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

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25 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
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0answers
21 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 ...
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0answers
21 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 ...
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0answers
9 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 ...
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1answer
18 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?
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0answers
35 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
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1answer
22 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 ...
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0answers
6 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 ...
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11 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
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1answer
62 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 (...
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0answers
14 views

How to develop a best allometric model for future biomass estmation depending on diameter? [closed]

I have three separate sets of data containing diameter at breast height, height of the tree and biomass of the tree for the tree age of 5, 10 and 15 yrs. Now, I want to develop age specific allometric ...
2
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0answers
24 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 ...
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0answers
5 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 ...
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1answer
24 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
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1answer
59 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 ...
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1answer
25 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 ...
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0answers
22 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 ...
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1answer
25 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
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1answer
33 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
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1answer
69 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 ...
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0answers
15 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 ...
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0answers
26 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
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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?
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1answer
24 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. ...
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0answers
37 views

Fitting heteroscedastic models using gls function

Consider the following heteroscedastic model: $$y_i = f(x_i, \beta) + g(x_i, \theta)\varepsilon_i, i = 1, \ldots, n, \tag{1}$$ where $f(\cdot, \beta)$ is the regression function and $g(\cdot, \theta)$ ...
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14 views

Which criteria should I use to remove high variable data

In a biological experiment, I have, for every instance (a gene), three replicates, in a given condition. Ideally, the three measurements should be very closed from each other. I would like to discard ...
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0answers
24 views

How to prove the Heteroskedasticiy of a $ u_i $ in a linear regression model

I have to solve the following problem: I've been given that $E[y_i|x_i] $ is non-linear in $ x_i = (1, x_i1, . . . , x_ik) $ (I have not been told "how" is non linear) and $ Var[y_i|x_i] = σ^2 $. I've ...
2
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1answer
35 views

What type of Generalized Linear Model can handle high-to-low-variance heteroscedasticity?

I am trying to model the relationship between a continuous response variable (sample-corrected species-diversity estimates) and a continuous predictor variable (geographic spread). I have ...
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0answers
21 views

How can I make these time-series data stationary?

I'm working on eventually getting to a Granger-causality (or VAR) test on my independent variable(s), but first I need to sort out my dependent variable, which is Bitcoin's USD exchange rate ...
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0answers
6 views

What is the significance level for leveneTest in R? [duplicate]

I want to perform a Levene Test in R to check if the variances of two samples are equal. I have the following data; test1 and test2 are my samples. ...
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0answers
8 views

Help accounting for heteroskedasticity in a Revenue~GHG model with out Log transforming

Context I work for a sustainability charity and I've been developing regression model to estimate the Greenhouse Gas Emissions of public companies based on reported data (both financial and ...
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0answers
29 views

Which test for autocorrelation in a time series

I need your help to test autocorrelation between residuals of a time series. But I don't know which test use: Breusch Godfrey test, ARCH test or Durbin–Watson test.. I don't understand the difference ...
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0answers
19 views

heteroscedasticity in a log-linear model using glm in R

I have a log-linear model, built using glm in R. I performed bptest on the model, using bptest function from lmtest package. It revealed high heteroscedasticity in the model. My model is based on ...
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0answers
31 views

Strange residuals pattern

I fit a linear model that obviously needs some work. Here is an example of my data: ...
4
votes
2answers
151 views

What to do with non-normality and heterogeneous variances in two-way ANOVA when transformations do not work?

I'm conducting a Two-Way ANOVA with my two factors being Sex and Cohort. I have data from two cohorts of subjects, with each cohort consisting of males and females that were measured on one response ...
4
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4answers
192 views

Time series analysis: since volatility depends on time, why are returns stationary?

I run Dickey Fuller test in order to know if stock returns are stationary. I get that no matter which stock I take, his return is stationary. I don't know why I get this result since it is clear that ...
1
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1answer
41 views

Interpreting the residuals vs. fitted values plot for logit GLMM?

What I have is a generalized linear mixed model of the log OR of a rater (random effect) giving a response above a certain level on an ordinal scale, given a specification of what the rater was ...
3
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0answers
30 views

Difference between pairwise t test and multivariate linear regression results

I got different results when comparing means of different groups using a pairwise t test and multivariate linear regression. ...
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0answers
29 views

Breusch Pagan test vs graph

I have data where there is one dependent variable (X) and one dependent variable (Y). When I fit a linear model to this and look at residuals vs X, I see that there is heteroscedasticity. Whereas, ...
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0answers
25 views

An improvised method to model heteroscedasticity in a mixed regression model

Here is a description of my experimental design: Randomized complete block design with 4 blocks/replications and a split-plot factorial design. I have the following treatments: 2 ...
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0answers
14 views

Modeling farm socio/demographics to determine influence on net income

I am attempting to isolate the effect on net income of incorporating a certain type of marketing strategy for farms. My initial OLS model produced positive and expected results, but when I graphed my ...
4
votes
1answer
292 views

What is the difference between these two Breusch-Pagan Tests?

Using R on some data and trying to see whether or not my data is heteroscedastic, I've found two implementations of the Breusch-Pagan test, bptest (package lmtest) and ncvTest (package car). However, ...
0
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0answers
20 views

3 groups to compare, non-normal, unequal variance. What to do

I'm comparing three groups by Julian Date. Group 1 (n=173), Group 2 (n=47), Group 3 (n=126). All three distributions are non-normal and the variance is not equal. I've tried transforming the data six ...
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0answers
64 views

Modeling of residual heteroscedasticity in generalized linear mixed models

I built a linear mixed-effects model assuming a Gaussian distribution for the response variable. My model has the following structure in R: ...
3
votes
2answers
56 views

Influence of HAC estimates to p-value of t-test

I have a linear regression model and because of heteroskedasticity or autocorrrelation I use HAC (Newey-West) estimates. This influences also p-values of significance t-tests of estimated coefficients ...
1
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0answers
22 views

Spline regression with variable variance of residuals

I am running a natural spline regression x vs y, like in figure (there are also some dummy variables but it doesn't matter here). It happens that I have a lot of heteroskedasticity, i.e. mutable ...
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0answers
19 views

Weighting to handle heteroscedasticity in regression

Suppose I have a model where expected error in the response is a function of the response $Y = \beta X + \epsilon Y$ is it correct to fit a model by least squares simply weighting each data point by ...
0
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1answer
88 views

Unbiased Estimators and Heteroskedasticity

Consider a consumption model with bivariate data points $(Y_i,X_i)$, $i=1,...,n$, with $Y_i$ consumption and $X_i$ income. The univariate model is $$Y_i=\beta X_i+u_i,$$ where $E(u_i|X_i)=0, ...
0
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0answers
37 views

heteroscedastic time series in SAS autoreg - white noise matter?

I normally work with categorical outcomes, so a lot of this is new to me. Attempting to model monthly interrupted time-series in proc autoreg. There were 11 intervention changes of varying potency ...
0
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1answer
70 views

Heteroscedasticity in linear regression, there is a a pattern. What to do?

I'm modelling the behaviour of two variables with a linear regression. Since I saw (and believe) there is a multiplicative behaviour I transformed the dependent and independent variables taking the ...