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17
votes
4answers
381 views

Why does my bootstrap interval have terrible coverage?

I wanted to do a class demonstration where I compare a t-interval to a bootstrap interval and calculate the coverage probability of both. I wanted the data to come from a skewed distribution so I ...
0
votes
0answers
21 views

rugarch - How to add confidence intervals to QQ plots?

I want to add a 95% confidence interval to standardised residuals QQ plot obtained from rugarch plot function. I don't know how to add this confidence interval but check the QQ plot that I obtained: ...
1
vote
0answers
25 views

What plots should be used for diagnostics for linear mixed model?

Before fitting a linear mixed model, can any plots be used to show a random intercept/slope is justifiable in the model? I.e. these plots may indicate a different pattern for each individual over ...
1
vote
0answers
16 views

Help in interpreting AUC values from ordinal variables

I would appreciate if someone could explain to me the benefit of using area under ROC for evaluating agreements between two raters. Here is an example from two raters on, let's say, clinical time ...
0
votes
0answers
24 views

Logistic regression diagnostics [duplicate]

In linear regression, we need to check which assumption is violated. But for logistic regression, what assumptions do we have for the model? I was attempting to wrap my head around this thing. But ...
1
vote
0answers
35 views

Simulation for model checks for sample size

In the book Bayesian and Frequentist Regression Methods, Wakefield notes that estimators for coefficients in a linear model will be normal if the error terms are normal or if the sample size is ...
1
vote
1answer
65 views

Visually inspecting normality of variables

I'm using R to plot some graphs for visually inspecting the normality of variables that will go into a linear regression model. Except for a histogram and a QQ plot, what other graphics could I use?
3
votes
1answer
102 views

What diagnostics for random effects logistic regression?

I'm wondering what checks/diagnostics you usually calculate and report if you do a random effects logistic regression. C-statistic/ROC curve Check multicollinearity? Check heteroscedasticity? ...
9
votes
1answer
274 views

Why are diagnostics based on residuals?

In simple linear regression one often wants to verify if certain assumptions are met to be able to do inference (e.g. residuals are normally distributed). Is it reasonable to check the assumptions ...
0
votes
0answers
54 views

Augmented component plus residual plots

To test for linearity, it has been suggested that augmented component plus residual plots are the best option (acprplot in Stata). Should this analysis be done for ...
1
vote
0answers
77 views

Has anyone written a package in R to calculate diagnostic plots after clogit (conditional logistic regression)? e.g. leverage

Has anyone written a package in R to calculate diagnostic plots after clogit, conditional logistic regression? e.g. leverage. Or ...
0
votes
0answers
30 views

What caveats apply to algorithmic detection of linearity/normality/homoscedasticity violations in residuals, and what cannot be automated at all?

Note: I start out talking about software, but this is not a software question. Please don't migrate to SO. I'm working on software that allows users to specify regression models using a graphical ...
0
votes
0answers
68 views

Running linear mixed effects model with Amelia package - How to run model diagnostics?

I'm trying to run a fairly simple linear mixed effects model in R, using the Zelig model ls.mixed (multi-level least-squares ...
4
votes
0answers
125 views

Diagnostics for GEE in R

I have been checking out which diagnostics to use for a GEE analysis. It seem that influence measures are appropriate (Preisser, 1996). Does anyone know of a package that can be used in R to examine ...
2
votes
2answers
179 views

does rstandard standardize in z?

I'm new to R, so please be gentle. I was under the impression that rstandard(model) returns the z-scores of the residuals in ...
2
votes
0answers
125 views

How to compute sample size to compare two diagnostic tests

I will be performing two diagnostic tests (one is the gold standard, one is novel) on the same subject aiming to establish sensitivity, specificity, PPV and NPV. What formula may be used to compute ...
4
votes
1answer
469 views

Please help me refine this zero-inflated negative binomial model

I have been working on a baseball model to predict success at the major league level using minor league statistics. After posting multiple threads on this site (1, 2, 3) and receiving valuable ...
4
votes
0answers
678 views

Fitting a zero-inflated negative binomial regression with R

In this thread, I laid out a problem involving fitting a model that attempts to use minor league baseball statistics to predict success at the major league level (explained in full in the thread). ...
3
votes
1answer
722 views

How to calculate the confidence intervals for likelihood ratios from a 2x2 table in the presence of cells with zeroes

I am analysing a diagnostic test (against a gold standard, using a 2x2 table). I want to calculate likelihood ratios (sensitivity / (1-specificity) etc) however I have several sets of data with 0 ...
3
votes
2answers
1k views

Standardized residuals in R's lm output

I have a quick question: if I plot the diagnostic plots to an R regression, a couple of them have "Standardized Residuals" as their y-axis such as in this plot: My question is this: what are the ...
2
votes
1answer
73 views

Explanation of a step in derivation of residuals for R lm diagnostic?

I'm reading Faraway's book (http://cran.r-project.org/doc/contrib/Faraway-PRA.pdf) to try to understand R's lm diagnostic plots. On page 72 of the book is this: I have been trying to understand a ...
1
vote
1answer
363 views

How do I compute a cutoff based on sensitivity/specificity when the characteristics of my sample is different from the population?

I have a dataset containing the performance of a novel instrument to screen for disease A. The novel instrument uses a scoring system to score the subject to determine if they have disease A. I then ...
3
votes
3answers
275 views

Troublesome residual plot from linear mixed model

I have fitted the following linear mixed model based on the results of an economic game: lmer(TotalScore~perOOgivenP+Game+(1|Subject),REML=T,data=mdl1table)->m1 ...
3
votes
1answer
1k views

How to validate & diagnose a gamma GLM in R?

I am fitting a generalized linear model in R with the log link and I need to validate and diagnose my model. I have never worked with the GLM in the past. Is there an article or any references I ...
1
vote
2answers
911 views

How to test outliers, normality, homoscedasticity? [closed]

With the Data Analysis command in Excel I made a plot, which I can't post, because this is my first post ever. ...
8
votes
2answers
262 views

What are some good exploratory analysis and diagnostic plots for count data?

Does anyone know of good reference material on exploratory analysis and diagnostic plots for count data?
1
vote
0answers
461 views

MCMC Geweke diagnostic

I'm running a Metropolis sampler (C++) and want to use the previous samples to estimate the convergence rate. One easy to implement diagnostic I found is the Geweke diagnostic, which computes the ...
4
votes
1answer
1k views

Diagnostic plots for lmer

I am trying to produce a glmm using the lme4 package in R. To validate my model I would like to produce some diagnostic plots ...
2
votes
0answers
256 views

How to verify linearity assumption in linear regression with categorical predictors?

I have used simple linear regression, and I'm now checking that the model meets the assumption of linearity. The model used a continuous response variable and categorical explanatory variables. How ...
2
votes
0answers
2k views

Collinearity diagnostics disagree - VIF, condition index, and correlation matrix

I'm working with a large dataset consisting of just over 1 million cases. The data are longitudinal covering 14 years and hierarchical with about 500 of the level 2 units. Each case is a criminal ...
0
votes
0answers
141 views

Test for convergence within Gibbs sampler

I am running a Gibbs sampler for Multivariate Normal times Inverse Wishart posterior distribution with missing data imputation step. I am trying to check if my step of simulating covariance matrices ...
13
votes
2answers
5k views

Interpreting residual diagnostic plots for glm models?

I am looking for guidelines on how to interpret residual plots of glm models. Especially poisson, negative binomial, binomial models. What can we expect from these plots when the models are ...
1
vote
2answers
3k views

How to interpret model diagnostics graphics after R linear regression? [closed]

I am interested in understanding the graph plots we get after running lm() command (for linear regression) in R like, for example ...
2
votes
1answer
5k views

How to interpret model diagnostics when doing linear regression in R?

I ran lm() on my data with models selected by individual lm's of each characteristic and then combined the top $R^2$ based on ...
5
votes
2answers
882 views

Residuals for logistic regression and Cook's distance

Are there any particular assumptions regarding the errors for logistic regression such as the constant variance of the error terms and the normality of the residuals? Also typically when you have ...
2
votes
1answer
253 views

Logistic regression and complementary log log model

is there like a diagnostic checking(like those in the time series) done for logistic regression and complementary loglog model?
3
votes
4answers
361 views

Communicating Regression Model Results

I am concerned about how unequipped most people are (both within and without academia) to properly employ standard model building methods such as linear regression and to interpret the results of ...
3
votes
1answer
1k views

Explanation of R diagnostic plot for logistic regression

I'm hoping someone can explain this bit of R code for me related to glm(). I don't understand the diagnostic plot that has been suggested. It seems a more ...
13
votes
2answers
11k views

How to read Cook's distance plots?

Does anyone know how to work out whether points 7, 16 and 29 are influential points or not? I read somewhere that because Cook's distance is lower than 1, they are not. Am, I right?
1
vote
1answer
608 views

How to test the randomness of residual plot?

Let's say in linear regression, I got a fit and I can plot residuals to see whether there is any systematic trend in such a plot. How to quantitatively determine whether the residues are really ...
14
votes
2answers
706 views

What diagnostic plots exists for quantile regression?

Following on my question for OLS, I wonder: what diagnostic plots exists for quantile regression? (and are there R implementation of them?) A quick google search already came up with the worm plot ...
6
votes
2answers
663 views

Possible extensions to the default diagnostic plots for lm (in R and in general)?

I started digging a bit into the plot.lm function, this function gives six plots for lm, they are: a plot of residuals against fitted values a Scale-Location plot of sqrt(| residuals |) against ...
3
votes
0answers
192 views

“Brute force” expected deviance for logistic regression?

A commonly used goodness of fit statistic for logistic regression is the deviance. This is also known as the likelihood ratio chi-square statistic. It is defined as: $$D=\sum_{i=1}^{N}d_i^2$$ ...
2
votes
1answer
352 views

Functions for regression diagnostics on mer objects in R

I'm particularly interested in plotting residuals against fitted values, and residuals against predictors. Often times I need to make boxplots of the residuals conditional on predictors. I'd be ...
5
votes
3answers
409 views

In linear regression, is the $R^2$ value enough to assess whether the relationship between the independent and dependent variable is linear?

In linear regression, is the $R^2$ value enough to assess whether the relationship between the independent and dependent variable is linear? It gives the amount of variability in the dependent ...
6
votes
2answers
424 views

How to combine the results of several binary tests?

First off let me say that I had one stats course in engineering school 38 years ago. So I'm flying blind here. I've got the results of what are essentially 18 separate diagnostic tests for a ...
1
vote
0answers
92 views

How do I go about conducting model diagnostics on WLS?

I'm familiar with the diagnostics required for OLS, however I'm in new territory with a model I'm fitting to data in R, using Poisson regression with GLM. What are the standard methods in evaluating ...
1
vote
0answers
88 views

Failure detection method

I receive 1000 points per day from installations who produces electricity. Every installation must proportionally produce the same amount of energy. I have to spot failures in those data. The actual ...
11
votes
2answers
13k views

Likelihood ratio test in R

I'm not sure if I'm asking something stupid or off topic here, but I can't think where can I ask this question. suppose I am going to do a univariate logistic regression on several independent ...
12
votes
3answers
536 views

Is it valid to analyze signal detection data without employing metrics derived from signal detection theory?

A signal detection experiment typically presents the observer (or diagnostic system) with either a signal or a non-signal, and the observer is asked to report whether they think the presented item is ...