You need to call the summary() method to obtain the standard errors, e.g.,
result.plr <- polr(formula, data = mydata, method = "probit", Hess = TRUE) coef(summary(result.plr)) for checking which predictors are significant you also use stepAIC() or the bootstrap version of it, i.e., boot.stepAIC() in the `bootStepAIC' package, e.g., library(bootStepAIC) boot.stepAIC(result.plr, data = mydata) I hope it helps. Best, Dimitris ---- Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/(0)16/336899 Fax: +32/(0)16/337015 Web: http://med.kuleuven.be/biostat/ http://www.student.kuleuven.be/~m0390867/dimitris.htm ----- Original Message ----- From: <[EMAIL PROTECTED]> To: <[email protected]> Sent: Monday, June 04, 2007 8:02 AM Subject: [R] How to obtain coefficient standard error from the result ofpolr? > Hi - I am using polr. I can get a result from polr fit by calling > > result.plr <- polr(formula, data=mydata, method="probit"); > > However, from the 'result.plr', how can I access standard error of > the estimated coefficients as well as the t statistics for each one > of them? > > What I would like to do ultimately is to see which coefficients are > not significant and try to refit the model again by excluding those > variables out. I would appreciate if anyone could give some hint on > this. Thank you. > > - adschai > > [[alternative HTML version deleted]] > > ______________________________________________ > [email protected] 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. > Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm ______________________________________________ [email protected] 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.
