Hello, I am all new here. Thanks for the job done, R really helped me in my thesis lately. However, I am kind of new in statistics, coming from mecanical engineering, and I mostly teached myself with "The R Book", so I may do silly things some time. PLease tell me if you think so.
Anyway, I've just build up a piecewise linear model to fit some data, including some interaction and i am not sure of how to interpret the summary:. here it is: -------------------------------------------------------------------------------- Call: lm(formula = weightedDiff ~ angleNoise + (reflection < Break[xMin]) * reflection + (reflection >= Break[xMin]) * reflection + angleNoise:(reflection < Break[xMin]) * reflection + angleNoise:(reflection >= Break[xMin]) * reflection) Residuals: Min 1Q Median 3Q Max -1.073e-03 -1.749e-04 -5.913e-06 1.650e-04 1.311e-03 Coefficients: (4 not defined because of singularities) Estimate Std. Error (Intercept) 0.0134798 0.0001086 angleNoise 0.0004658 0.0002245 reflection < Break[xMin]TRUE -0.0028766 0.0001236 reflection 0.0316122 0.0014741 reflection >= Break[xMin]TRUE NA NA reflection < Break[xMin]TRUE:reflection 0.0683631 0.0027668 reflection:reflection >= Break[xMin]TRUE NA NA angleNoise:reflection < Break[xMin]TRUE 0.0011158 0.0002548 angleNoise:reflection >= Break[xMin]TRUE NA NA angleNoise:reflection < Break[xMin]FALSE:reflection -0.0055751 0.0030620 angleNoise:reflection < Break[xMin]TRUE:reflection -0.0343745 0.0049164 angleNoise:reflection:reflection >= Break[xMin]TRUE NA NA t value Pr(>|t|) (Intercept) 124.079 < 2e-16 *** angleNoise 2.075 0.0384 * reflection < Break[xMin]TRUE -23.265 < 2e-16 *** reflection 21.445 < 2e-16 *** reflection >= Break[xMin]TRUE NA NA reflection < Break[xMin]TRUE:reflection 24.708 < 2e-16 *** reflection:reflection >= Break[xMin]TRUE NA NA angleNoise:reflection < Break[xMin]TRUE 4.379 1.41e-05 *** angleNoise:reflection >= Break[xMin]TRUE NA NA angleNoise:reflection < Break[xMin]FALSE:reflection -1.821 0.0692 . angleNoise:reflection < Break[xMin]TRUE:reflection -6.992 7.35e-12 *** angleNoise:reflection:reflection >= Break[xMin]TRUE NA NA --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.0002885 on 592 degrees of freedom Multiple R-squared: 0.9666, Adjusted R-squared: 0.9662 F-statistic: 2450 on 7 and 592 DF, p-value: < 2.2e-16 -------------------------------------------------------------------------------------------- Basically, I am really not sure of the meaning of this parameter: angleNoise:reflection < Break[xMin]FALSE:reflection Overall, my interpretation is that reflection is important , angle Noise also but specially when reflection is below the breaking point. Is that correct? well, sorry for the first long post thanks in advance -- View this message in context: http://r.789695.n4.nabble.com/help-interpreting-a-model-summary-tp2546161p2546161.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ 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.