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

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5
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1answer
29 views

Robust option in Stata: why are the p values computed using a Student distribution?

The commonly used "robust" option in the regress command of Stata gives standard errors using the Huber-White sandwich estimators. The t statistic also uses these standard errors. However I have ...
3
votes
1answer
33 views

Bartlett's test vs Levene's test

I am currently trying to address violations to ANOVA assumptions. I have used Shapiro-Wilk to test normality, and have dabbled with both Levene's test and Bartlett's test of variance equality. I have ...
3
votes
0answers
34 views

How to compare three groups to one control group without assuming equal variances?

I need to determine if one dependent variable (tensile strength) for each of three new groups is equivalent to that from my original ("control") group. I am not concerned with how the three new groups ...
3
votes
1answer
28 views

Is an F-test for equality of variance appropriate for a very large dataset?

I have a dataset with about 500,000 subjects and I am trying to establish whether the variance is equal. I first performed an F-test but then I realised the data is slightly skewed with kurtosis. So ...
0
votes
0answers
28 views

Mixed-effects models: autocorrelation for data with gaps in R

I wonder if there is a way of modelling of an autocorrelation for data with gaps in mixed-effects models in R? In addition, I would like to model heteroschedasticity. Thanks!
0
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0answers
33 views

How to apply heteroskedasticity and autocorrelation tests to panel data in eviews 8?

I am trying to test for heteroskedasticity and/or autocorrelation in my fixed effects panel regression in Eviews 8. There do not appear to be the necessary tests available. The Breusch-Pagan LM test ...
2
votes
2answers
80 views

Are the model residuals well-behaved (homoscedasticity)?

Can I say looking at this residuals-vs-fitted plots, that my residuals are homoscedastic?
5
votes
1answer
55 views

How bad can heteroscedasticity be before causing problems?

I have two questions about heteroscedasticity in multiple regressions. According to my trusty textbook (Using Multivariate Statistics 2007, p.127), it says that deviations from ...
7
votes
1answer
189 views

Fitting a heteroscedastic generalized linear model for binomial responses

I have data from the following experimental design: my observations are counts of the numbers of successes (K) out of corresponding number of trials (...
11
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2answers
67 views

Estimate The Rate At Which Standard Deviation Scales With An Independent Variable

I have an experiment in which I am taking measurements of a normally distributed variable $Y$, $$Y \sim N(\mu,\sigma)$$ However, previous experiments have provided some evidence that the standard ...
3
votes
0answers
34 views

heteroskedasticity in logit/cox

I am using a logit and a cox proportional hazard model for my analysis, and the newest version of Stata. I have found that there are no tests to check for heteroskedasticity for logit/probit models, ...
1
vote
0answers
33 views

robust s.e. versus clustered s.e

I am using survey data and understand that many times it is appropriate to correct for heteroscedasticity due to (a) errors for groups of individuals being correlated and (b) specific sub-populations ...
1
vote
0answers
15 views

Non-parametric Levene's test by Nordstokke and Zumbo

The example they mention is using a one-way ANOVA. What if I have two factors (3x11) and a dependent variable, can I do a two-way ANOVA to calculate the univariate levene's test? If so, how would I ...
7
votes
2answers
156 views

How to get ANOVA table with robust standard errors?

I am running a pooled OLS regression using the plm package in R. Though, my question is more about basic statistics, so I try posting it here first ;) Since my regression results yield ...
1
vote
1answer
29 views

Do unequal sample sizes matter for 1-factor analysis of variance if the sample variances are similar?

Suppose I have five samples with unequal sample sizes (50, 9, 10, 30, 15). If the variances of the samples are similar (e.g. p>0.05 from Levene's test), is it OK to use 1-factor analysis of variance ...
4
votes
4answers
200 views

Both t-test and F-test are significant, do I report both?

I undertook a large study (N about 200 in both control and treatment) in which one of the user ratings is significantly different (p < 0.0001). When I ran the unpaired t-test, the F-test also ...
0
votes
1answer
20 views

Is testing for endogeneity necessary?

I was wondering if testing for endogeneity is necessary when doing an OLS multiple regression. Similarly, is testing for autocorrelation necessary if there is no time series data? Is testing for ...
0
votes
0answers
18 views

How to add a fixed variance structure do a GAM

I am using GAM to fit a smooth line to represent the recovery of timber stocks following forest harvest. The data is heterogenous and I do not want to transform it. I understand that a nice way to ...
1
vote
0answers
51 views

Panel data with N < T heteroscedasticity and autocorrelation. Should I include country dummies?

I have panel data of $N=18$ countries with $T=72$ months. Heteroskedasticity and autocorrelation are present in the dataset. I was working in Stata with xtreg fixed ...
0
votes
0answers
14 views

Method to analyze data which has no repetitional measurement

I am trying to find a good method to analyze my data, and I am really lost. My data is only from one riverstretch, no repetitional measurement. I look at three stretches of the river, near ...
0
votes
0answers
52 views

How to use the Glejser test?

Glejser tests for heteroskedasticity of a single independent variable within a multiple regression model. And, it tests it by conduction a basic regression: ABS(Residual) = intercept + slope(X). In ...
3
votes
1answer
37 views

What are the three forms of the Park test for heteroskedasticity?

I understand the Park test for heteroskedasticity has three different forms. The best known one is in a log form: LN(Residual^2) = intercept + slope (LN(X)). The second one is in a linear form: ...
0
votes
0answers
20 views

Pairwise Wilcoxon test gives wrong results

I'm trying to perform a pairwise Wilcoxon test in R. When using Bonferroni p-adjustment I got only 1's and 0's. When changing p-adj to 'none', I get this: ...
1
vote
1answer
56 views

Heteroscedasticity and simple linear regression

I have 2 continuous variables and I want to conduct a simple linear regression, 1 DV and 1 IV. There is a moderate correlation between them. However, I suspect there may be some heteroscedasticity and ...
3
votes
1answer
40 views

Scientifically reasonable or not ? exclusion of very, very uncertain values from statistical analysis

I have 5 treatments A1 .. A5 and 4 independent individuals per treatment, whose parameter X is of interest to me. My objective is to compare X among treatments, and see if one or more treatment ...
0
votes
1answer
81 views

binary logit regression - which test apply for detecting heteroskedasticity?

After reading a lot of different papers and a lot of different posts on the internet I still don't have a clue how to test on heteroskedasticity with my logistic regression (binary). The White test ...
2
votes
1answer
37 views

Do I have to standardize my data to calculate variance?

I have 2 groups/samples. Correct me if I'm wrong, but before doing an independent-group t-test we have to verify the homogeneity of variance with Hartley's F-max test. When doing this test, we have ...
1
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0answers
31 views

Why is it possible that the White test and the special case of the White test can give different values of $R^2$

In the textbook I am using (Introductory Econometrics: A Modern Approach by Jeffrey M. Wooldridge, 5e), it is implied that the $R^2$ from the regression of residual-squared on all independent ...
7
votes
1answer
75 views

How can heteroskedasticity that is only contingent on omitted variables not effect the validity of standard errors?

In the textbook I am using (Introductory Econometrics: A Modern Approach by Jeffrey M. Wooldridge), there is a description that goes, By explicitly stating the homoskedasticity assumption as ...
7
votes
2answers
232 views

How can you test homogeneity of variance of two groups with different sample sizes?

I have two groups of data that have different sample sizes and in order to be able to analyze both sets they must have the same variance. I was told I should use Bartlett's to test the homogeneity of ...
1
vote
1answer
83 views

Groupwise heteroskedasticity

I know how to derive the GLS estimator of beta (theoretical GLS), but there a slight change to the question and i am not quite sure how to go about it. A researcher has reason to believe that the ...
3
votes
0answers
45 views

Simple Linear Regression - Prediction Interval and Non-constant variance

I have two questions about a simple linear regression model. I want to use test1 scores to predict test2 scores. I am using R software. x=test1, y=test2, Let's say that both tests are scored from 1 ...
1
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0answers
45 views

Stationarity ⇒ homoscedasticity? [duplicate]

If my data is stationary, can I also write that it is homoscedastic? Does stationarity imply homoscedasticity of the data?
2
votes
2answers
281 views

Dealing with Heteroscedasticity in ANOVA

I need to perform an ANOVA on percentages data. I have 3 factors: TREATMENT, SAMPLE and DaysAfterTreatment (DAT). Treatment has 3 levels: Control, A, B. SAMPLE has 2 levels: SampleA, SampleB. DAT has ...
8
votes
2answers
160 views

How do residuals relate to the underlying disturbances?

In the least squares method we want to estimate the unknown parameters in the model: $$Y_j = \alpha + \beta x_j + \varepsilon_j \enspace (j=1...n)$$ Once we have done that (for some observed ...
0
votes
1answer
33 views

Is non-stationary the same as heteroscedastic?

Are the terms non stationary and heteroscedastic one and the same? As in they both imply a variable whose mean and variance changes with time?
1
vote
1answer
18 views

detecting change in variance with age

I have some data on some measure of performance for a group of participants of different ages (11-30 years). The scatterplot suggests that the variance changes over that time, with a wide range of ...
0
votes
0answers
117 views

Residual Diagnostics and Homogeneity of variances in linear mixed model

Before asking this question, I did search our site and found a lot of similar questions, (like here, here, and here). But I feel those related questions were not well responded or discussed, thus ...
1
vote
1answer
34 views

Consistency of heteroskedasticity-robust standard errors

Is the following statement true or not? When applying OLS with model $y=a+bx+u$, the heteroskedasticity-robust standard errors are consistent because $\hat u_i^2$ (the squared OLS residual) is a ...
1
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0answers
56 views

How to test heteroskedasticity at the independent variable level?

I know how to test the heteroskedasticity of a model's residuals. I am inquiring about how to test for heteroskedasticity for each specific independent variables included in the model. What is the ...
0
votes
0answers
21 views

Transformations in Simple Linear Regression [duplicate]

Suppose a linear model for Y in a single predictor var, X. If the residuals show a pattern of increasing variance (wrt X), sometimes a transformation of Y, Y'=f(Y) is considered (where f is sq rt, ...
0
votes
0answers
27 views

Troubles reporting transformed variables for log and sqrt into a general equation

Good morning everybody, I see CrossValidated has really high level of questions and answer; I am just a student so I hope this question is not too basic... Suggestion of further readings available ...
0
votes
1answer
99 views

ANOVA - when homogeneity of variance is violated

My data was a repeated measurement (3-4 measuring times) with one fixed factor (4 doses) and nested (Please find an example below). I would like to ran ANOVA but the assumption of homogeneity of ...
2
votes
0answers
126 views

Accounting for heteroskedasticity in lme linear mixed model?

I have a data set where I measured the number of molecules (M) present in cells as a function of drug (with or without) and days of treatment (5 timepoints). I repeated the experiment 3 times, with ...
4
votes
2answers
213 views

How to perform residual analysis for binary/dichotomous independent predictors in linear regression?

I am performing the multiple linear regression below in R to predict returns on fund managed. reg <- lm(formula=RET~GRI+SAT+MBA+AGE+TEN, data=rawdata) Here ...
3
votes
2answers
351 views

Heteroscedasticity in Regression

I have seen a tutorial video where a person is advising to check for heteroscedasticity in a regression by plotting the IV against the DV. Is this a problem? Are there any drawbacks with this ...
2
votes
1answer
109 views

How to deal with heteroscedasticty: choosing between White, WLS or Log linear model?

I am dealing with heteroscedasticity, and as we learned several methods to deal with the issue, I would like your help in choosing which one. The problem comes out of the econometrics book of ...
1
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3answers
83 views

ANOVA with outlier group

This is my first question (previously the search function has been enough), so please bear with me. I have a very simple experimental design with one outcome variable and 5 groups. My typical ...
10
votes
2answers
405 views

Explanation for non-integer degrees of freedom in t test with unequal variances

The SPSS t-Test procedure reports 2 analyses when comparing 2 independent means, one analysis with equal variances assumed and one with equal variances not assumed. The degrees of freedom (df) when ...
2
votes
1answer
56 views

Exponential regression residual check

If you have an exponential regression of the form log(y) = b0 + b1x with predicted equation ŷ = 10^(b0 + b1x) and you need to ...