# Tagged Questions

Refers to the property of a random process to have non-constant variance along some continuum. This most commonly presents in regression where the error variance increases as a function of one or more predictors, but also commonly refers to a time series whose variance changes over time.

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### When conducting a t-test why would one prefer to assume (or test for) equal variances rather than always use a Welch approximation of the df?

It seems like when the assumption of homogeneity of variance is met that the results from a Welch adjusted t-test and a standard t-test are approximately the same. Why not simply always use the Welch ...
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### Checking ANOVA assumptions

A few months ago I posted a question about homoscedascity tests in R on SO, and Ian Fellows answered that (I'll paraphrase his answer very loosely) "homoscedascity tests are not a good tool when ...
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### Transforming proportion data: when arcsin square root is not enough

Is there a (stronger?) alternative to the arcsin square root transformation for percentage/proportion data? In the data set I'm working on at the moment, marked heteroscedasticity remains after I ...
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### Measures of residuals heteroscedasticity

This wikipedia link lists a number of techniques to detect OLS residuals heteroscedasticity. I would like to learn which hands-on technique is more efficient in detecting regions affected by ...
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### Regression modelling with unequal variance

I would like to fit a linear model (lm) where the residuals variance is clearly dependent on the explanatory variable. The way I know to do this is by using glm with the Gamma family to model the ...
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### What are the dangers of violating the homoscedasticity assumption for linear regression?

As an example, consider the ChickWeight data set in R. The variance obviously grows over time, so if I use a simple linear regression like: ...
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### Advice on explaining heterogeneity / heteroscedasticty

I am looking for any help, advice or tips in how to explain heterogeneity / heteroscedasticity to biologists in my department. In particular I want to explain why its important to look for it and deal ...
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### Linear regression, heteroscedasticity, White's test interpretation?

I am trying to test whether my regression has an issue of heteroscedasticity. After running a regression, I can clearly see that the residual plot has a pattern. After taking a log of the dependent ...
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### What to do with heterogeneity of variance when spread decreases with larger fitted values

I am trying to produce a linear mixed model the R code is as follows. lme(Average.payoff~Game+Type+Others.Type+Game:Type+Game:Others.Type+Type:Others.Type,random=~1|Subjects,method="REML", ...
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### Interpretation of the p-values produced by Levene's or Bartlett's test for homogeneity of variances

I have run Levene's and Bartlett's test on groups of data from one of my experiments to validate that I am not violating ANOVA's assumption of homogeneity of variances. I'd like to check with you guys ...
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### Spearman's or Pearson's correlation with Likert scales where linearity and homoscedasticity may be violated

I am wanting to run correlations on a number of measurements where Likert scales were used. Looking at the scatterplots it appears the assumptions of linearity and homoscedasticity may have been ...
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### Whether to use robust linear regression or bootstrapping when there is heteroscedasticity?

I have a dataset where I need to do linear regression. Unfortunately there is a problem with heteroscedasticity. I´ve rerun the analysis using robust regression with the HC3 estimator for the variance ...
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### Brown-Forsythe and Welch f-ratios in two-way ANOVAs?

I understand that in One-Way ANOVA two alternative F-Ratios have been derived to be robust when homogeneity of variance has been violated. Tomarkin and Serlin (1986) review amongst other techniques ...
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### Calculate Newey-West standard errors without an lm object in R

I asked this question yesterday on StackOverflow, and got an answer, but we agreed that it seems a bit hackish and there may be a better way to look at it. The question: I would like calculate the ...
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### How to run two-way ANOVA on data with neither normality nor equality of variance in R?

I am working on my master thesis at the moment and planned on running the statistics with SigmaPlot. However, after spending some time with my data I came to the conclusion that SigmaPlot might not be ...
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### Kruskal-Wallis or Fligner test to check homogeneity of variances?

I have a doubt, I need to check the homogeneity of variances on the residuals of a linear regression. I read that Kruskal is also good without assuming a normal-distribution. But I don't know if it's ...
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### Linear model Heteroscedasticity

I have the following linear model: To address the residuals heteroscedasticity I have tried to apply a log transformation on the dependent variable as $\log(Y + 1)$ but I still see the same fan ...
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### Model errors, residuals and heteroscedasticity

I have a quick question about the correct way to describe variance functions when seeking to cope with heteroscedasticity. As I understand it the statistical error of a model represents the departure ...
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### Examples of Hetero- and Homoscedasticity with the Same Dependent Variable?

What are good examples to show that, even if a regression of $Y$ on $X$ is heteroscedastic, a regression of $Y$ on a different independent variable $Z$ could be homoscedastic? More formally, what are ...
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### Weighted least squares to correct for heteroscedasticity

I would like to use a weighted least squares (WLS) regression to perform tests on heteroscedastic spatial data. Each data point represents the mean of some variable over an area, and the sample sizes ...