similar to: new package clubSandwich: Cluster-Robust (Sandwich) Variance Estimators with Small-Sample Corrections

Hello All! I have been working with R for the last couple of weeks and I am very impressed with the capabilities. I am creating hundreds of tables and need to dynamically name the columns. Here is a small snippet of my code: # Turn my clustering data into a data.frame object. names( clusters ) <- Abbreviate( distMethods[ i ], hclustMethods[ j ] ) df <- data.frame( clusters,

The Toolkit for Weighting and Analysis of Nonequivalent Groups (twang 1.0) has been released to CRAN. The package collects functions useful for computing propensity score weights for treatment effect estimation, developing nonresponse weights, and diagnosing the quality of those weights. The package includes a vignette containing some basic theory and walks through two examples. It is available by

Hi All, I have a dataset, longitudinal in nature, each row is a 'visit' to a clinic, which has numerous data fields and a count variable for the number of 'events' that occurred since the previous visit. ~50k rows, ~2k unique subjects so ~25 rows/visits per subject, some have 50 some have 3 or 4. In STATA there is an adjustment for the fact that you have multiple rows per

Dear R-Users: I am trying to find the robust (or sandwich) estimates of the standard error of fixed effects parameter estimates using the package "lmer2". In model-1, I used "robust=TRUE" on the other, in model-2, I used "robust=FALSE". Both models giving me the same estimates. So my question is, does the robust option works in lmer2 to get the robust estimates of

There may be benefits to having a machine learning method that explicitly targets covariate balance. We have experimented with optimizing the weights directly to obtain the best covariate balance, but got some strange solutions for simple cases that made us wary of such methods. Machine learning methods that yield calibrated probability estimates should do well (e.g. those that optimize the

Nav?tivte na?e webov? str?nky infotigra a objevte, jak JEDNA jedin? mal? modr? pilulka m??e do?ivotn? zm?nit VA?I sexu?ln? v?konnost! ? V??en? z?kazn?k! V?deck? testy prok?zaly, ?e TIGRA funguje l?pe ne? jak?koli jin? pilulka. Test na 800 mu??ch ve v?ku 21 a? 80 let prok?zal ohromuj?c? v?sledky: ? 1. A? o 71 % siln?j?? touha

Dear useRs, here is the announcement for the next "new" package: sandwich 0.1-3. sandwich provides heteroskedasticity (and autocorrelation) consistent covariance matrix estimators (also called HC and HAC estimators). The former are implemented in the function vcovHC() (which was available in strucchange before - and independently in hccm() in John Fox's car package). And the

Dear useRs, here is the announcement for the next "new" package: sandwich 0.1-3. sandwich provides heteroskedasticity (and autocorrelation) consistent covariance matrix estimators (also called HC and HAC estimators). The former are implemented in the function vcovHC() (which was available in strucchange before - and independently in hccm() in John Fox's car package). And the

Is it possible to get the empirical (sandwich) S.E. estimates for the fixed effects in lme () (thus allowing possibly correlated errors within the group)? In SAS you can get it by the 'empirical' option to PROC MIXED. Cheers, Michael -- Na (Michael) Li, Ph.D. Division of Biostatistics A443 Mayo Building, MMC 303 School of Public Health 420 Delaware

Hi, I'm trying to reproduce with R the results of this study: https://learn.gold.ac.uk/mod/resource/view.php?id=262406 More precisely I want to reproduce the results of the table 6 (pag.280), which can also be seen here: http://picpaste.de/pics/table-robin-llKCOeWV.1501745645.png Let's take the first column: we have a coeff. of 0.097 and a SE of 0.026, which represents clustered robust

Dear useRs, a new version 2.0-0 of the sandwich package for estimating sandwich covariance matrices is available from the CRAN mirrors. The tools for computing heteroskedasticity (and autocorrelation) consistent covariance matrix estimators (also called HC and HAC estimators, including the Eicker-Huber-White estimator) have been generalized over the last releases from linear regression to

Hi, I would like to estimate coefficients using poisson regression and then get standard errors that are adjusted for heteroskedasticity, using a complex sample survey data. Then I will calculate prevalence ratio and confidence intervals. Can sandwich estimator of variance be used when observations aren?t independent? In my case, observations are independent across groups (clusters), but

Dear R-help, I have a four-part question about regression, matrices, and sandwich package. 1) In the sandwich package, I would like to better understand the meat() function. >From the bread() documentation, for a simple OLS regression, bread() returns (1/n * X'X)^(-1) That is, for a simple regression (per the documentation on bread()): MyLM <- lm(y ~ x) bread(MyLM)

Dear List, I'm just teaching myself semi-parametric techniques. Apologies in advance for the long post. I've got observational data and a longitudinal, semi-parametric model that I want to fit in GAM (or potentially something equivalent), and I'm not sure how to do it. I'm posting this to ask whether it is possible to do what I want to do using "canned" commands

thank you, achim. I will try chol2inv. sandwich is a very nice package, but let me make some short suggestions. I am not a good econometrician, so I do not know what prewhitening is, and the vignette did not explain it. "?coeftest" did not work after I loaded the library. automatic bandwidth selection can be a good thing, but is not always. as to my own little function, I like the

First of all, Thank you for a great program... I am trying to setup a sort of Radio Station for our College and your program is ideal. So yeah thanks. However i have a question: I understand that to stream over the internet you need a streaming server. Correct? BUT for me, streaming over our LAN, will that be necerssary? Ideally I would like to use the computer that is running Icecast to

>>>>> "TL" == Thomas Lumley <tlumley@u.washington.edu> >>>>> on Sun, 6 Oct 2002 09:19:27 -0700 (PDT) writes: TL> On Sat, 5 Oct 2002 roxburg@kih.net wrote: >> This is not a bug report but didn't see another way to >> ask a question. TL> Well, you could try the r-help or r-devel mailing lists >> For

When using function heckit() from package ‘sampleSelection’, is there anyway to make t-tests for the coefficients using robust covariance matrix estimator? By “robust” I mean something like if a had an object ‘lm’ called “reg” and then used: > coeftest(reg, vcov = vcovHC(reg)). I’m asking this because in Stata we could use function heckman and then use vce option “robust”. We could do the

Dear Sir/Madam Hi. I am a general paediatrician, and I have read *some* chapters of the following books(1-3). I think SPSS lacks some features that may be important in data analysis (for example: interval of correlation coefficient in bivariate normal distribution, PRESS, and MSPR in cross-validation). I am thinking about changing SPSS to R: 1. SPSS is very expensive for me to update.

(This time with the r-help in the recipients...) Be careful when mixing lme4 and lmerTest together -- lmerTest extends and changes the behavior of various lme4 functions. >From the help page for lme4-anova (?lme4::anova.merMod) > ?anova?: returns the sequential decomposition of the contributions > of fixed-effects terms or, for multiple arguments, model >