similar to: Probit cluster-robust standard errors

Dear User R It's been a pleasure talking with you. I am newcomer use R. Would you please help me how to translate the script below to "R" script? * Area under receiver operating characteristic (AU-ROC) predict r1m1p, p roctab malaria r1m1p, graph summary * Area under receiver operating characteristic (AU-ROC) curve predict r1m2p, mu roctab malaria r1m2p, graph summary

Hi, I am trying to manipulate a gls regression model output to adjust for use of two-stage least squares. Basically, I want to estimate a model, then feed in a new set of residuals, then re-calculate all of the model output (i.e. the standard errors of the estimators, etc.). I have found some documentation on doing this in stata, which is below: http://www.stata.com/help.cgi?ereturn I am

*Dear Bert, * Thank you very much for your feedback and the useful link https://rseek.org/ and https://www.r-bloggers.com/calculating-auc-the-area-under-a-roc-curve/. Actually, I want to know different performance between Stata and R, in multilevel logistic regression. For this purposes, I replicate ".do" file use Stata in

Is there a way to create a BRR svrepdesign from a survey design when the number of PSUs is odd in one or more stratum? Creating a JKn svrepdesign with that condition works okay, but when I tried to create a svrepdesign with type="BRR" I get an error and this message: "Can't split with odd numbers of PSUs in a stratum" I get that message when I tell it to merge the

Hi, I am trying to figure out exactly what the bootcov() function in the Design package is doing within the context of clustered data. From reading the documentation/source code it appears that using bootcov() with the cluster argument constructs standard errors by resampling whole clusters of observations with replacement rather than resampling individual observations. Is that right, and is

Hi R-helpers I have a dataframe DF (lets say with the variables, y, x1, x2, x3, ..., clust) containing relatively many NAs. When I fit an ordinal regression model with the function lrm from the Design library: model.lrm <- lrm(y ~ x1 + x2, data=DF, x=TRUE, y=TRUE) it will by default delete missing values in the variables y, x1, x2. Based on model.lrm, I want to apply the robust covariance

I am trying to extract significance levels out of a robcov+ols call. For background: I am analysing data where multiple measurements(2 per topic) were taken from individuals(36) on their emotional reaction (dependent variable) to various topics (3 topics). Because I have several emotions and a rotation to do on the topics, I'd like to have the results pumped into a nice table.

Hi! I need to run ols regressions with Huber-White sandwich estimators and the correponding standard errors, without an intercept. What I'm trying to do is create an ols object and then use the robcov() function, on the order of: f <- ols(depvar ~ ind1 + ind2, x=TRUE) robcov(f) However, when I go f <- ols(depvar ~ ind1 + ind2 -1, x=TRUE) I get the following error: Error in

Greetings, I am revisiting code from several different files I have saved from the past and all used to run flawlessly; now when I run any of the svyglm related functions, I am coming up with an error: Error in model.frame.default(formula = F3ATTAINB ~ F1PARED, data = data, : the ... list does not contain 4 elements The following is a minimal reproducible example: library(RCurl)

I'm working with a 350MB CSV file on a server that has 3GB of RAM, yet I'm hitting a memory error when I try to store the data frame into a survey design object, the R object that stores data for complex sample survey data. When I launch R, I execute the following line from Windows: "C:\Program Files\R\R-2.9.1\bin\Rgui.exe" --max-mem-size=2047M Anything higher, and I get an

*Hola!!! resulta que tengo unos datos de divisas ordenados por fechas (días) los que he convertido a formato tipo YYYY-MM-DD donde DD siempre es 01:* * * * EUR.resto$date<-as.Date(EUR.resto$date) EUR.resto$mo <- substr(EUR.resto$date,6,7) EUR.resto$yr <- substr(EUR.resto$date, 1,4)

Hello, Is there a way to get complex sample variances in the survey package on summary statistics other than means? If not, can they be added to a future version? It would be be great to have them on totals, quantiles, ratios, and tables (eg row percent, columns percent, etc). Thanks. Fred --------------------------------- [[alternative HTML version deleted]]

Dear all, I am a R beginner, and I am looking for a way to do the same thing for all levels of a column in a table. Basically, I have a bunch of protein sequences composed of different amino acid residues, and each residue is represented by an uppercase letter. I want to calculate the ratio of different amino acid residues at each position of the proteins. Here is an example table: Proteins

hi, i am not hitting an error when i copy and paste your code into a fresh console. maybe compare your sessionInfo() to mine? > sessionInfo() R version 3.4.1 (2017-06-30) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows Server 2008 R2 x64 (build 7601) Service Pack 1 Matrix products: default locale: [1] LC_COLLATE=English_United States.1252

suddenly a few days ago it takes about a minute for local help to come up . i type : ?hist and get starting httpd help server ... done but only after a minute does http://127.0.0.1:15686/library/graphics/html/hist.html appear . Lee De Cola, PhD, MCP. DATA to Insight LDECOLA@COMCAST.NET Reston, Virginia 703 709 6972 571 315 0577 mobile [[alternative HTML version deleted]]

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934

Dear all, my aim is to estimate the efficacy over time of a treatment for headache prevention. Data consist of long sequences of repeated binary outcomes (1 if the subject has at least 1 episode of headache , 0 otherwise) on subjects randomized to placebo or treatment. I have fit a logistic regression model with Huber-White cluster sandwich covariance estimator. I have put in the model the

I am trying to compute the white heteroskedasticity-robust standard errors (also called the Huber standard errors) in a linear model, but I can't seem to find a function to do it. I know that the design library in S+ has something like this (robcov?), but I have not yet seen this library ported to R. Anyone know if there is already a function built into R to do this relatively simple job?

Hi, I want to make a plot similar to sm1 (attached). The code I tried is: dcols <- densCols(x,y) smoothScatter(x,y, col = dcols, pch=20,xlab="A",ylab="B") abline(h=0, col="red") But it turned out to be s1 (attached) with big dots. I was wondering if anything wrong with my code. Thanks,Zhengyu -------------- next part -------------- A non-text

I am using the Design library and robcov to compute variance-covariance matrices for clustered data regression. Is there an easy way to compute the F-test (i.e. linear hypothesis) for clustered data regression ? Thanks in advance! Benn