Re: [R-sig-eco] Output for interactions in models that do not include all main effects
On 04/03/2012 11:31 PM, Kristen Gorman wrote: Dear all, I have R code to run AIC including multi-model inference. I am running into a problem in calling the output from models where both parameters in an interaction are not included as main effects. Why would you want to do that? Why would you (for example) expect the average of the Rlipid slope to be zero if the slope varies with the value of RFGinit? Does this make sense? (this is the sort of thing that makes statisticians splutter into their tea when they see someone do it: it rarely makes sense. Well, unless you have nested effects - which you don't have here- where the interaction is the nested effect) if you respect marginality, there won't be a problem because the main effect is always included. If you really want to include interactions without main effects, you can either write the formula by hand, using paste(): something=Rlipid form = paste(Slipid ~ , something, + RFGinit:, something, sep=) lm(form, data = DataSet) and then work out how to get the order. Or you could try using update(): mod1 = lm(formula = Slipid ~ RFGinit*Rlipid, data = DataSet) mod2=update(mod1, . ~ . -RFGinit) HTH Bob In R, the interaction will be called depending on the parameter that was used as the only main effect in the model. So, I end up generating 2 different interactions (e.g., Rlipid:RFGinit vs RFGinit:Rlipid) that are actually the same. This becomes a problem in the remaining R code that requires weighted and summed values for the parameter and SE estimates. Thus, I would like to call the interaction consistently across models. See the following code: -- lm(formula = Slipid ~ Rlipid + RFGinit:Rlipid, data = DataSet) Residuals: Min 1Q Median 3Q Max -74.075 -19.047 7.233 20.445 45.391 Coefficients: Estimate Std. Error t value Pr(|t|) (Intercept)120.338475.30405 22.6882e-16 *** Rlipid 0.304930.23615 1.2910.202 Rlipid:RFGinit -0.020990.01773 -1.1840.241 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 30.88 on 60 degrees of freedom Multiple R-squared: 0.02721,Adjusted R-squared: -0.005221 F-statistic: 0.839 on 2 and 60 DF, p-value: 0.4372 lm(formula = Slipid ~ RFGinit + Rlipid:RFGinit, data = DataSet) Residuals: Min 1Q Median 3QMax -76.35 -21.63 7.09 22.46 45.71 Coefficients: Estimate Std. Error t value Pr(|t|) (Intercept)131.028546 8.717104 15.0312e-16 *** RFGinit -0.933483 0.742083 -1.2580.213 RFGinit:Rlipid 0.003926 0.009283 0.4230.674 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 30.9 on 60 degrees of freedom Multiple R-squared: 0.02586,Adjusted R-squared: -0.00661 F-statistic: 0.7964 on 2 and 60 DF, p-value: 0.4556 -- Is there a way to tell R to call the interaction based on alphabetical order of the 2 interaction terms and not based on the term that was used as a main effect? Thanks very much for any insight. Kristen Gorman ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology -- Bob O'Hara Biodiversity and Climate Research Centre Senckenberganlage 25 D-60325 Frankfurt am Main, Germany Tel: +49 69 798 40226 Mobile: +49 1515 888 5440 WWW: http://www.bik-f.de/root/index.php?page_id=219 Blog: http://blogs.nature.com/boboh Journal of Negative Results - EEB: www.jnr-eeb.org ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
[R-sig-eco] Output for interactions in models that do not include all main effects
Dear all, I have R code to run AIC including multi-model inference. I am running into a problem in calling the output from models where both parameters in an interaction are not included as main effects. In R, the interaction will be called depending on the parameter that was used as the only main effect in the model. So, I end up generating 2 different interactions (e.g., Rlipid:RFGinit vs RFGinit:Rlipid) that are actually the same. This becomes a problem in the remaining R code that requires weighted and summed values for the parameter and SE estimates. Thus, I would like to call the interaction consistently across models. See the following code: -- lm(formula = Slipid ~ Rlipid + RFGinit:Rlipid, data = DataSet) Residuals: Min 1Q Median 3Q Max -74.075 -19.047 7.233 20.445 45.391 Coefficients: Estimate Std. Error t value Pr(|t|) (Intercept)120.338475.30405 22.688 2e-16 *** Rlipid 0.304930.23615 1.2910.202 Rlipid:RFGinit -0.020990.01773 -1.1840.241 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 30.88 on 60 degrees of freedom Multiple R-squared: 0.02721,Adjusted R-squared: -0.005221 F-statistic: 0.839 on 2 and 60 DF, p-value: 0.4372 lm(formula = Slipid ~ RFGinit + Rlipid:RFGinit, data = DataSet) Residuals: Min 1Q Median 3QMax -76.35 -21.63 7.09 22.46 45.71 Coefficients: Estimate Std. Error t value Pr(|t|) (Intercept)131.028546 8.717104 15.031 2e-16 *** RFGinit -0.933483 0.742083 -1.2580.213 RFGinit:Rlipid 0.003926 0.009283 0.4230.674 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 30.9 on 60 degrees of freedom Multiple R-squared: 0.02586,Adjusted R-squared: -0.00661 F-statistic: 0.7964 on 2 and 60 DF, p-value: 0.4556 -- Is there a way to tell R to call the interaction based on alphabetical order of the 2 interaction terms and not based on the term that was used as a main effect? Thanks very much for any insight. Kristen Gorman ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
Re: [R-sig-eco] Output for interactions in models that do not include all main effects
Maybe your solution can be found here: http://cran.r-project.org/doc/FAQ/R-FAQ.html#Why-does-the-output-from-anova_0028_0029-depend-on-the-order-of-factors-in-the-model_003f 2012/4/3 Kristen Gorman kgor...@sfu.ca Dear all, I have R code to run AIC including multi-model inference. I am running into a problem in calling the output from models where both parameters in an interaction are not included as main effects. In R, the interaction will be called depending on the parameter that was used as the only main effect in the model. So, I end up generating 2 different interactions (e.g., Rlipid:RFGinit vs RFGinit:Rlipid) that are actually the same. This becomes a problem in the remaining R code that requires weighted and summed values for the parameter and SE estimates. Thus, I would like to call the interaction consistently across models. See the following code: -- lm(formula = Slipid ~ Rlipid + RFGinit:Rlipid, data = DataSet) Residuals: Min 1Q Median 3Q Max -74.075 -19.047 7.233 20.445 45.391 Coefficients: Estimate Std. Error t value Pr(|t|) (Intercept)120.338475.30405 22.688 2e-16 *** Rlipid 0.304930.23615 1.2910.202 Rlipid:RFGinit -0.020990.01773 -1.1840.241 --- Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 Residual standard error: 30.88 on 60 degrees of freedom Multiple R-squared: 0.02721,Adjusted R-squared: -0.005221 F-statistic: 0.839 on 2 and 60 DF, p-value: 0.4372 lm(formula = Slipid ~ RFGinit + Rlipid:RFGinit, data = DataSet) Residuals: Min 1Q Median 3QMax -76.35 -21.63 7.09 22.46 45.71 Coefficients: Estimate Std. Error t value Pr(|t|) (Intercept)131.028546 8.717104 15.031 2e-16 *** RFGinit -0.933483 0.742083 -1.2580.213 RFGinit:Rlipid 0.003926 0.009283 0.4230.674 --- Signif. codes: 0 *** 0.001 ** 0.01 * 0.05 . 0.1 1 Residual standard error: 30.9 on 60 degrees of freedom Multiple R-squared: 0.02586,Adjusted R-squared: -0.00661 F-statistic: 0.7964 on 2 and 60 DF, p-value: 0.4556 -- Is there a way to tell R to call the interaction based on alphabetical order of the 2 interaction terms and not based on the term that was used as a main effect? Thanks very much for any insight. Kristen Gorman ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology -- Currículo: http://lattes.cnpq.br/7541377569511492 [[alternative HTML version deleted]] ___ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
