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

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1answer
15 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
23 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
6 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
18 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
12 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
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1answer
176 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, ...
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0answers
11 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
39 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
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2answers
37 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
17 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
13 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
78 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, ...
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0answers
21 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
46 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 ...
0
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2answers
47 views

How to get rid of heterogeneity of variance?

I'm measuring the impact of three different types of videos on vocabulary learning (the dependent variable). Participants were divided into three different groups. Each group watched one type of video ...
3
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0answers
53 views

Can I use a Poisson model for data with a linear fit but Poisson distribution? [closed]

Say I have a multivariate model which I expect to have linear fit but with a relative (not absolute) error term: $ y = \beta X + \epsilon y$ and for which the distributions of the $X$s and $y$ are ...
2
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1answer
60 views

How to deal with non-normal variable distributions in R glmnet

I am regressing actual counts of traffic against predictions using ridge regression (cv.glmnet in R). The data (both predicted and actual) has a roughly ...
1
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1answer
42 views

Calculating prediction intervals from heteroscedastic data

What is the standard method for generating a 95% predicton interval (not confidence) for a linear regression given heteroscedastic data? Let me be more specific with an example: ...
1
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1answer
39 views

Proof MLE expected cell frequencies in chi-square test of homogeneity - the last step

The problem is from John A. Rice "Mathematical Statistics and Data Analysis" proof that in determining the estimate value for a given cell in a test of homogeneity the MLE is what our intuition would ...
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0answers
23 views

SAS Heteroscedasticity and Autocorrelation

I did a white test for heteroscedasticity problem and got the following: DF=27, Chi-Square=33.91, Pr>ChiSq=0.1688 Do I have heteroscedasticity? How do I know? Also Durbin Watson test showed to be: ...
0
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1answer
52 views
0
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0answers
20 views

Weighted least squares regression and heteroskedasticity tests in SAS (Breusch-Pagan)

I have a question on weighted least squares regression model in SAS, and the Breusch-Pagan heteroskedasticity test. Should the Breusch-Pagan test statistic be the same before and after applying ...
0
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0answers
12 views

TS, problem with heteroscedasitcity

I have a time series (156 obs.; q-quantity; APromoW-promotions; PPI-price per item above 35: dummy 0,1; priceup: Dummy 0,1) with multiple lags in model: ...
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0answers
42 views

RESET Test in R Influenced by Heteroskedasticity in the Data?

I'm running a negative binomial model in R on 558 observations of count data, along with "vcov" to add robust errors. I am using the Ramsey RESET Test as a criteria to judge my model. I have always ...
0
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0answers
10 views

heteroscedasticity of standardised residuals and heirachical multiple regression in SPSS?

Using SPSS, I have used hierarchical multiple regression to predict variance on my continuous DV from a continuous IV while controlling for other (continuous or dichotomous) variables. I have ...
2
votes
2answers
30 views

Can a Levene's test be conducted with only summary statistics?

My research question specifically deals with testing the variances of 3+ groups for significant differences. I'm not looking to test an assumption of homoscedasticity for an ANOVA or any other test, ...
3
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1answer
47 views

Performing test for homogeneity of variance without samples

I'd like to perform a test for homogeneity of variance in r, but I don't have samples available to test. I have the sample mean of each group, the sample deviation of each group, and the sample ...
0
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0answers
10 views

Fligner Killeen Test on Residuals

Is it a good Idea to perform Fligner Killeen test on residuals of a model, to check Heteroscedasticity?
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0answers
10 views

Multiple Regression approach and ANCOVA approach to check for homogeneity of regression slopes

Hi i have a mixed design set of data with one continuous variable of satisfaction with 2 levels (pre- & post-) and one categorical variable of Service with 3 levels (S1, S2, S3). When running ...
0
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1answer
28 views

CSTS dataset - robust standard errors lead to big drop in t-values

I am running a regression on a Cross section time series data set (cross sectional dominant) that has the following characteristics: 1,200 cross sections (6 countries * 200 products). Each country - ...
0
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0answers
59 views

ARIMA diagnostic testing in Stata

I am using an ARIMA(1,1,0) in Stata. I have already executed estat aroots and wntestq (white noise test) for the residuals. I ...
1
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1answer
65 views

What is an appropriate test for a normally distributed, heteroscedastic, multi-factor data set?

I have a data set of active layer depths from an Arctic field site. There are two factors in the data set, Month measured (July or August), and Location (shrub patch or open tundra). I had intended on ...
4
votes
1answer
47 views

Standardized residuals vs fitted values: OLS assumptions satisfied?

Based on only the above plot, what comments would you make about whether the OLS assumptions are satisfied? In particular homoskedasticity, normality. I just want to know if I'm right. It seems to ...
4
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0answers
36 views

Multicollinearity in WLS regression

I run a weighted-least squares regression to account for the heteroscedasticity in my data. When I examine the Pearson correlations between all predictor variables, I can't detect high collinearity. ...
0
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0answers
12 views

Substantive assumptions of precision weighting

In linear regression with heteroskedastic residuals, people sometimes weight by the precision of the residuals. Does doing this involve a substantive assumption about the data-generating process? ...
0
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1answer
35 views

Linear mixed model heterogeneity

I have a run a linear mixed effects model in R to model clinical data. However, this model is heteroscedastic (as there excess zeros in the response variable). I have tried transforming the data (log ...
0
votes
1answer
77 views

What is the difference between GARCH and MGARCH model

I am struggling with the different GARCH-type models. Is there a difference between a GARCH and a MGARCH model?
0
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0answers
24 views

Intraclass Correlation Coefficient for Ordinal Probit model with heterogenous variances

I have a hierarchical ordinal probit model (subjects within locations) with heterogeneous variances, modelled in JAGS, somewhat similar to: http://www.ncbi.nlm.nih.gov/pubmed/19520453. The model is a ...
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0answers
6 views

An index of homogenity in answers to poll questions

I've a dataset from an experiment where ppl were asked to answer more times the same question from a closed set of answers we're going to label here as {A, B, C, D}, then I count the number of answers ...
1
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1answer
168 views

correlation coefficient in linear regression

My interest is to develop a relation of the correlation coefficient when the data (both the dependent and independent variables) have measurement errors. Intro The measured values are related to the ...
0
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0answers
61 views

How to model partially nested & partially non-nested data in a mixed model?

How to model the data structure (correlation matrix / multicollinearity) for my dataset (described below)? Will it allow me to run a mixed model? At our website, we have pages with a block of ads ...
3
votes
3answers
144 views

Prediction Intervals with Heteroscedasticity

I am using R to perform linear regression. I have seen ways to calculate prediction intervals, but these depend on homoscedastic data. Is there a way to calculate prediction intervals with ...
1
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0answers
43 views

Presence of Heteroskedasticity, Robust Standard Errors - Stata

I have a panel of 49 observations, 7 countries, 7 years, running Panel fixed effects and IV fixed effects on Stata. I have used the modified Wald test to test for the presence of heteroskedasticity p ...
9
votes
3answers
205 views

What is this bias-variance tradeoff for regression coefficients and how to derive it?

In this paper, (Bayesian Inference for Variance Components Using Only Error Contrasts, Harville, 1974), the author claims ...
0
votes
1answer
250 views

How to determine the appropriate number of lags when using Newey-West (or HAC) standard errors

I have an unbalanced panel dataset where both autocorrelation and heteroskedasticity are present. I have read, in the Stata manual, that the newey command (see Newey-West, 1987) is one way in which ...
2
votes
1answer
80 views

General Linear Model Univariate with unequal variances - what are my options?

I'm using SPSS to run a GLM (general linear model) univariate with 1 fixed factor (Treatment) and one random factor (experimental replicate). There are 4 treatment groups. The measurement is number of ...
0
votes
0answers
105 views

Welch's one-way ANOVA vs other solutions for unequal sample sizes

I want to make a one-way ANOVA with three groups of data (inflow bays, non-inflow bays and main reservoir) on methane emission. After transformation each sample group is normally distributed and a ...
0
votes
1answer
23 views

Detecting heterogeneity in simple data set

I have a data set with an amount of tests that were done by a group of people for each day over two weeks (no weekends). Basically, I need to know which days differ the most from others. Here is the ...
0
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0answers
11 views

Testing for Homogeneity (not sure how to select benchmark/standard)

I am trying to see if the values for each day are homogeneous, and if not, which days seem different. Dataset is attached. I believe the right test for homogeneity would be a chi square test (correct ...
0
votes
0answers
15 views

How to conduct a three way ANOVA with non-normal and heteroscedastic data?

I am currently trying to analyze a data set to check the effect of three factors (year, plant, water stress) on yield. But the distribution of my data is not normal. I tried several transformations ...