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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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Why are my Hazard Ratio coefficients so large or small in Coxph regression?

I have some grade data for an institution I work at for a specific sub population and comparing it to retention over time. In the first table below are some hazard ratios from a coxph regression in R, ...
Tytalus's user avatar
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4 votes
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How to fit and perform diagnostics for (Linear) Mixed Effects Models on Rating data in R

I conducted an experiment where 143 test subjects (Interview) rated sets of 20 Stimuli (Stimulus) on a scale from 0 to 100. ...
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Diagnostic for GLM Gamma model in R

I am applying a glm model with gamma distribution and log link function to a continuous variable defined only on R+. I have tried to fit the model but I am having some difficulty interpreting the ...
GiulioSurya's user avatar
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3 way interaction, residual plot showing clustering across fitted values, do I need to account for grouping in a different way?

I have created a model with a three way interaction, analyzing how taste of bread (fr2) decreases over time (time2), and how skill of the baker (skill2) impacts longevity of taste, across different ...
Jackson's user avatar
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Is deleted residuals same as dffit [duplicate]

Is deleted residuals same as DFFIT? I was reading on identifying influential datapoints, and it confuses me. It seems to me that both means $\hat{y_i}-\hat{y_{i(i)}}$ thank you
Junho65's user avatar
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Which test do I use for checking chain convergence on an mcmc glmm with a factorial response variable?

I am running an mcmc glmm (mcmc package in R) with the following structure: continuous response variable + continuous response variable + factorial response variable ~ all of my covariates+etc. This ...
Juliette's user avatar
1 vote
1 answer
38 views

Why does the Gelman plot of a JAGS model start at 1000?

I am looking at the diagnostics of a Bayesian model using rjags in R. In particular, I am considering its Gelman-Rubin-Brooks plot. Independent of the number of ...
Lukas D. Sauer's user avatar
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Residual autocorrelation in ARMA-GARCH model

I have used the auto.arima function on my data set, which is the Ethereum-USD exchange rate, and I end up with an ARMA(2,2) model based on the AIC. I have estimated ...
Htcharnock's user avatar
4 votes
2 answers
229 views

What causes the parameter phi (precision) to be very small in beta regression (by betareg in R)?

I tried to do a beta regression for a variable affected by age and intimacy, but it did not work well. The value of phi (precision) estimated by maximum likelihood method is very small, and when I ...
TomoChang's user avatar
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16 views

Why does the serial.test function from the vars package in R yield contradictory results for type='BG', 'ES', and 'PT.asymptotic'?

I fitted a VAR model, individually all the residuals do not have autocorrelation, but if I use the serial.test I get different results: Type 'ES' Edgerton and Shukur (1999) Test p.value=0.99 Type 'BG'...
abraham granados carmona's user avatar
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1 answer
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Clusters in residuals v fitted diagnostic plot

I'm fitting a linear model in R with a (non-transformed) response variable and two independent variables: one of them is continuous and the other is numeric but treated as an ordinal variable with ...
S. Dolan's user avatar
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32 views

Assessing Model Fit for Cumulative Link Mixed Models (CLMM)

I have a CLMM model that accounts for repeated measurements within individuals (ID) over time, using mixed effects. ...
Bettina's user avatar
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0 answers
21 views

Necessary diagnostics of multiple quantile regression

I am wondering what are necessary statistics for multiple quantile regression model. I am considering creating a model e.g. using the quantreg R package: ...
Mikołaj's user avatar
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3 votes
0 answers
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Why do we check residual distributions in OLS when OLS is distribution free? [duplicate]

The way I see it, in OLS, we are geometrically fitting a line of best fit to some data. Unlike MLE (even though OLS and MLE give the same regression estimates for simple linear regression), there are ...
Uk rain troll's user avatar
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What critical level to use in diagnostic tests for model selection in forecasting?

I have been reading Hyndman & Athanasopoulos "Forecasting: Principles and Practice" (newest edition here) recently, and I noticed something that I regard as a possible inconsistency. On ...
Richard Hardy's user avatar
1 vote
1 answer
99 views

Issues with metaprop function for computing pooled specificity in meta-analysis

I am training to learn how to perform meta-analysis using R. I conducted a meta-analysis using the metaprop function in R with the provided dataset. The goal is to ...
Reza Khayami's user avatar
5 votes
2 answers
316 views

Residuals vs fitted values plot interpretation for "striped residuals"

I tried to run a simple linear regression in R, and when I check for the linearity, my "Residuals vs Fitted" graph is like this: Are the points randomly scattered? Or this showing a pattern ...
Reimy Tan's user avatar
3 votes
2 answers
182 views

Interdependence between leverages and residuals

According to the following online quote I read online: It’s worth noting that an observation can have a high absolute value for a standardized residual, yet have a low value for leverage. My ...
Andrea Catucci's user avatar
0 votes
1 answer
150 views

Impact of outliers to QQ plot

I'm trying to build an GLM regression (10k samples and 50 dimensions). I ran an analysis of the dependent variable since the regression has a normality assumption for the dependent variable. The QQ ...
cat's user avatar
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What are the main differences between a traditional receiver-operating curve and a Lorenz curve?

I am analyzing a dataset of cardiac echocardiographic exams, aiming to compare the diagnostic accuracy of a novel test in comparison to a standard one. I have recognized that using Stata I can ...
Giuseppe Biondi-Zoccai's user avatar
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Check linearity Residual vs Fitted Chart

I have a question about one of the simple linear regression test graphs. Looking at the graph it apparently appears to be linear but this curve is causing me a lot of doubt, I did another test that I ...
user avatar
2 votes
1 answer
28 views

ARIMA - Identifying an outlier in residuals

I am trying to perform an ARIMA (SARIMAX in fact) and when looking at the residuals I see a large outlier. I am using python statsmodels.tsa.statespace.sarimax. I ...
Solebay Sharp's user avatar
2 votes
1 answer
17 views

How to interpret this model diagnostics?

A model was fit as below: m1 <- lmer(log (ld50) ~ var * strain * time + (1|rep) + (1|rep:var) + (1|strain:env), dt) The response ld50 ranges from 0.15 (lower ...
Rabin KC's user avatar
2 votes
1 answer
84 views

GARCH diagnostics via standardized residuals: interpreting my findings

I have fit a GARCH(1,) model in Python, assuming the residuals are $t$ distributed. I am checking the standardized residuals. ARCH and Ljung-Box tests don't reject the null hypothesis. However, I am ...
Mattia's user avatar
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4 votes
3 answers
263 views

How to compare influence of outlier in regression model. ANOVA of two models in R

I am doing linear regression in R. I have identified an outlier in my data: ...
Mark Davies's user avatar
2 votes
1 answer
34 views

standardized residuals GARCH

I am having a hard time understanding ACF and PACF. I estimated a GARCH(1,1) model and now I am checking its standardized residuals. This is what I get: I can not really understand why the lag 0 has ...
Mattia's user avatar
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3 votes
1 answer
148 views

What aspects should I test from a fitted GARCH model?

I estimated a GARCH(1,1) assuming that the residuals follow Student-$t$ distribution. ...
Mattia's user avatar
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0 answers
9 views

Question about residual diagnostic tests in time series

I was reading a chapter from this book on residual diagnostics for time series data. The book presents Box Pierce and Ljung Box test statistics $Q = T\sum_{k=1}^lr_k^2$ and $Q^*=T(T+2)\sum_{k=1}^l(T-k)...
Yandle's user avatar
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60 views

Gamma GLM goodness-of-fit diagnostics and remedies for double glm

I’m looking for some help in diagnosing a gamma GLM. I am not sure whether the apparently poor fit is to do with the fact that my glm models dispersion rather than the mean, whether I am ...
Fiona's user avatar
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2 votes
2 answers
410 views

Understanding slope in plot of residuals vs. fitted values

How should I interpret the negative relationship between the residual and the fitted value in the plot shown below?
CCZ's user avatar
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1 vote
1 answer
41 views

How to diagnose HMC results like r-hat for a Mixture Model?

I have the following distribution $$ \begin{align} \boldsymbol \pi&\sim\text{Dirichlet}([1,\cdots 1]\in R^K)\\ \boldsymbol \theta&\sim P(\boldsymbol \theta) \\ \mathbf y&\sim \sum _{i=1}^K\...
wd violet's user avatar
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0 answers
43 views

Can linear regressions be used, given these diagnostic plots? [duplicate]

I'm using several linear regressions on a big dataset (about 1000 datapoints) with one numerical dependent variable and several independent variables (both dummy and numerical): ...
statuser's user avatar
2 votes
0 answers
62 views

Multinomial gam diagnostic help

I have created a Generalized additive model of a multinomial distribution using the mgcv package, I have used check.gam to do some diagnostic tests but they look ...
G_man932's user avatar
0 votes
0 answers
76 views

Correcting issues with binomial GLM (identified with DHARMa)

I'm working with a binomial GLM that I've fit in R using the glm() function. The percent of deviance explained is decent for my field (35%) and I don't think the residuals vs fitted plot looks too bad....
pfadenhw's user avatar
2 votes
0 answers
852 views

C-statistic vs AUC [closed]

I am analysing diagnostic accuracy. I have a dataset with a ground truth and 3 predictors. Ground truth = binary (0/1) Predictor 1-2 = binary (0/1) Predictor 3 = continuous (0-100) I have 50,000 ...
user12541161's user avatar
0 votes
0 answers
13 views

What is the best way for comparing the diagnostic performance of sequential testing? Log regression? Compare ROC?

I have two index tests, Test A and Test B, both of which have been studied in participants. Every participant also underwent the reference standard. I've found that Test A and Test B perform equally ...
Jorge's user avatar
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0 votes
1 answer
82 views

Residuals with mean 0 but with bigger standard deviation in regression

When I tried to fit a regression model to my data to predict a power variable using steam at entry and steam at exit variables in a thermal power plant, after taking care of outliers, etc... I fit the ...
Yahya SGHIOURI's user avatar
0 votes
0 answers
16 views

How to determine the best cut-off of measurement numbers for diagnostic decision?

I am currently doing a research on determining a cut-off of a ECG signal's number of 12 patients with their diseased/normal label that is produced by classifier for diagnostic decision purpose. ...
Dziban N's user avatar
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0 answers
17 views

Intercept residuals correlated with level-one residuals in MLM

I am running my ever first multi-level model. The model has three fixed effects and a random intercept by the grouping factor "participant id". The outcome variable is "bone mineral ...
Trypanosoma's user avatar
0 votes
0 answers
28 views

I need help interpreting diagnostic plots for a glm

I have used a function in the R package boot that give me diagnostic plots for a generalised linear model: glm.diag.plots(). I dont have experience with these, and ...
EcotoxicologyGirl's user avatar
0 votes
0 answers
36 views

Evaluating linear regression model [duplicate]

I understand that when performing linear regression, one common rule-of-thumb is that for a good 'fit', the residuals should be 1) independently distributed, 2) stationary and 3) not serially ...
joaocandre's user avatar
1 vote
0 answers
64 views

How to check assumptions for time series linear regression? [closed]

So, I am checking the assumptions for my time series data. I also did this test and it seems to reject the null hypotheses. Then, to check the equal variances, I made a box plot. So, I found that ...
Priscilla Raj's user avatar
10 votes
3 answers
687 views

How to get confidence interval for the population variance?

I have data that is reasonably assumed to be iid samples from some distribution. Our goal is to put a confidence interval on the population variance. Notationally, we have IID $X_i, i = 1, ..., n$ ...
travelingbones's user avatar
2 votes
1 answer
74 views

Techniques/diagnostics for gaining confidence in normality assumptions and resulting confidence intervals

I have data that is reasonably assumed to be iid samples from some distribution. Our goal is to put a confidence interval on the population mean and have something similar for the population variance. ...
travelingbones's user avatar
1 vote
1 answer
71 views

Comparing binary and continuous predictors for diagnostic test

There is a "traditional" biomarker (binary predictor) used in the diagnosis of a disease (binary outcome) that has a high cost to perform for the clinical labs. I'm studying alternatives, ...
Daniel Nunes's user avatar
1 vote
1 answer
75 views

Statsmodels VAR plot_acorr() amount of plots

I am working on a statsmodels VAR model to forecast some values and want to analyze the created model. In the examples and in some books I read about calculating the autocorrelation of the residuals ...
Krautsultan's user avatar
0 votes
0 answers
52 views

Whether my model follows the QQ plot and DHARMa residual in glmmTMB?

I ran this code and found the result. Could you please help me to figure out my model follows DHARMa residual? ...
Tanjijul Haque Tonmoy's user avatar
2 votes
1 answer
137 views

Validity of Automatic Portmanteau test for serial correlation vs Ljung-Box Test

I would like to model the Value-at-Risk of U.S. sector indices and the U.S. Broad Dollar Index using the variance-covariance method. To achieve this, I model the conditional means and variances of the ...
WebSurfer's user avatar
1 vote
0 answers
69 views

Concurvity involving categorical variables (?)

I recently learned how to test for concurvity on a GAMM I constructed, but I'm confused about how to test if 2 factors (2 categorical parametric terms), or 1 factor and a smooth term, are too closely ...
Nate's user avatar
  • 1,609
2 votes
1 answer
279 views

Understanding residual vs fit plot for mixed effect model with AR1 structure

I am running a linear mixed effects model for time series data using R-INLA. My response variable is normally distributed. The model has a random intercept, and temporal autocorrelation between data ...
user21085294's user avatar

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