Hello dear all, I am unable to understand why when I run the following three lines:
set.seed(4254) > a <- data.frame(y = rnorm(40), x=ordered(sample(1:5, 40, T))) > summary(lm(y ~ x, a)) The output I get includes factor levels which are not relevant to what I am actually using: Call: > lm(formula = y ~ x, data = a) > Residuals: > Min 1Q Median 3Q Max > -1.4096 -0.6400 -0.1244 0.5886 2.1891 > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) -0.03276 0.15169 -0.216 0.830 > x.L -0.28968 0.33866 -0.855 0.398 > x.Q -0.38813 0.33851 -1.147 0.259 > x.C -0.27183 0.34027 -0.799 0.430 > x^4 0.25993 0.33935 0.766 0.449 > Residual standard error: 0.9564 on 35 degrees of freedom > Multiple R-squared: 0.08571, Adjusted R-squared: -0.01878 > F-statistic: 0.8202 on 4 and 35 DF, p-value: 0.5211 I am guessing that this is having something to do with the contrast matrix that is used, but this is not clear to me. Can anyone suggest a good read, or an explanation? Thanks. ----------------Contact Details:------------------------------------------------------- Contact me: tal.gal...@gmail.com | 972-52-7275845 Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | www.r-statistics.com (English) ---------------------------------------------------------------------------------------------- [[alternative HTML version deleted]] ______________________________________________ R-help@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.