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
votes
0answers
9 views
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 ...
1
vote
2answers
55 views
Hypothesis testing a location shift in heteroscedastic and non-normal data
How do I test for a "location shift" in something like the mean or median if the shape of the distribution has changed quite significantly between groups?
Often an experimental intervention seems to ...
2
votes
1answer
47 views
Crises: ANOVA? Or: how to analyse non-normal, non-Homogeneity data with different group sizes?
I'm somewhat new the world of statistics, or at least it has been years since I last used it and basically the only program I know generally how to work with is SPSS. However, for my Master thesis I ...
0
votes
0answers
47 views
Hettest Not Appropriate for Robust Cluster
I am using stata, and running a regression with robust standard errors.
I want to test the Heteroscedasticity after running the regression with robust standard errors, and to compare this to before ...
1
vote
2answers
30 views
Quantifying homogeneity
I am hydrologist and I am looking for a solution for the following problem:
Suppose that I have $k$ samples of observations (region) of the same variable (e.g., annual peak flow) at different ...
4
votes
3answers
121 views
Why it is natural to expect equality of variances?
When conducting various statistical test why do we expect equality of variances/ homoscedasticity/sphericity etc.?
0
votes
1answer
35 views
Do I need heteroscedasticity consistent Standard Errors in LMER when applying Heckman's two stage procedure?
When including an Inverse Mill's ratio to account for selection in a mixed model using LMER in R (following Heckman's [1979] two-stage procedure), do I still need to estimate robust SEs or does the ...
0
votes
0answers
33 views
Testing for structural break on included variables under heteroscedasticity
I am doing an analysis on how energy ratings affects the prices in the housing market.
My data series ranges from 2003 to 2013, and to account for fluctuations in the sales price over time, I use ...
5
votes
2answers
62 views
Homogeneity testing of baseline characteristics in medical trials
I have been reading medical journals and they repeatedly show baseline characteristics of samples from a randomised controlled trial, which they have then tested to ensure no differences between the ...
0
votes
0answers
80 views
What method is better to model percentage response with each subject measured two times and heteroscedastic error?
The response was calculated as $\frac{Control-Observation}{Control}*100\%$. Raw values of $Control$ and $Observation$ are not available, I have only calculated values. Each value was measured twice. ...
3
votes
1answer
48 views
Dealing with outliers when comparing variances with Bartlett's test
I have four different groups (with unequal sample sizes of 100 to 120) and want to test if the variance differs.
For ANOVAs I used the winsorized mean to get a more robust estimate and I am wondering ...
1
vote
1answer
60 views
Comparison of p values for Levene mean test and Levene median test?
I am doing Levene's mean test and Levene's median test (Brown-Forsythe).
I want to compare the p-values of these two tests to see which is better.
I get large p-values for both tests which are 0.562 ...
2
votes
2answers
134 views
Alternative to One-way ANOVA unequal variance
I would like to compare the means across three groups of equal sizes (equal sample size is small, 21). The means of each group are normally distributed, but their variances are unequal (tested via ...
0
votes
0answers
20 views
Getting a posterior belief from noisy observations
Say I have a dataset $X = \{x_i\} \supset \mathbb{R}^n$ for which I assume that $x_i = y_i + \sigma(y_i)$ for some unobserved variables $\{ y_i \}$. That is, I believe that my data is subject to ...
5
votes
1answer
204 views
Is bootstrapping standard errors and confidence intervals appropriate in regressions where homoscedasticity assumption is violated?
If in standard OLS regressions two assumptions are violated (normal distribution of errors, homoscedasticity), is bootstrapping standard errors and confidence intervals an appropriate alternative to ...
0
votes
1answer
91 views
how to test heteroskedasticity of a time series in R?
How can I test heteroskedasticity of a time series in R? I have heard of two tests McLeod.Li.test and bptest (Breusch-Pagan ...
1
vote
1answer
71 views
Bootstrapped confidence intervals for the parameters of a linear model applied to multiply imputed data
I would like to construct CIs for $\beta$ in the linear model
$Y = X\beta + \epsilon$
I observe $\{X', Y'\}$ which is $\{X,Y\}$ contaminated with values missing at random. $\epsilon$ is not Gaussian ...
0
votes
0answers
67 views
TIme series analysis: ARCH-LM statstics and length of a time series
I have four 30-year long time series of daily correlated weather variables. I estimated a VAR model to the series using vars R package. Then, I executed seriality and normality test on VAR residuals, ...
5
votes
1answer
71 views
Constant variance assumption in regression model
My question is how do we check the constant variance assumption in a regression model?
2
votes
1answer
110 views
Can I justify performing a two-way anova where data is normally distributed but has heterogeneous variances?
I'm an undergraduate psychology student currently finishing up my dissertation, but a few days ago, while going through my SPSS output, I realized my Levene's test is significant, but my data is ...
0
votes
1answer
61 views
Finding structural breaks in heteroskedastic time series
I'm currently writing my thesis and I'm a little stumped.
I'm trying to identify structural breaks in the movement of reserve currencies. I'm not yet all that versed in the finer details of time ...
0
votes
1answer
73 views
Estimate how coefficient of variation changes as a function of $x$ without replication
Suppose I have data points of the form (x,y) and I know that CV should be constant across all x values. (i.e. heteroskedastic data). That being said, how can I compute the estimated CV if I don't have ...
0
votes
0answers
60 views
What is the MLE if the variance is heteroskedastic
The normal distribution of MLE is start ${x_1,...,x_n}$ random sample from $\sim\mathcal{N}(\mu,\sigma^2)$
This family of distributions has two parameters: $\theta = (\mu, \sigma)$, so we maximize ...
2
votes
3answers
105 views
Linear model estimation in the presence of heteroscedasticity
Assuming a sample of random variables where the error terms for each random variable ($y_{i}$) are given by $\epsilon_{1}, \dots, \epsilon_{n} \sim N(0, \sigma^{2})$, a linear model is developed such ...
2
votes
2answers
159 views
Is it possible to calculate variable confidence intervals, conditional on $\hat{Y}$ to address heteroscedasticity?
Estimating confidence intervals for non-normally distributed residuals can be accomplished using bootstrapping procedures, sandwich estimators or quantile regression.
But is there a way to calculate ...
3
votes
1answer
117 views
QQ plot is consistent with normality when subgroups are non-normal
I have read that for a one way ANOVA, you should check that the model residuals are normally distributed. If the variance of each group is homogeneous then this implies that the residuals with each ...
3
votes
1answer
138 views
ANOVA:How to detect non-normality with a QQPlot in the presence of non-homogeneous variance
This is a pretty general question but, I often find statistical textbooks claiming that, in order to justify the within groups normality assumption of a one way ANOVA, you can look at a QQ plots of ...
0
votes
1answer
115 views
“Constant variance” violation
If we apply linear regression on a data which has a BINARY(0,1) dependant variable, the very important assumption of "constant variance" of the dependant variable across independant variables is ...
5
votes
2answers
848 views
What does having “constant variance” in a linear regression model mean?
What does having "constant variance" in the error term means. As I see it , we have a data with variable and 1 independent variable. This is one assumption of linear regression. I am wondering what ...
5
votes
1answer
224 views
Sandwich estimator intuition
Wikipedia and the R sandwich package vignette give good information about the assumptions supporting OLS coefficient standard errors and the mathematical background of the sandwich estimators. I'm ...
4
votes
0answers
71 views
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 ...
1
vote
0answers
48 views
High heteroscedasticity level
My dependent variable - logincome - and one independent variable - age - are continuous. All other explanatory variables are categorical including BA_degree, race, occupation, region, homeownership.
...
1
vote
2answers
168 views
Several intraclass correlations (ICC) when modeling heterogeneous variances?
In a nested design (e.g., students in schools, ants in colonies, individuals in a species, leaves in a tree), ICC is defined as the proportion of variance among observations from the same subject ...
5
votes
1answer
144 views
Conceptual distinction between heteroscedasticity and non-stationarity
I'm having trouble distinguishing between the concepts of scedasticity and stationarity. As I understand them, heteroscedasticity is differing variabilities in sub-populations and non-stationarity is ...
1
vote
1answer
413 views
What if results from a Breusch-Pagan test for heteroscedasticity contradicts those of a White's test?
Testing for heteroscedasticity I get these results:
Breusch-Pagan / Cook-Weisberg test for heteroskedasticity
Ho: Constant variance
Variables: fitted values of log_expdu
...
0
votes
0answers
109 views
How to run Pesaran Cointegration Bound test and removing heteroskedasticity fron short term model?
At first, excuse my english because i don't speak it very well. I am also new in this place. I hope i can ask this question here.
Thanks a lot for what you're doing! I have a question. Now i'm ...
2
votes
1answer
127 views
Chi-square test in finite mixture models
I was trying to figure out whether or not the distribution of a biomarker came from heterogeneous populations. Analyzing the data with normalmixEM in the ...
1
vote
0answers
303 views
Question about Hausman-test for endogeneity with two endogenous regressors with potential heteroscedasticity
First question: Is the following example of computing the Hausman-test for endogenity with two endogenous regressors adequate?
Second question: Is it true that in case of heteroscedasticity, i.e. ...
1
vote
0answers
69 views
Couple of linear regressions with heteroskedasticity and correlated errors
I have two linear models:
$$
y_1 = \mu_1 + \beta_1x + \epsilon_1
$$
$$
y_2 = \mu_2 + \beta_2x + \epsilon_2
$$
where $\epsilon_1, \epsilon_2 \sim \text{MVN}(0, \Sigma(x))$, where $\Sigma(x)$ in NOT ...
1
vote
2answers
316 views
Testing assumptions of multiple regression
When doing a multiple regression and testing for homoscedasticity
some people look at raw observations and others the residuals. Which
is correct?
Do you use raw data or residuals to test linearity?
...
2
votes
1answer
138 views
Should raw data or residuals be used to check homogeneity of variance?
Unexpectedly for me (!) I've recently learnt that:
"We have assumed that the error terms, $\epsilon_{ij}$, of the variates in each sample will be independent, that the variances of the error terms ...
2
votes
0answers
183 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 ...
4
votes
0answers
294 views
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 ...
1
vote
0answers
26 views
How do I calculate the difference between incidences?
I'm making a study on the necessity of routine omentectomy in ovarian cancer patients.
The plan is to first find the incidence of occult metastases of the omentum in ovarian cancer patients, and ...
1
vote
1answer
149 views
Variances not homogeneous problem in ANOVA mixed between-within subjects, too bad?
I'm conducting a 2x3 mixed between-within subjects ANOVA (group x time). I have 20 participants, 10 for each group, who undergo all the 3 measures over time.
Levene's test of equality of variances is ...
2
votes
0answers
438 views
Newey-West t-statistics
I have a time-series which is autocorrelated by construction, and might be heteroscedastic. I have calculated the sample mean of this time-series, and would like to calculate the t-statistic ...
0
votes
0answers
152 views
Homogeneity of variance in ANOVA mixed model?
I'm conducting a 2x3 mixed between-within subjects ANOVA (group x time). I have 20 participants, 10 for each group, who undergo all the 3 measures over time.
I have checked with SPSS: variance is ...
1
vote
0answers
60 views
Need to analyze: Unequal variances, Factorial Completer Randomized Design
I'm trying to analyze data that violates the assumptions of an ANOVA (homogeneity of variances), thus I think I have to conduct a non-parametric test. My study follows a factorial completely ...
4
votes
1answer
163 views
Is there a better way to create variables with a certain correlation and one of them is heteroskedastic?
My goal is to generate two variable which are correlated and one of them is heteroscedastic with regards to an grouping variable.
To create two variables with a desired correlation the common way to ...
1
vote
1answer
315 views
Alternative to 2-way ANOVA when variances are unequal
I'm working on a question on 2-way ANOVA where there are 2 treatments and 1 blocking factor. The residual plots suggest unequal variance. What is another parametric or non-parametric alternative ...
