how to test the random factor effect in lme
This post https://stat.ethz.ch/pipermail/r-sig-mixed-models/2009q1/001819.html may help you understand why the standard p-values in some cases are not the right thing to do and what one alternative is.
On Tue, Feb 14, 2012 at 3:36 PM, Xiang Gao <xianggao2006 at gmail.com> wrote:
Hi I am working on a Nested one-way ANOVA. I don't know how to implement R code to test the significance of the random factor My R code so far can only test the fixed factor : anova(lme(PCB~Area,random=~1|Sites, data = PCBdata)) ? ? ? ? ? ?numDF denDF ? F-value p-value (Intercept) ? ? 1 ? ?12 1841.7845 ?<.0001 Area ? ? ? ? ? ? ?1 ? ? 4 ? ?4.9846 ?0.0894 Here is my data and my hand calculation.
PCBdata
? Area Sites PCB 1 ? ? A ? ? 1 ?18 2 ? ? A ? ? 1 ?16 3 ? ? A ? ? 1 ?16 4 ? ? A ? ? 2 ?19 5 ? ? A ? ? 2 ?20 6 ? ? A ? ? 2 ?19 7 ? ? A ? ? 3 ?18 8 ? ? A ? ? 3 ?18 9 ? ? A ? ? 3 ?20 10 ? ?B ? ? 4 ?21 11 ? ?B ? ? 4 ?20 12 ? ?B ? ? 4 ?18 13 ? ?B ? ? 5 ?19 14 ? ?B ? ? 5 ?20 15 ? ?B ? ? 5 ?21 16 ? ?B ? ? 6 ?19 17 ? ?B ? ? 6 ?23 18 ? ?B ? ? 6 ?21 By hand calculation, the result should be: Source ?SS ? ? ?DF ? ? ?MS Areas ? ? ?18.00 ?1 ? ?18.00 Sites ? ? ? ?14.44 ?4 ? ?3.61 Error ? ? ? ?20.67 ?12 ?1.72 Total ? ? ? ? ? 53.11 ? 17 ? --- MSareas/MSsites = 4.99 --- matching the R output MSsites/MSE = 2.10 Conclusion is that Neither of Areas nor Sites make differences. My R code so far can only test the fixed effect : anova(lme(PCB~Area,random=~1|Sites, data = PCBdata)) ? ? ? ? ? ?numDF denDF ? F-value p-value (Intercept) ? ? 1 ? ?12 1841.7845 ?<.0001 Area ? ? ? ? ? ? ?1 ? ? 4 ? ?4.9846 ?0.0894 -- Xiang Gao, Ph.D. Department of Biology University of North Texas
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