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16 views

t-Test residual analysis and Welch's correction

I'm reading Experimental Design and Analysis by H.Seltman (http://www.stat.cmu.edu/~hseltman/309/Book/Book.pdf) and working on the provided HCI dataset (SPSS format, can be downloaded from page 143). ...
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0answers
23 views

Prediction with a linear simple regression model - out of sample testing

I am validating a model and was analysing the residuals. Although they have mean zero and st. deviation close to zero, when I plot them (q-q plot), they don't seem to follow a normal distribution. Is ...
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1answer
26 views

Residual Analysis and ANOVA Model

I am very new to residual analysis and ANOVA. To my understanding, in the residual plot, residuals should not show obvious patterns, thus if the pattern is random, it indicates a good fit for a linear ...
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0answers
48 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 ...
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0answers
3 views

Find damage index by residual force method

I need to find damage index by residual force method. I have found the residual force then I need to find the damage index. I have the formula $S \alpha = R$ where $\alpha$ is my damage index. The ...
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0answers
16 views

Jackknife residuals formula

I know that the jackknife residuals are $$t_i={y_i-\hat y_{(i)}\over \hat \sigma^2_{(i)}(1+x^t_i(X^t_iX_i)^{-1}x_i)^{1/2}}$$ But there is alsa a formula for computing these residuals: ...
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1answer
69 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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0answers
22 views

Standardized residuals vs fitted values for Poisson regression

McCullagh and Nelder's book on glm suggest to plot standardized deviance residuals against either the linear predictor ($\hat{\eta}$) or the fitted values ($\hat{\mu}$) transformed to the constant ...
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1answer
46 views

variance decreases when x gets farther from the average x?

I just read the description of Studentized residual on Wikipeida. I'm confused about what it says about variance, it says that "the residuals, unlike the errors, do not all have the same ...
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0answers
13 views

Visual examination of residuals for a large dataset

Often, as part of verifying that the assumptions of a model (such as OLS) are reasonable, I see advice to visually check that the model residuals are distributed relatively consistently around 0 as ...
0
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1answer
38 views

Correlation residuals vs standardized residuals in SEM package in R

I've been working with SEM package in R recently that I happened to read it's manual for the standardizedResiduals. In the manual, Residuals are defined as S - C, where S is the sample covariance ...
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0answers
25 views

When forecasting a time series using artificial intelligence, why aren't the errors diagnositic?

Recent, modern methods for predict or forecast time series has widely used. several modern methods are neural network, fuzzy logic, ANFIS, etc. When we use these method for time series forecasting, ...
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18 views

Plots of residuals in linear regression

I wanted to know the intuition behind the plots of residuals vs time, residuals vs fitted values and residuals vs explanatory variables. Could anyone intuitively explain to me what they are supposed ...
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0answers
29 views

Why points of fitted vs. residuals plot are dependant of random effect level in my mixed model?

I have fitted a linear mixed model. The fitted vs. residuals plot is colored by the random effect level. As the model takes care of the random effect, I would expect that the fitted vs residuals ...
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0answers
21 views

Residual Not Normal for Model Seasonal Time Series in R

I got a problem when choose the model for forecasting with time series. I'm in a middle writing my Thesis. My data have a seasonal pattern so, i tried use this model ...
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1answer
35 views

Positive serial correlation

Blows are the pictures from my course lecture. The lecture states only the second picture shows a positive serial correlation, and the first picture requires time to be added as a predictor while ...
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2answers
39 views

Regression Analysis — Correlation of Residuals

I see a lot of info on how to detect correlation of residuals and why it might negatively impact the quality of our model. I however dont see much info on how to mitigate the bad effects of these ...
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0answers
86 views

What causes bands/stripes in residual plots?

I ran a model and got the following residuals: I proceeded to log the fitted values to get an idea of what's happening at the lower end of my predicted values: It was then I saw on the left side ...
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0answers
7 views

When should we use Absolute Deviance Residual Plot or Deviance Residual Plot?

My lecturer mentioned that Absolute Deviance Residual Plot is better to use than the Deviance Residual Plot when analyzing fit of model in the GLM process. I was wondering what do you guys think about ...
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0answers
80 views

Residuals plot interpretation

These are plots created in R. All of them are residuals (errors) vs. fitted values. They come from multiple linear regression models fitted by least squares. The five plots represent 5 different ...
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0answers
26 views

TReading Residual Plot: Omitted Variable Bias of Dummy Variable

I have a plot of the residuals versus fitted values of an OLS model such that the shape of the plot are two identical randomly scattered clouds, one above and one below the $\hat{e} = 0$ line. Can I ...
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1answer
169 views
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0answers
33 views

Estimating Studentized Residuals (or Another Similar Measure) After Linear Regression With Robust Standard Errors

I have estimated a linear multiple regression with robust standard errors using Stata (regress depvar indepvar1 indepvar2 indepvar3 indepvar4 indepvar5, robust). ...
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21 views

Does it make sense to standardize residual using $SSE/(n-1)$?

See[Dean and Voss]Design and Analysis of Experiments,1999. pp.105 The authors proposed that we standardize residuals using: $$z_{it}=\frac{\hat{e_{it}}}{\sqrt{ssE/(n-1)}}$$ where ...
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23 views

Analysis of charts

Let $X$ a variable that represents the performance of a student in high school and a variable $Y$ representing the performance of this same student at the university. Consider the regression ...
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3answers
206 views

Residuals in regression should not be correlated with another variable

This minitab post on checking residuals says: If you can predict the residuals with another variable, that variable should be included in the model. I would think if we can predict residuals ...
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2answers
288 views

GLM diagnostics and Deviance residual

From my understanding, the deviance residual of a GLM model, when plotted against the fitted values, should give a scatterplot distributed with mean 0 and constant variance? Does this hold for any GLM ...
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0answers
71 views

Diagnostics and residual analysis for Poisson regression

Recently, I was asked to check for serial correlation after doing a panel Poisson regression. I haven't seen such a test and in general, researchers (at least in the econom(etr)ics literature) don't ...
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1answer
3k views

How exactly are standardized residuals calculated

I'm working on a model for something and at the moment I prefer working solely in Excel. I've been double checking the results of the linear model in JMP, Minitab, and Statistica, and (more or less) ...
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0answers
55 views

Plotting and interpreting residuals in Stata - How to identify a structural break?

I am researching firm level data with Stata 13. My endogenous variable is (unfortunately only) of binary nature and indicates whether a firm engaged in R&D activities or not (0;1). I use a panel ...
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2answers
95 views

I am running a logistic regression model and get very low predicted probabilities

I am running a logistic model for catastrophic health expenditure (CHE) in Argentina. The sample size is 22500. I followed Xu et al. methodology to define CHE and adjusted for 8 socioeconomic ...
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4answers
555 views

How can I test a nonlinear vs a linear regression model?

I've got a panel regression model where the Ys assume a curved shape when plotted over time. A histogram of the residuals shows they are normally distributed but a residual-vs-fitted plot shows a ...
0
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1answer
171 views

Residual diagnostics after a logistic regression model [duplicate]

I wonder about how the residuals of a logistic regression model should be distributed. Of course, running a linear regression model and by assuming the Normal distribution assumption, the residuals ...
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2answers
1k views

Residual plots: why plot versus fitted values, not observed $Y$ values?

In the context of OLS regression I understand that a residual plot (vs fitted values) is conventionally viewed to test for constant variance and assess model specification. Why are the residuals ...
2
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2answers
318 views

Interpreting linearity in residual vs. fitted plot

I am working on a linear regression model and I am not sure how to interpret the following residual vs fitted values plot. For all I know residuals are supposed to fluctuate randomly around 0 ...
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1answer
61 views

Can heteroskedastic residuals be justified by variance in dependent variable?

This is a very basic question and I hope it is not a duplicate. Im using a pooled regression model with a log-transformed dependent variable (electricity consumption meter values). The variance of ...
2
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2answers
250 views

How to verify a linear model?

Given a dataset and liner model, how can I verify its sufficient quality? ...
0
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1answer
66 views

Goodness of regression model

What are the main indicators of goodness of a regression model? Are they MSE (mean squared error) http://en.wikipedia.org/wiki/Mean_squared_error , R-squared and adjusted R-squared only? Can mean of ...
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0answers
359 views

How to use residual analysis to remove the effect of confounding variables in a model in R

I want to find which soil variables better explain plant productivity, using a database that contains information for about 100 forests plots across Europe. These plots have only one species per plot, ...
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0answers
42 views

Degrees of freedom with duplicate data points

The degrees of freedom of the residual in an OLS model is $n - p - 1$, where $n$ is the number of samples, and $p$ is the number of independent variables. I.e., the data matrix $X$ is $n\times p$. If ...
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0answers
204 views

Arima Models Diagnostics

I'm doing a forecasting using seasonal ARIMA method. I'm using astsa package in r and I'm testing two models that I can't decide which one is better to use than the other The ACf and PACF for the ...
2
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0answers
79 views

Heavy-tailed errors in mixed-effects model

I'm relatively new to statistical modelling and `R', so please let me know If I should provide any further information/plots. I did originally post this question here, but unfortunately have not ...
3
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1answer
331 views

Interpreting case influence statistics (leverage, studentized residuals, and Cook's distance)

I just wanted to clarify some things about leverage, studentized residuals, and Cook's distance: Does a large (in absolute value) studentized residual mean that a case is an outlier? Does a large ...
3
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1answer
108 views

What if a transformed variable yields more normal and less heteroskedastic residuals but lower $R^2$?

I am trying to decide whether to use a square root transformed dependent variable in multiple linear regression. Transforming $y$ leads to more normally distributed residuals and also to less ...
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1answer
79 views

Analysing the residuals themselves

As far as I know, it is possible to fit a linear regression model and then fit a second model to predict the residuals from the first model by using some other variables. By this you can understand ...
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1answer
290 views

Not sure about the interpretation of this residual plot

I'm analyzing a residual plot of the residuals vs the fitted values. I'm not quite sure how to interpret this plot since there looks like there is a pattern and the average is not actually zero. ...
2
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1answer
78 views

What is the benefit of knowing the F statistic in multiple linear regression?

One of the basic figures you get when running multiple linear regression using almost any off-the-shelf software is the F statistics. However, I cannot recall one situation, where the F value was low ...
2
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1answer
97 views

Multiple Regression - Residual Analysis

I am doing a multiple regression analysis regressing GPA against several 0/1 indicator variables (representing course completions). My fitted vs. residual plot is biased and looks awful. See below. Is ...
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2answers
4k 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
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1answer
85 views

How to perform residual analysis for weighted linear regression?

How do we perform residual analysis (verifying homoskedasticity, normality and independence of errors) for weighted linear regression? By weighted, I mean each row in the dataset has weight assigned ...