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Bivariate normal regression in R
3 messages · DHIMAN BHADRA, Dimitris Rizopoulos, Viechtbauer Wolfgang (STAT)
One possibility is function gls() from package nlme. Best, Dimitris
On 8/25/2011 8:22 PM, DHIMAN BHADRA wrote:
Hello everyone, I need to fit a bivariate normal regression model to a dataset where the same covariate (say, X) influences two separate but correlated responses (say, Y1 and Y2). So, the bivariate model would look like : Y1 = a1 + b1*X + e1 Y2 = a2 + b2*X + e2 where e1 and e2 are error terms which can be correlated. Is there any package in R which can help me fit this model ? Any help will be appreciated. Best regards, Dhiman Bhadra Worcester Polytechnic Institute, 100 Institute Road, Worcester, Ma : 01609. [[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Dimitris Rizopoulos Assistant Professor Department of Biostatistics Erasmus University Medical Center Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands Tel: +31/(0)10/7043478 Fax: +31/(0)10/7043014 Web: http://www.erasmusmc.nl/biostatistiek/
Another way would be to consider this as a path model and use the sem or lavaan package to fit this model. Here is an example:
x <- rnorm(1000)
e1 <- rnorm(1000)
e2 <- e1 + rnorm(1000)
e1 <- e1 + rnorm(1000)
y1 <- 2 + 1*x + e1
y2 <- 4 + 2*x + e2
dat <- data.frame(x, y1, y2)
model <- 'y1 ~ x
y2 ~ x'
fit <- sem(model, data=dat)
summary(fit)
However, note that you could just as well run two separate regressions:
summary(lm(y1 ~ x))
summary(lm(y2 ~ x))
The results are virtually identical.
Best,
Wolfgang
-----Original Message----- From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Dimitris Rizopoulos Sent: Thursday, August 25, 2011 20:28 To: DHIMAN BHADRA Cc: r-help at r-project.org Subject: Re: [R] Bivariate normal regression in R One possibility is function gls() from package nlme. Best, Dimitris On 8/25/2011 8:22 PM, DHIMAN BHADRA wrote:
Hello everyone, I need to fit a bivariate normal regression model to a dataset where the same covariate (say, X) influences two separate but correlated responses (say, Y1 and Y2). So, the bivariate model would look like : Y1 = a1 + b1*X + e1 Y2 = a2 + b2*X + e2 where e1 and e2 are error terms which can be correlated. Is there any package in R which can help me fit this model ? Any help will be appreciated. Best regards, Dhiman Bhadra Worcester Polytechnic Institute, 100 Institute Road, Worcester, Ma : 01609. [[alternative HTML version deleted]]
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-
guide.html
and provide commented, minimal, self-contained, reproducible code.
-- Dimitris Rizopoulos Assistant Professor Department of Biostatistics Erasmus University Medical Center Address: PO Box 2040, 3000 CA Rotterdam, the Netherlands Tel: +31/(0)10/7043478 Fax: +31/(0)10/7043014 Web: http://www.erasmusmc.nl/biostatistiek/
______________________________________________ R-help at r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting- guide.html and provide commented, minimal, self-contained, reproducible code.