a random process that has non-constant variance along some continuum.

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10 views

How to test for serial correlation with pooled OLS, FE an RE?

I have pooled data for 3 years, and I have come across the problem of serial correlation. Some books mention the problem of serial correlation when pooling the data. My question is: is it possible to ...
4
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2answers
61 views

Robust regression - a better understanding

I looked at robust regression for the first time today and I am a bit confused, comparing it to something like ordinary least squares and I am not sure if I am on the right track. I read a few ...
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0answers
6 views

testing for heteroskedasticity with Breusch Pagan in time series

I want to use a Breusch-Pagan test with time series data, I have regressed the residual on the independent variables and added a lag for the dependent variable: is this the right way to be going ...
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1answer
20 views

Appropriate homogeneity test for meta-analysis

I'm looking at measures from different studies (for a meta-analysis) and hoping to provide an aggregate effect size. I'm trying to identify hetero-/homo-geneity to determine whether I should use a ...
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2answers
103 views

Efficiency of beta estimates with heteroscedasticity

I need something clarified and that is when you have non-constant variance, estimates won't be biased but will be a problem when it comes to the S.E. formulas and efficiency. Therefore OLS estimates ...
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1answer
16 views

Heteroscedasticity filter for time series

I am looking for a method or package in R that can remove heteroscedasticity from time series. Specifically, I have a number of time series to which I want to fit a VAR model. Each time series may or ...
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1answer
42 views

How should you fit ANOVA and linear regression models, if the equal variance assumption is violated?

This is my topic for the paper I'm working on for an undergrad stats class. It's supposed to be 20 pages... and I'll be honest, I understand very little beyond the basics and am over my head. From ...
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2answers
55 views

Homoscedastic and heteroscedastic data and regression models

How to understand the homoscedasticity and heteroscedasticity in context of regression models? Is there a way to check these properties in R?
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0answers
11 views

Homogeneity of Variance, 2 Way Completely Crossed Design

I am looking for some advice as to how I might handle having an unfavorable Levene's test outcome, that is to say a highly significant value. DOE Various containers with water were microwaved for ...
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1answer
97 views

Detecting heteroscedasticity - Can I use Breusch-Pagan Test on binary logistic regression?

I'm currently testing a (binary) logistic regression model, which seems to have at least some issues with multicollinearity. Now I don't really trust the data anymore and would like to also test it on ...
3
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2answers
192 views

Why does sphericity diagnosed by Bartlett's Test mean a PCA is inappropriate?

I understand that Bartlett's Test is concerned with determining if your samples are from populations with equal variances. If the samples are from populations with equal variances, then we fail to ...
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1answer
60 views

Does heteroskedasticity matter if you have a large enough sample?

Let's say you run a regression with over 200 observations. Would this reasonably large sample mitigate the impact of residuals heteroskedasticity as an offshoot of the Central Limit Theorem, or ...
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0answers
15 views

Standard Deviation Grows Quadratically with Input Variable

I take an input x, based on which I do an experiment that gives me several data points. I compute the standard deviation of these data points. Then, I change ...
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0answers
17 views

Multiple comparison in the unequal variance case

I have found procedures such as Tamhanes T2, Dunnets T3 and the Games & Howell procedure that deal with unequal variances in the one-way model. However, I have a Randomized complete block design, ...
1
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1answer
43 views

Analysing overdispersed data with generalised linear models

Let's say I have an explanatory variable and a response variable that represents counts. I want to see if the explanatory variable can predicts counts. I'm aware the response variable is ...
4
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1answer
75 views

Alternatives to one-way ANOVA for heteroskedastic data

I have data from 3 groups of algae biomass ($A$, $B$, $C$) which contain unequal sample sizes ($n_A=15$, $n_B=13$, $n_C=12$) and I would like compare if these groups are from the same population. ...
4
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0answers
40 views

Visualizing many left-skewed distributions

I have a series of left-skewed/heavy tailed distributions that I would like to show. There are 42 distributions across three factors (labeled as A, ...
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1answer
25 views

How to compare distributions of two groups where each group has multiple observations from a small group?

I have data on continuous measurements (length of time of a behaviour) from two groups of individuals which differ in their phenotype (phenotype A or B, the variable used to group them). Each group is ...
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0answers
52 views

Using Weighted Least Squares with Robust Standard Errors

Weighted least squares (WLS) and robust standard errors are sometimes presented as alternative approaches for obtaining reliable standard errors of estimates of regression coefficients in the presence ...
2
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0answers
22 views

Multiple ANOVAs, shall I correct the homogeneity of variance test?

I want to run nine different ANOVAs on different variables that may change among groups. The ANOVAs are preceded by the Levene test of variance homogeneity. Of course, I want to correct for multiple ...
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0answers
30 views

Unequal variance, one replication, empty cells RCBD ANOVA

I could use some advice on how to handle this situation. I have a Randomized Complete Block Design (RCBD) ANOVA with 5 blocks and 8 treatments, the response is dry weight of some plant, there is 1 ...
5
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1answer
249 views

Is it ever okay to ignore heteroskedastic residuals and continue with analysis?

My data is misbehaving and I can't seem to get residuals with constant variance despite doing more transformations than Optimus Prime. Is it ever okay to just continue with analysis in and just make a ...
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1answer
36 views

Visually random model residuals, yet heteroskedastic? ( very small Breusch-Pagan Test P-Value)

Can anyone explain why the BP, Breusch-Pagan, test rejects homoscedasticity with such an apparently randomized plot of residuals?
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0answers
40 views

Post hoc tests from Anova() from car-package

I have a small sample unbalanced RCBD, where I have reason to suspect unequal variances, hence I wish to fit a ANOVA with type-3 SS with heterscedasticity consistent esimators. The simplest way to do ...
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0answers
19 views

Logistic regression when a covariate is measured with known but heterogenous measurement error

Let $y$ be a binary variable and $x$ be a covariate measured with known heterogeneous measurement error: $x_{i}$ ~ $\operatorname{Normal}(x^{*}_{i},\sigma_{i}^{2})$. Now suppose the relationship ...
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1answer
42 views

Bayesian estimation of multivariate Gaussian from noisy observations with known error variances

I have a dataset $\mathbf{D} = \{ (\tau_i, \Gamma_i) : 1 \le i \le n \}$ of observations $\tau_i = X_i + \epsilon_i$ from a $p$-dimensional Gaussian $X_i \sim \mathcal{N}(\mu, \Sigma)$ contaminated by ...
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0answers
48 views

ldentifying observations on the edges in heteroscedastic data

Consider bivariate data consisting of correlated variables (r ~ 0.9). It is known how both the variables are calculated. Each observation is identically distributed but non independent. Also, the ...
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3answers
46 views

Formal test for heteroscedasticity

Are there any formal tests for heteroscedasticity for non-normal data? I want to run the test on time series logged returns, so would it be okay to assume a linear relationship? To me it makes ...
2
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0answers
50 views

How to correct for non-linearity of response in linear regression

I want to train a linear regression model to predict a non-linear variable. This how the two independent variables correlated against the response (points are jittered): And the residuals against ...
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2answers
35 views

Can you have constant mean across samples with different distributions?

This might be a stupid question - but can data samples have constant means even if they are from different distributions?
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1answer
21 views

How should I split this data when testing for heteroskedasticity

I have a set of time series data and am looking to split into different time periods to test for heteroskedascity or not over different time frames. Intially, I planned to do it this way: Take the ...
2
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2answers
124 views

Standard error of regression coefficients without an assumption of homoscedastic normal noise

I have a time series that is affected by two (or more) kinds of events. When event $A$ happens, some signal is linearly added to the time series (the signal lasts, for example, for 100 time points). ...
0
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0answers
12 views

Random walk with stochastic volatility

I've done some analysis on a financial random walk, and even post-transformations am finding heteroskedascity across longer time periods. I want to investigate whether this is due to stochastic vol ...
0
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0answers
24 views

Testing homogeneity of variances among samples across replicates

I would like to receive any advice on the following question: If one wants to test that variances are homogeneous among a certain number of population samples a possibility is to use the Levene’s ...
3
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0answers
28 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 $V_0=$ ...
3
votes
2answers
232 views

Calculating statistical significance with unequal sample sizes and unequal variances

I have two samples, one with $n_1 = 41,000$ and the other with $n_2 = 881$; the larger sample has a standard deviation of $13.74$, and the smaller has an $SD=10.75$. The means are different, and when ...
1
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0answers
23 views

Weighted normal errors regression with censoring

I have some data which I would model via standard multiple regression except: There is censoring (left-censored, fixed but varying censoring points which are known) The errors are assumed ...
3
votes
1answer
91 views

Why do we say that the variance of the error terms is constant?

I always think about the error term in a linear regression model as a random variable, with some distribution and a variance. So if the error terms come from this random variable, why do we say that ...
0
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0answers
61 views

Non-parametric correlation for continuous and dichotomous variables

I have two variables I want to test with correlation, one is continuous and the other dichotomous. My data are non-normally distributed, plus the variance is heterogeneous, so I have to apply a ...
0
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1answer
47 views

Variance structure with multiple covariates in GLS

I am building a GLS model following protocol in "Zuur, 2009. Mixed effects models..." on p.90. I have 5 continuous predictors. VarConstPower variance structure works best for me. At first the fixed ...
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0answers
22 views

Error when using corAR1 and varExp in mutilevel model

I'm using nlme in R to fit a multilevel model for some physiological (skin conductance level) responses while watching a film. I'm specifying the model as: model <- lme(SCL <- variableA * ...
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0answers
40 views

Sandwich covariance for robust regression using M estimators for data exhibiting heteroskedasticity

Following the answer and comments on Python Statsmodels Testing Coefficients from Robust Linear Model based on M-Estimators: I'm wondering how the sandwich form of an m estimator's covariance matrix ...
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0answers
44 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 ...
2
votes
1answer
218 views

Games-Howell Post Hoc Test in R

I am doing some data analysis for my masters and I had some data that is normally distributed but does not fit the assumption of homogeneity of variance and has unequal sample sizes. I have been doing ...
2
votes
1answer
62 views

Heteroskedasticly Consistent Estimators for Var-Cov Matrix, Large Sample OLS Regression

I have a cross-sectional data sample of nearly 40,000 observations and tests for heteroskedasticity fail to reject the assumption of homoskedasticity. However, it seems common practice to report ...
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0answers
28 views

Graph interpretation hetroskedasticity [duplicate]

I ran a command of rvf plot . Does this graph show no heteroskedasticity?
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0answers
87 views

Non-converging heteroscedastic linear mixed-effects model (R lme)

I'm working on a project where I try to determine the influence of consulting expenditures companies made the year before on several economic figures. My dataset consists of roughly 2'000 different ...
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0answers
19 views

What is the difference between the studentized and non-studentized Breusch-Pagan test?

I have a multiple regression model with 4 independent variable. I want to test heteroscedasticity with the Breusch-Pagan test. If I do a studentized BP test the p-value is 0,173, with a ...
4
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1answer
237 views

How do I interpret this fitted vs residuals plot

I don't really understand heteroscedasticity. I would like to know whether my model is appropriate or not according to this plot.
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34 views

RESET Test and Heteroscedasticity Test for Hierarchical Multilevel Model

Are there implemented tests in R to check heteroscedasticity and linearity for multilevel regressions? I am using a two Level Regression Framework (lmer function in R). Is it necessary to do those ...