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2
votes
0answers
22 views

Refining “good” mixing time estimate

Fix a Markov chain $\{ X_{t} \}_{t \in \mathbb{N}}$ with mixing time $\tau_{\mathrm{mix}}$. Assume that I know some finite bound on the mixing time $\tau_{\mathrm{mix}} < \tau < \infty$, and ...
0
votes
0answers
43 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 ...
5
votes
1answer
139 views

Are normally distributed residuals not necessarily homoskedastic?

Let's say I've ran a linear regression and I'm checking the model diagnostics. I made a histogram of the residuals and they appear more or less normally distributed as below. I thought for a long ...
3
votes
3answers
67 views

Too many predictors to manually check linearity

Say I have 1000 potential predictors in a logistic regression. I don't have time to check each predictor manually for linearity. I could wait till after variable selection, but in that case I wonder ...
0
votes
0answers
22 views

Diagnostics for the analysis of variance model

I have problem with the diagnostic of the one way analysis of variance model (fitted in R). I've checked all the assumptions of the analysis of variance 1) "For each level of the within-subjects ...
0
votes
0answers
45 views

Model assumptions and diagnostics for proportional hazard regression model with frailty in R

I am wondering are there any assumptions that must be met in the proportional hazard regression model with frailty? I remember that in regular proportional hazard model without frailty all variables ...
2
votes
2answers
155 views

Is residuals autocorrelation always a problem?

I read that OLS underestimates variance when residuals are autocorrelated. I see why autocorrelation would be a problem in time series analysis, in the sense that the coefficient are not efficient ...
1
vote
0answers
26 views

VECM Diagnostic Test

I have got few questions about VECM and cointegration test. Basically I conducted a cointegration test on two time series (spot vs forward price) by using the Johansen procedure. The results suggest ...
3
votes
1answer
122 views

What resolution should I be using for residuals vs fitted values plot from a linear regression?

I made this linear regression that shows how well estimated animal locations (longitude) predict actual animal locations. ...
4
votes
1answer
46 views

Geweke diagnostic of a Markov chain: why does the first window have to cover the burn-in?

I read the following statement in this document$^{[1]}$, at the bottom of page 11: Too wide A will some times “hide” the burn in part within the converged part of the chain and the difference in ...
1
vote
1answer
113 views

How to compare the positive predictive value and negative predictive value of two diagnostic tests?

Im a surgeon who's trying to compare two diagnostic tests that are used to diagnose appendicitis. Two diagnostic tests were applied on 150 patients and the results were compared to a gold standard. I ...
5
votes
1answer
109 views

Is the goodness of fit test in JMP the Hosmer-Lemeshow goodness of fit test?

I'm working with an organization that is using JMP in their analysis, and I can't tell from the description in JMP's help files if the test for goodness of fit in their logistic regression is the ...
3
votes
1answer
70 views

How to treat this OLS based on residual diagnostics

I am struggling already a couple of days with this simple OLS, can you help? Outcome years in function of predictor score, very simple linear model. The residual plot does absolutely not look good ...
18
votes
4answers
484 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
100 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
55 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
29 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
25 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
43 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
111 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?
4
votes
1answer
269 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
324 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 ...
1
vote
0answers
105 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 ...
4
votes
0answers
215 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
349 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
171 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 ...
5
votes
1answer
869 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
2k 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
2k 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
2k 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
91 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
682 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
358 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
2k 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
1k 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
309 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?
4
votes
1answer
620 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
327 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
3k 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
161 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 ...
15
votes
2answers
7k 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
4k 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
9k 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
1k 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
317 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
444 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
2k 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 ...
16
votes
2answers
15k 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
698 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 ...