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

learn more… | top users | synonyms (3)

0
votes
1answer
14 views

Heteroscedascity and sample size

Can a small sample be cause of heteroscedascity? My guess is that it doesn't depends only on sample size, but also on sample bias or measurement error.
1
vote
0answers
52 views

MLE of heteroscedastic model

I'm doing some practice questions for an upcoming exam and am unsure whether I've understood the problem correctly. Can anyone confirm what I've done or point out where I've gone wrong? My final ...
2
votes
1answer
26 views

Should I use vce (robust) in a single year regression model?

Should I use vce (robust) in a single year regression model? The regression is for diversity measurement among 66 organizations in one year only
1
vote
0answers
26 views

Testing for Stochastic Dominance - Mann Whitney with Unequal Variance

I've been looking for methods like Mann Whitney, but without homogeneity of variance. So far, I found that I suppose to test for stochastic dominance instead - i.e. modifying the null hypothesis. ...
0
votes
1answer
18 views

coding a JAGS error model for a dependent variable that has increasing variance as a function of the magnitude of the dependent variable

I am running a model in JAGS. I have a situation where y is a linear function of x, but the error in ...
0
votes
0answers
23 views

Heteroscedastic raw residuals but homoscedastic studentized residuals

I know some examples of weighted regression models whose raw residuals are heteroscedastic but the studentized residuals are homoscedastic. Does anyone know an unweighted regression model whose raw ...
0
votes
0answers
7 views

Heteroskedastic errors may still explain more deviance?

Among a population, N = 1,100, you employ 10-iteration, 10-fold cross-validation on 1,000 observations using OLS model #1: $Y_i = \beta X + \epsilon$ This has an Adjusted $R^2$ of Q1 with a standard ...
1
vote
0answers
19 views

Contrast between BP-test and White test. is there heteroschedasticity?

I'm doing an econometric analysis to try to explain the gender wage gap. Here's my regression: Bp-test, White test outputs and residuals VS fitted values plot (rvfplot command in stata) So for ...
1
vote
0answers
75 views

If I do a robust regression using standard error, what do I need to analyse in the residuals

Let's say I do a multiple regression, using robust (Stata option). It is a robust standard error regression. I want to analyse and discuss residuals. Residuals versus fitted values Is it ...
1
vote
0answers
37 views

Heteroscedasticity in generalised linear regression

I have a heavily positively skewed continuous outcome variable y. Therefore I log transformed it to achieve normality. My interest is to assess the association between a few explanatory variables (...
0
votes
0answers
16 views

Multiple regression with (partially) non-independent predictors?

Question 1: Let’s say I want to predict SAT scores, and I have a hypothesis that IQ is a better predictor of SAT scores than weight is. What is the method that would allow me to reject the null ...
1
vote
1answer
32 views

Heteroskedasticity Question

I have a model that's affected by Heteroskedasticity: bptest(m1) studentized Breusch-Pagan test data: m1 BP = 65.055, ...
0
votes
0answers
25 views

Nested ANOVA alternative for heteroscedastic data (Nested Welch ANOVA)

Question: Is there an equivalent of Nested -ANOVA for data which fails ANOVA requirement? Is it possible to perform in R? Many thanks, Savani I am doing an analysis of large data set. I have ...
0
votes
0answers
11 views

when variances are unequal between groups. (Welch ANOVA in r)

I want to know why the results are different between oneway.test() and gls() I assume the variance are different across ...
0
votes
0answers
25 views

Pattern in scale-location plot, despite transforming y variable

The regression model being built uses about 2200 odd observations and about 20 input variables (majority of which are categorical with a couple of continuous and ordinal variables). I fail the ...
0
votes
0answers
17 views

Heteroskedasticity consistent SEs with Proc ROBUSTREG in SAS

We are using the Proc ROBUSTREG command in SAS to down-weight the influence of the outliers (mainly in the Y-direction). Furthermore, we wish to use heteroskedasticity consistent SEs and standardized ...
0
votes
1answer
41 views

Independence and homoskedasticity

Does $E(u|x)=0$ imply homoscedasticity? If yes, why? Also, does $E(u|x)=0$ mean that $u$ and $x$ are fully independent? If answers to both these question are no: Does full independence of $u$ and $...
0
votes
0answers
18 views

Correct equation for Breslow-Day statistic in homogeneity test of odds ratio

In Statistical Methods of Cancer Research; Volume 1 - The analysis of case-control studies the authors Breslow and Day derive a statistic to test for the homogeneity of combining strata into an odds ...
0
votes
1answer
44 views

Does my residuals vs fitted values plot show constant variance for my regression?

I'm having trouble interpreting my R output. I know when checking for variance no patterns should occur but I have only covered the textbook scenario where it is very easy to interpret. However with ...
0
votes
1answer
44 views

Heteroscedasticity in Fixed Effects model

I've found heteroscedasticity in my panel data. However, Gujarati (2009) says in a footnote to the chapter "The fixed-effect within group estimator" that Stata provides heteroscedasticity-corrected ...
0
votes
0answers
78 views

what is the difference between xtgls and fixed effects with clustered standard errors?

I wonder what the difference is between a feasible generalized least squares model and a fixed effects model with clustered robust standard errors. In STATA terms, I want to know when I should use one ...
1
vote
0answers
27 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 ...
0
votes
0answers
19 views

In testing Heteroscedasticity, when should I use Park Test or Glejser Test?

I am currently running a data analysis on survey data. In testing the heteroscedasticity assumption in Multiple Linear Regression, using Park Test, the research actually passed the test. However, when ...
0
votes
0answers
16 views

null hypothesis for Breush Pagan test

I´m doing a simulation study about some test for homocedastic variance. I have Levene, Bartlett, Fligner and Goldfeld test. The null hypothesis is: $H_{o} = \sigma_{1}^{2} = \ldots = \sigma_{k}^{2}$ ...
0
votes
0answers
22 views

How do I test the parametric assumptions of a split-plot ANOVA?

I have an RCBD split-plot experimental design for testing the effects of drought, tillage, and nutrients on plant biomass: Block = random factor (2 blocks of 10 plots each, total 20 plots) Drought = ...
3
votes
0answers
23 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 ...
0
votes
0answers
33 views

Heteroskedasticity test for panel data

I failed to use traditional heteroskedasticity tests in an unbalanced panel data, and I am not very clear on how to proceed in a different satisfactory manner. When trying to plot the residuals ...
0
votes
0answers
51 views

Heteroscedasticity and bias shown in residual plots, lme

I have been fitting a linear mixed-effect model. The residual plots are not desirable. I have found many posts telling me the first is heteroscedastic, and the second is biased. But I can't find info ...
1
vote
0answers
24 views

Two versions of the Breusch-Pagan test?

I have learned (and it is the case for instance in Woolridge's Introductory Econometrics) that for testing heteroskedasticity with the BP test, the sample statistic is $nR^2_{\hat{u}^2}$, that follows ...
1
vote
0answers
54 views

Breusch–Godfrey test under heteroskedasticity

Do I need to account for heteroskedasticity when performing the (vector) AR1-2 test? The Autocorrelation (AR) 1-2 test is defined as follows - often reffered to as the Breusch–Godfrey test (Wiki link)...
0
votes
0answers
11 views

Classification of overlapping hetegenerous cell nuclei

We are two people doing a image analysis project on segmentation of cell nuclei. Our data set consist of about 300-400 cell nuclei, from 10-15 images containing different cell types. Our main problem ...
1
vote
1answer
37 views

Heteroscedasticity,Autocorrelation,Chow test

Can a Chow test be run on a dataset which has autocorrelation and/or heteroscedasticity? Will the F-stat give accurate results?
1
vote
0answers
39 views

How to change your data to be homoscedastic?

I want to use a linear discriminant analysis and need homoscedasticity. I'm wondering how to get this assumption correct with the data that I have. I have in total over 7000 samples, but I'm ...
1
vote
1answer
31 views

Data violates homogeneity of variances and is not normally distributed. Can I still run the t-test?

I have two categorical, independent groups, and a continuous dependent variable. The data violates homogeneity of variances, and the dependent variable is not normally distributed for each of the two ...
0
votes
0answers
7 views

Is it meaningful to look at predicted values vs residual plot to assess homogeneity of variance assumption for mixed ANOVA?

I have two-way mixed ANOVA. I remembered getting the a single value predicted values when I plotted predict vs residual plot for one-way repeated measures ANOVA. So is it meaningful to produce the ...
0
votes
0answers
20 views

How to fix a linear regression where the residuals are dependent on fitted values?( i.e heteroskedasticity)

I fitted a linear regression(LM) in R to a bunch of variables. I can see model is heteroskedastic. However, reading around various resources, I couldnt find a simple solution to fix this. Some of ...
3
votes
1answer
77 views

Mixed model or ANOVA on differences in pre-post design

I want to analyse the effect of different treatment types (control, treatment1, ..., treatment4) on the surface of specimens made of certain materials (...
2
votes
0answers
27 views

White test confirms heteroskedasticity while Breusch-Pagan test doesn't [duplicate]

I'm using SAS in order to create a model for a cars datasets. The response variable y, is the price of the car. By the way I'm using the PROC MODEL statement in order to check heteroskedasticity. This ...
0
votes
0answers
8 views

How to know if my data is homogeneous or not

This is for general understanding and I don't have a specific task or data I need to relate it to, but I'm trying to understand how do I know if my point data is homogeneous or inhomogeneous. Is that ...
1
vote
2answers
37 views

Unit root tests ambigous - is time series stationary?

I am testing a time series (quarterly) for stationarity. However, using the KPSS test, the ADF test and PP test, I get different results (ADF and PP reject non-stationarity, KPSS rejects stationarity, ...
1
vote
1answer
74 views

Does this residual plot indicate heteroscedasticity?

These are two versions of the same residual plot, just with a different scales, (I'm not sure which is easier to interpret so I included both). I don't need to know major details (for the assignment ...
1
vote
1answer
30 views

Compare several means with different sample sizes (greater than 2)

I have seven different groups with different sample sizes and variances and I want to compare the means of their data. I'm not very informed in statistics, so could anyone help me out here? I've only ...
0
votes
0answers
26 views

Autocorrelation test in case of heteroskedasticity and endogeneity

During my thesis I encountered the problem of having some degree of heteroscedasticity in my error terms. This creates a problem when I want to test for autocorrelation since for example the Breusch-...
0
votes
1answer
36 views

Proper definition of AR()-ARCH() time series model

This is how I would define it, if anyone has any objections please let me know! AR(m)-ARCH(m) time series is an ARCH(m) process in which the variance at time t is conditional on the previous m times ...
3
votes
1answer
56 views

Significant Result in Levene's Test

I am very confused right now. I ran Levene's test on my data and got a p-value of 0.000, meaning that variances are very heterogeneous. I transformed the data but no method can make them homogeneous. ...
3
votes
1answer
361 views

Reporting Shapiro-Wilk and Levene's test results

In light of questions such as this: Interpretation of Shapiro-Wilk test and others. I was wondering if it is better to state that "data were (formally) tested for violation of normality (p < x) and ...
0
votes
0answers
17 views

Normality and homogeneity test for small sample size

I would like to inquire if testing for normality and homogeneity is still necessary for my data from an experimental where trials were done only three times. Or can I directly perform ANOVA and post-...
0
votes
0answers
32 views

Heteroscedasticity and Linear relationship?

I am new to statistics and am doing my first analysis using SPSS. I am doing multiple regression and I am not too sure how badly this graph violates linearity and homoscedasticity. I am not keen on ...
2
votes
1answer
26 views

Heteroskedasticity that is not due to excluded moderating variables

Is heteroskedasticity always caused by excluded moderating variables in a regression model? Are there any phenomena where heteroskedasticity is independent from such exclusion?
1
vote
1answer
27 views

ANOVA and Kruskal-Wallis Test in One Study

I am currently analyzing the results of my study which deals with several dependent variables. I have tested the data for normality and homogeneity and all but one passed the assumptions for ANOVA. ...