[R] Correct statistical inference for linear regression models without intercept in R

[peter dalgaard]

On Jul 20, 2010, at 11:41 AM, StatWM wrote:

> 
> Dear R community,
> 
> is there a way to get correct t- and p-values and R squared for linear
> regression models specified without an intercept?
> 
> example model:
> summary(lm(y ~ 0 + x))
> 
> This gives too low p-values and too high R squared. Is there a way to
> correct it? Or should I specify with intercept to get the correct values?

They are already correct. If you want incorrect ones, please specify their definition...


> Thank you in advance!
> 
> Wojtek Musial
> -- 
> View this message in context: http://r.789695.n4.nabble.com/Correct-statistical-inference-for-linear-regression-models-without-intercept-in-R-tp2295193p2295193.html
> Sent from the R help mailing list archive at Nabble.com.
> 
> ______________________________________________
> 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.

-- 
Peter Dalgaard
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com