E}$, where $\boldsymbol{Y, X, B}$ and $\boldsymbol{E}$ have dimension $n \times m$, $n \times p$, $p \times m$ and $n \times m$, ...
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What is gained from a scale-location plot?

The plot function in R provides four diagnostic plots for linear regression: It seems like the residuals vs fitted plot and the scale-location plot are basically ...
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High GLMER dispersion parameters

I am running a glmer with a random effect for count data (x) and two categorical variables (y and ...
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63 views

Picking a model: Diagnostics or Model Strengths

I am building a lot of models and want to pick one to use for predicting. I am using linear regression, elastic net, and partial least squares regression. I know my data is highly correlated and that ...
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Polynomial Regression with grouped independent observations

I am trying to model how porosity changes across burn up levels of a fuel pellet. I have 300 observations at varying levels of burn up. The way my data is collected makes burn up appear as a ...
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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 ...
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Is my model any good, based on the diagnostic metric ($R^2$/ AUC/ accuracy/ RMSE etc.) value?

I've fitted my model and am trying to understand whether it's any good. I've calculated the recommended metrics to assess it ($R^2$/ AUC / accuracy / prediction error / etc) but do not know how to ...
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60 views

Conflicting residual diagnostics for GLMM for binary data: zero-inflation

I fitted a mixed logit model with crossed random effects in lme4_1.1-21::glmer to some experimental binary data. The maximal random-effect structure justified by ...
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54 views

Diagnostic plot of glmm model

I am very new to R and I have a problem with the diagnostics of my models...can anyone help me please? I have run my model: ...
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135 views

Overdispersion tests from DHARMa and sjstats: conflicting results?

I ran some models for my count data, and did some diagnostics to check for overdispersion. Here is a dharma graph, which as I understand, indicates no overdispersion. And this is the result I get ...
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Can positive and negative likelihood ratios be combined into one parameter?

Positive and negative likelihood ratios (PLR, NLR) are considered to be much better than sensitivity and specificity as parameters of usefulness of a test. Is it possible to combine PLR and NLR into ...
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204 views

DHARMa diagnostics: testDispersion and testZeroInflation interpretation

I have been analyzing count data using Poisson distribution in glmmTMB, and just ran some DHARMA diagnostics. However, there don't seem to be a lot of help online on how to interpret the results. Does ...
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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 ...
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Is there formal test of non-linearity in linear regression?

In logistic regression there is Box-Tidwell but I know of nothing like that in linear regression. I use partial residual plots to look for this, a graphical feature, but would love to find a formal ...
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How to read lm() plots for models with factors

I'm trying to get a handle on how to read the Residuals vs Fitted and Scale-Location plots of lm() objects when the predictors are a mix of continuous and factor ...
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Confused by Cook's Linear Related Predictors

Chapter 19 of Cook and Weisberg's Applied Regression book is entitled "Visualizing Regression with Multiple Predictors" and discusses when diagnostic plots are valid. They say "we need conditions on ...
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What diagnostic tests are mandatory for VECM?

I have finished a test of VECM, I have included Breusch-Godfrey Serial Correlation LM Test and Heteroskedasticity Test (Breusch-Pagan-Godfrey). Not sure are these sufficient? Do I need to do other ...
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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 ...
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64 views

Between-subject fMRI classification: subjects with different number of runs

The main purpose of my work is to discriminate patients vs healthy controls using fMRI and multivariate pattern analysis (MVPA). Since I want to classify at the subject level I performed a separate ...
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model diagnostic using plot(model) in r: return the suspicious values

plot(model) gives us a number of diagnostic plots with regards to the model we build. In these plots, if there are suspicious values (values which might decrease model performance), their index is ...
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How can you test dependence for non-Gaussian standardised residuals?

Let's say you fit an ARMA-GARCH model to financial data and find that the standardised residuals are non-Gaussian through the Kolmogorov-Smirnov test. These residuals have mean -0.002 and standard ...
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73 views

If diagnostics for multiple linear regression are ok, are diagnostics of the component variables needed?

This is a follow-on question from here. I received two conflicting answers to the question posed in the title of this post. The diagnostics of the multiple regression looked okay (see link), but it ...
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863 views

Rules of thumb for partial residual (component + residual) plots as diagnostics for linearity?

Here are the standard R diagnostic plots of a multiple linear regression model that includes an autoregressive term at lag-1 (i.e. AR(1)). I have logged & z-scored my input data. Ben Bolker says ...
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38 views

What are the diagnostic measures for linear regressions?

I am working with the BostonHousing dataset. I have created a number of models and I'd like to select amongst them. ...
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1answer
1k views

Jarque-Bera test for Normality

Which test should I consider if by JB-test result I have heteroscedasticity and by the result of two others no. $JB JB-Test (multivariate) data: Residuals of ...
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1answer
802 views

Interpreting Regression Diagnostic Plots

I'm sorry if this is a broad question but can someone explain to me how to interpret these regression diagnostic plots? I understand the Normal Q-Q show's how normal the spread of the data is, but the ...
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1answer
119 views

GAM using a cyclic spline improves residual structure but reduces fit

I'm working on a dataset monitoring soil moisture levels throughout the summer. The general trend in the data is the following: When I use a GAM with default thin-plate spline and AR(1)process there ...
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MCMC - Diagnostics plots

I am currently using MCMC for Bayesian Inference and am now plotting diagnostics plots. While I understand what I am looking for in a trace plot, I am not so sure about the cumulative quantile plot ...
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567 views

How can I check model assumptions in AFT survival model?

I am working with interval censored data and I am fitting an AFT model with the survreg() function from the survival package. ...
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144 views

Failing to implement Bayesian Chi2 goodness of fit test

I am trying to implement one of the methods described in Valen Johnson's A Bayesian Chi-Squared Test for Goodness of Fit. It presents a couple of variants depending on whether the random variable of ...
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101 views

CUSUM test for a Nonlinear Regression Model

I would like to do a CUSUM test for the regression parameters of a nonlinear regression model to analyze possible parameters variations. For linear regression models the CUSUM test is based on the ...
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1answer
82 views

Linear regression very significant βs with multiple variables, not significant alone

Could anyone provide intuition on why for y ~ β1x1 + β2x2 + β3x3, β1 β2 and β3 can be significant in a multiple variable model (p range 7x10-3 to 8x10-4), but the βs are not significant in separate ...
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30 views

estimate probability that sensitivity/specificity greater than threshold value

Is there a Bayesian method to estimate the probability that the sensitivity of a diagnostic test is greater than some value, say 0.70? Rather than estimate sensitivity and a confidence interval (e.g., ...
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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: ...
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1answer
191 views

What should I do after multiple imputation in the data?

I have a data set with missing observations. I used VIM package in R for imputation. After imputation, I will try to run a ...