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.
3
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1answer
322 views
How can these residuals have homogeneity of variances?
I'm testing the Homogeneity of Variances with Fligner-Killeen test using the function fligner.test in stats
On the chart below I have plotted the residuals that pass this test ...
5
votes
1answer
174 views
Inference in linear model with conditional heteroskedasticity
Suppose I observe independent variable vectors $\vec{x}$ and $\vec{z}$ and dependent variable $y$. I would like to fit a model of the form:
$$y = \vec{x}^{\top}\vec{\beta_1} + \sigma ...
3
votes
3answers
2k views
Why is the Breusch-Pagan test significant on simulated data designed not to be heteroscedastic?
I'm testing the residuals of a linear regression using Breusch-Pagan Test to detect Heteroscedasticity.
This is the plot of the residuals:
and this is the R code:
...
4
votes
2answers
204 views
ANOVA for non-normal heterogenous unequally replicated data
I need some advice on how to proceed with my data analysis. I have 3 groups (Archaea, Bacteria and Eukarya). Each group has unequal number of individual species (70, 651, and 244 respectively). Each ...
2
votes
0answers
156 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 ...
8
votes
2answers
4k views
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 ...
11
votes
2answers
3k views
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 ...
5
votes
2answers
229 views
Measuring homogeneity across different spatial aggregations of data
I'm working with dataset of individual households that I aggregate into 'areas' using several different spatial configurations, from smaller to bigger.
These areas are then characterized by four ...
6
votes
2answers
6k views
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 ...
8
votes
3answers
948 views
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 ...
4
votes
1answer
216 views
Is there an exact version of marginal homogeneity test?
Here's what I know:
I have read the chapter (p347ff) in Agresti, 1990, regarding dependent two-way tables, and I believe I understand the basics. My problem is that Agresti's model-based approaches ...
3
votes
2answers
4k views
How do I interpret the results of a Breusch–Pagan test?
In R I can perform a Breusch–Pagan test for heteroscedasticity using the ncvTest function of the ...
7
votes
3answers
5k views
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 ...
3
votes
2answers
1k views
Why do I get different heteroscedasticity robust standard errors in R when using the plm package?
I am now writing my bachelors thesis and I have come across some difficulties. I am about to do some panel regressions with time and entity fixed effects and I would therefore like to use the plm ...
4
votes
3answers
732 views
Can you use heteroskedastic time series variables within a regression model?
We are working on a multivariate linear regression model. Our objective is to forecast the quarterly % growth in mortgage loans outstanding.
The independent variables are:
1) Dow Jones level.
2) % ...
6
votes
1answer
2k views
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 ...
7
votes
2answers
844 views
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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vote
2answers
815 views
Auxiliary Model in the White Test
Why in the white test, we estimate auxiliary regression model of the squared residuals (in the original model) and not just plain residuals?
4
votes
1answer
786 views
Calculating probability for bivariate normal distributions based on bootstrapped regression coefficients
Dear all,
I was encouraged to ask this question here as well as on stackoverflow and would be very appreciative of any answers...
Due to hetereoscedasticity I'm doing bootstrapped linear regression ...
11
votes
4answers
1k views
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 ...
7
votes
2answers
706 views
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 ...
5
votes
2answers
2k views
When to use (non)parametric test of homoscedasticity assumption?
If one is testing assumption of homoscedasticity, parametric (Bartlett Test of Homogeneity of Variances, bartlett.test) and non-parametric (Figner-Killeen Test of ...
22
votes
6answers
1k views
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 ...
