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Help with mixed-effects model in lme
3 messages · Jonathan Myers, ONKELINX, Thierry, Dunbar, Michael
Dear Jonathan, I would move the block factor from the ramdom effects to the fixed effects. You have only two levels of that, which can give rather unprecise estimates of the variance of the random effects. Moving block to the fixed effects will cost you only one degree of freedom. So that would not be a big problem. lme(species.richness ~ water*fuel*seed*year + block, random = ~1 |plot) HTH, Thierry ------------------------------------------------------------------------ ---- ir. Thierry Onkelinx Instituut voor natuur- en bosonderzoek / Research Institute for Nature and Forest Cel biometrie, methodologie en kwaliteitszorg / Section biometrics, methodology and quality assurance Gaverstraat 4 9500 Geraardsbergen Belgium tel. + 32 54/436 185 Thierry.Onkelinx at inbo.be www.inbo.be To call in the statistician after the experiment is done may be no more than asking him to perform a post-mortem examination: he may be able to say what the experiment died of. ~ Sir Ronald Aylmer Fisher The plural of anecdote is not data. ~ Roger Brinner The combination of some data and an aching desire for an answer does not ensure that a reasonable answer can be extracted from a given body of data. ~ John Tukey -----Oorspronkelijk bericht----- Van: r-sig-ecology-bounces at r-project.org [mailto:r-sig-ecology-bounces at r-project.org] Namens Jonathan Myers Verzonden: donderdag 17 september 2009 22:52 Aan: r-sig-ecology at r-project.org Onderwerp: [R-sig-eco] Help with mixed-effects model in lme Dear List Members, I am using a mixed-effects model in lme and would like to know whether I am using the proper structure for the random-effects component of the model. My experiment consists of three categorical treatments (fire, water, seed) arranged in a split-plot design. The fire treatment (2 levels) and water treatment (3 levels) were assigned to plots, and the seed treatment (2 levels) was assigned to two subplots within each plot. There are 60 total plots (120 total subplots), divided equally among two large blocks (30 plots per block). I measured species richness in each subplot in three separate years. My goal is to test for main effects of the three treatments, a main effect of year, and all interactions. My current model consists of four factorial fixed effects (fire, water, seed, year) and 1 random effect (block), with plots nested within blocks (to account for the split-plot structure of the experiment): model = lme(species.richness ~ water*fuel*seed*year, random = ~1 | block/plot) The ANOVA output includes two denominator degrees of freedom (denDF): 53 denDF for plot factors (fire, water, fire x water interaction) and 270 denDF for split-plot factors (everything else). I would greatly appreciate feedback as to whether the random-effects component of the model looks appropriate, and if not, how it should be modified. Thanks very much! Cheers, Jonathan ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Jonathan A. Myers Department of Biological Sciences Division of Systematics, Ecology, and Evolution Louisiana State University Baton Rouge, LA 70803 USA E-mail: jmyer19 at lsu.edu Telephone: 225-578-7567 Fax: 225-578-2597 Website: http://www.biology.lsu.edu/labpages/harmslab/jmyers/index.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ _______________________________________________ R-sig-ecology mailing list R-sig-ecology at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology Druk dit bericht a.u.b. niet onnodig af. Please do not print this message unnecessarily. Dit bericht en eventuele bijlagen geven enkel de visie van de schrijver weer en binden het INBO onder geen enkel beding, zolang dit bericht niet bevestigd is door een geldig ondertekend document. The views expressed in this message and any annex are purely those of the writer and may not be regarded as stating an official position of INBO, as long as the message is not confirmed by a duly signed document.
Dear Jonathan A couple of things. If your have treatments applied to sub-plots then it makes sense to have subplot in the random component, i.e. random = ~1|plot/subplot. The other issue you have is ALL interactions. With four factors, this is an awful lot of interactions which together will eat a lot of degrees of freedom which would be better in your residual. In the most extreme case, unless you have replicate samples within each year and sub-plot, you may not even be able to estimate the four way interaction correctly. Are you sure that if you see a one of the three way interactions or the four way interaction that you can explain what it means ecologically? cheers Mike -----Original Message----- From: r-sig-ecology-bounces at r-project.org [mailto:r-sig-ecology-bounces at r-project.org] On Behalf Of Jonathan Myers Sent: 17 September 2009 21:52 To: r-sig-ecology at r-project.org Subject: [R-sig-eco] Help with mixed-effects model in lme Dear List Members, I am using a mixed-effects model in lme and would like to know whether I am using the proper structure for the random-effects component of the model. My experiment consists of three categorical treatments (fire, water, seed) arranged in a split-plot design. The fire treatment (2 levels) and water treatment (3 levels) were assigned to plots, and the seed treatment (2 levels) was assigned to two subplots within each plot. There are 60 total plots (120 total subplots), divided equally among two large blocks (30 plots per block). I measured species richness in each subplot in three separate years. My goal is to test for main effects of the three treatments, a main effect of year, and all interactions. My current model consists of four factorial fixed effects (fire, water, seed, year) and 1 random effect (block), with plots nested within blocks (to account for the split-plot structure of the experiment): model = lme(species.richness ~ water*fuel*seed*year, random = ~1 | block/plot) The ANOVA output includes two denominator degrees of freedom (denDF): 53 denDF for plot factors (fire, water, fire x water interaction) and 270 denDF for split-plot factors (everything else). I would greatly appreciate feedback as to whether the random-effects component of the model looks appropriate, and if not, how it should be modified. Thanks very much! Cheers, Jonathan ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Jonathan A. Myers Department of Biological Sciences Division of Systematics, Ecology, and Evolution Louisiana State University Baton Rouge, LA 70803 USA E-mail: jmyer19 at lsu.edu Telephone: 225-578-7567 Fax: 225-578-2597 Website: http://www.biology.lsu.edu/labpages/harmslab/jmyers/index.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ _______________________________________________ R-sig-ecology mailing list R-sig-ecology at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
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