Questions tagged [heteroscedasticity]

Non-constant variance along some continuum in a random process.

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Varying dispersion parameter (=dispformula) in glmmTMB in R to account for heteroscedasticity that originates from one predictor

I struggle with understanding the dispersion model and dispersion parameter of glmmTMB , and could not find answers anywhere. I constructed a GLMM using ...
eab's user avatar
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What are the differences between HC estimators and their small sample properties?

I am currently using R to run regression with the following code: ...
Brennan's user avatar
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Robust Gamma Regression

I am modeling some spectroscopic data where the response of the instrument to the size of the input is strictly positive and non-linear. Gamma regression seems like a good choice to explain the data, ...
udushu's user avatar
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How to correct for heteroskedasticity in fixed effects panel regression with correction for clustered standard error?

I am a student at RSM and I have a question regarding my regression analysis for my thesis as I have encountered issues I do not know how to deal with. I have performance data (dependent variable) of ...
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The shortest confidence interval (in the sense of expectation) for two sample t test when variances are unknown and unequal

I have had a question since graduate school. For a given significance level alpha, the test with smallest confidence interval length expectation should be optimal, because it usually also means a ...
Chang Wang's user avatar
5 votes
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Why is homoscedasticity (homogeneity of variance) important in neural network layers?

I'm studying the famous Xavier initialization paper (Understanding the Difficulty of Training Deep Feedforward Neural Networks (Glorot and Bengio, 2010)) and had a question. When they explain the ...
Sean's user avatar
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Consequences of heteroskedasticity for regression with correlated errors

What are the statistical consequences of heteroskedasticity for regression models where the errors are correlated, e.g., due to spatial or phylogenetic autocorrelation? For example, consider a ...
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Techniques for addressing the homoskedasticity and normality assumption violations in mixed models with a non-all-positive response variable

I have a mixed model which the heteroskedasticity and normality assumptions for the residuals are violated. Up to this point, I have been addressing that by using the ...
Katie's user avatar
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Do asymptotic statistics "solve" the Behrens-Fisher problem?

The Behrens-Fisher problem concerns comparing two means from independent (maybe multivariate) samples in a way robust to heteroskedasticity in the populations being compared. It seems that if one ...
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Optimal block size for spatial bootstrapping

Take a regression model: $$ y_s = X_s\beta + \epsilon $$ Where $E[\epsilon|X] = 0$, but $cor(\epsilon_s, \epsilon_{near}) > cor(\epsilon_s, \epsilon_{far})> 0$. In other words, $X$ is ...
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Test for heteroscedasticity of continuous variables in R similar to betadisper()?

Before using adonis() with factors as explanatory variables in R, it is important to check for group dispersion (betadisper()) so that you know whether your significant p-value from adonis is real, i....
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Multiple comparison of non-normal, heteroscedastic data. What test should I use?

I have a set of brain pathology data. These were obtained by counting certain parameters in the brain. Due to availability of human brains, the amount of cases vary a lot across the different groups ...
hintursul's user avatar
4 votes
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Scientifically reasonable or not ? exclusion of very, very uncertain values from statistical analysis

I have 5 treatments A1 .. A5 and 4 independent individuals per treatment, whose parameter X is of interest to me. My objective is to compare X among treatments, and see if one or more treatment ...
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Assumption violations with heteroscedastic data and OLS regression

I'm trying to model the typical performance of an experimental approach I've developed. I have a total of 3000 observations for 72 different case studies. My observations consist of a reading for <...
Anonymous Coward's user avatar
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Parametric segmented or piecewise regression with heteroscedastic errors

I am fitting longitudinal data with an increase in variance over time. The standard physiological model is a bi- or tri-linear model with variable breakpoints. The estimated parameters are used to ...
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Regression model with heteroskedasticity in both variables

I've been learning (lurking) from this site for a while and I finally have a question I haven't seen answered yet. I'm doing a flight test and trying to fit the resulting data to linear line. From a ...
achase90's user avatar
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prediction interval for heteroscedastic data

Here are some data: ...
Stéphane Laurent's user avatar
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Can I conclude heteroskedasticity in this case?

I plot a standardized residuals against the fitted values and it does exhibit a megaphone shape. It looks like there is more variation in the lower level of fitted values. I then conduct a Breusch-...
rodericktung's user avatar
3 votes
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Comparison of variances with multiple factors using fligner kileen test

Hope my question fits in here and I have described everything well enough. Somehow I cant quite get my head around it. I have a data set with pesticide residue data in flowers, which had been obtained ...
Fee's user avatar
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Why do heteroscedasticity-robust standard errors in logistic regression?

I am following a course on R. At the moment, we are working with logistic regression. The basic form we are taught is this one: ...
SnupSnurre's user avatar
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why arima uses differencing transform not the log transform to make data stationary?

I am currently working on time series project and i am naive. I would like to ask, there exist strict stationary, differencing stationarity. If i understood correct the first order differencing ...
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Heteroscedasticity in GLMM

I'm after some advice regarding heteroscedasticity in a residuals vs predicted plot. I have measured the length of a group of animals at birth and then at five subsequent time points into the future. ...
Pat Taggart's user avatar
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52 views

(G)LM prediction interval with heteroscedasticity

I am trying to get prediction intervals from some non-linear data which also exhibits heteroscedasticity. ...
user2974951's user avatar
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3 votes
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Test for non-normal data with homogeneity of variance

I'm new to the platform and would like the following question to be answered: I have performed a latent class cluster analysis with 28 variables and 9000 observations, for which I am currently ...
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Failure to replicate calculation of PCA residuals in linear regression with heteroscedasticity

In their preprint, Rocha et al. suggest a new type of residual for linear regression models with heteroscedasticity. They call their new residual PCA residuals. I have tried to replicate some of their ...
COOLSerdash's user avatar
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ANOVA with post hoc for non-normal data with unequal variance

I have 200-some variables with 25,000 observations in each of 4 categories. For each variable individually, I need to identify where we have variability between categories. Therefore, I need an ...
Alicia's user avatar
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Robust Regression in MATLAB's robustfit: what is the optimal weight function to tackle heteroskedasticity?

I'm currently performing a linear regression analysis and encountered a fair amount of heteroskedasticity. Increases in predicted values go along with decreases in residual variance. Otherwise, the ...
mzunhammer's user avatar
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Should I test for heteroskedasticity when I run unit root tests?

"The Phillips-Perron (PP) unit root tests differ from the ADF tests mainly in how they deal with serial correlation and heteroskedasticity in the errors." Zivot (2005) Modelling Financial Time Series ...
Fabio A. Correa's user avatar
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693 views

Bayesian Linear Regression: Error heteroscedasticity with conjugate form?

I was wondering if there are any ways of modelling a regression with heteroscedastic normal errors in conjugate form using Bayesian Linear regression. I.e., is there a conjugate form for the model \...
Jeremias K's user avatar
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3 votes
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261 views

Cross-validation and testing for linear regression on small heteroscedastic data sets

I would like to perform simple linear regression on a data set ($y_i = a x_i + b + \epsilon_i$) with $N \approx 50$. However, my residuals $\epsilon_i = \epsilon_i(x_i)$ exhibit heteroscedasticity as ...
physguy's user avatar
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How appropriate is it to fit a regression line through median values?

I have a data set of tone separation (ranging from 1-3 octaves, plotted on the x-axis) vs. subject performance (y axis) through which I am fitting a regression line. The problem is that I have many ...
Ellen's user avatar
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3 votes
0 answers
531 views

Evaluating hetroskedasticity in a binomial residuals vs. fitted plot in glmer?

I am trying to validate the goodness of fit of a model in glmer using residuals plotting. I went through many threads here related to this but still I am not sure that the solutions offered apply to ...
Shad's user avatar
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1k views

Linear regression with trimmed data

I would like to know how experts deal with real data. Even if statistical text books uses real data I'm always surprised how good the real data are and at the end of the exercises the residuals are ...
giordano's user avatar
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3 votes
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287 views

Assumption of homogeneity of variance when performing an independent t-test with bootstrap

An important assumption of the independent-samples t-test is that the two group's variances are equal in the population. To test whether these variances are different in the population, we can perform ...
mat's user avatar
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Unbalanced Panel data using R - Removing outliers and heteroskedastcity

I am new in R and it’s my first time using it so I’ll appreciate the help. I am estimating income elasticity for electricity consumption using budget shares. I have data for 8 regions categorized into ...
Fadhila Alfaraj's user avatar
3 votes
0 answers
1k views

Heteroskedasticity and autocorrelation in simple linear regression?

While looking through a simple linear regression, I noted the presence of both heteroskedasticity and autocorrelation, and am looking to understand the consequences of each. On this project, I am not ...
Matt's user avatar
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How to compare three groups to one control group without assuming equal variances?

I need to determine if one dependent variable (tensile strength) for each of three new groups is equivalent to that from my original ("control") group. I am not concerned with how the three new groups ...
materials_analyzer's user avatar
3 votes
0 answers
478 views

heteroskedasticity in logit/cox

I am using a logit and a cox proportional hazard model for my analysis, and the newest version of Stata. I have found that there are no tests to check for heteroskedasticity for logit/probit models, ...
Wateep's user avatar
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3 votes
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813 views

Simple Linear Regression - Prediction Interval and Non-constant variance

I have two questions about a simple linear regression model. I want to use test1 scores to predict test2 scores. I am using R software. x=test1, y=test2, Let's say that both tests are scored from 1 ...
user61575's user avatar
3 votes
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78 views

Estimate power for linear model with Bernoulli-distributed error

I want to estimate a linear model for a phenotype $y_i$ defined by a liability threshold model, using observable data $x_i, c_i$. $$y_i = \mu + \beta x_i + \epsilon_i$$ $$\text{Pr}(\epsilon_i | x_i, ...
Michael K's user avatar
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3 votes
0 answers
444 views

Testing for multiple conditional heteroskedasticity in multivariate regression

Briefly, I am looking for an extension of the Breusch-Pagan test to the case of multivariate dependent variables. The scalar form of the test, with multiple regressors, assumes the model \begin{...
shabbychef's user avatar
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3 votes
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95 views

Relationship between $\text{Cov}(x_i^2, e_i^2)$, the asymptotic variance of b under homoscedasticity and heteroscedasticity?

I am trying to figure out the relationship between $\text{Cov}(x_i^2, e_i^2), V$ and $V_0$, where: $V=$ asymptotic variance of $\sqrt{n(\hat{\beta}-β)}$ under heteroskedasticity, and $V_0=$ ...
user40908's user avatar
3 votes
0 answers
1k views

How to constrain covariance parameters in sas proc mixed?

I would like to test whether 3 dependent variables (measured with the same participants) differ in variance. My plan is to fit one model in which the 3 variables have the same variance, and one model ...
user38429's user avatar
3 votes
0 answers
3k views

Homoscedasticity violation: repeated-measures ANOVA

My study is a clinical trial with 2 treatment groups measured over 4 time points...with the outcomes assessed being blood levels. So my independent variables are "treatment" (2 groups) and "time" (4 ...
elsa's user avatar
  • 31
3 votes
0 answers
1k views

Negative Binomial Regression and Heteroskedasticity test

I am running a negative binomial regression in Stata and would like to know if I need to include the vce(robust) option in the model. I know the negative binomial ...
atwell17's user avatar
3 votes
0 answers
1k views

Wild cluster bootstrap seems really simple. Too simple. Am I missing someting?

I've been dealing with the problem of how to construct confidence intervals on penalized spline estimators in the presence of cluster-wise auto-correlation and heteroskedasticity. My previous thread ...
generic_user's user avatar
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3 votes
0 answers
291 views

Comparing model fit with heteroscedastic data

I am developing a physiological test using R that requires some parameters optimised. In comparing the new method against the existing method, the values of individual readings correlate in a linear ...
Marc Sarossy's user avatar
3 votes
1 answer
286 views

How to test homoscedasticity when the errors are DEPENDENT?

I have done a linear regression and plot the residuals. I noticed that the errors are dependent(autocorrelated), how could I test homoscedasticity of this series? I read that Breusch-Pagan test only ...
Dail's user avatar
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3 votes
0 answers
326 views

Two-sample t-test / ANOVA on functions, with unequal variances

Suppose $N$ experiments can be made in varying conditions. Each of them yields an estimate $f_i$ of a continuous (and, if necessary, positive) function of x over some interval. Experiment $i$ is ...
yannick's user avatar
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3 votes
1 answer
526 views

How to deal with heteroscedasticty: choosing between White, WLS or Log linear model?

I am dealing with heteroscedasticity, and as we learned several methods to deal with the issue, I would like your help in choosing which one. The problem comes out of the econometrics book of Verbeek....
Kasper's user avatar
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