Re: [R] re peated measures
Hi, Thank you. It was that. Julien. Tal Galili wrote: check for missing values. Tal On Wed, Sep 23, 2009 at 3:27 PM, pompon julien.pom...@agr.gc.ca wrote: Hi, I am performing a repeated measures 2-way ANOVA to assess the influence of plant and leaf on aphid fecundity. Fecundity is measured for each aphid on a single leaf. Here is what I typed. wingless - reshape(Wingless, varying = list(c(d0,d1,d2,d3,d4,d5,d6,d7,d8,d9,d10,d11,d12,d13,d14,d15,d16)), v.names = c(fecundity), timevar = time, direction = long) wingless.aov - aov(fecundity ~ factor(time) * clip.cage * plant + Error(factor(id)), data = wingless) summary(wingless.aov) and I obtained Error: factor(id) Df Sum Sq Mean Sq F value Pr(F) factor(time)4 56.789 14.197 3.0613 0.05925 . clip.cage 1 14.149 14.149 3.0509 0.10621 plant 1 3.251 3.251 0.7010 0.41880 factor(time):clip.cage 1 0.304 0.304 0.0655 0.80240 clip.cage:plant 1 17.114 17.114 3.6903 0.07880 . Residuals 12 55.652 4.638 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Error: Within Df Sum Sq Mean Sq F value Pr(F) factor(time) 16 340.83 21.30 11.5222 2e-16 *** factor(time):clip.cage16 27.341.71 0.9242 0.54195 factor(time):plant16 46.362.90 1.5673 0.07783 . factor(time):clip.cage:plant 16 24.501.53 0.8281 0.65304 Residuals255 471.441.85 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 I don't understand why I have the factor(time) inmy between subject results, whereas with a similar set of data I don't. Thank you very much, Julien Pompon. -- View this message in context: http://www.nabble.com/repeated-measures-tp25531110p25531110.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. -- -- My contact information: Tal Galili Phone number: 972-50-3373767 FaceBook: Tal Galili My Blogs: http://www.r-statistics.com/ http://www.talgalili.com http://www.biostatistics.co.il [[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. -- View this message in context: http://www.nabble.com/repeated-measures-tp25531110p25610539.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.
Re: [R] re peated measures
check for missing values. Tal On Wed, Sep 23, 2009 at 3:27 PM, pompon julien.pom...@agr.gc.ca wrote: Hi, I am performing a repeated measures 2-way ANOVA to assess the influence of plant and leaf on aphid fecundity. Fecundity is measured for each aphid on a single leaf. Here is what I typed. wingless - reshape(Wingless, varying = list(c(d0,d1,d2,d3,d4,d5,d6,d7,d8,d9,d10,d11,d12,d13,d14,d15,d16)), v.names = c(fecundity), timevar = time, direction = long) wingless.aov - aov(fecundity ~ factor(time) * clip.cage * plant + Error(factor(id)), data = wingless) summary(wingless.aov) and I obtained Error: factor(id) Df Sum Sq Mean Sq F value Pr(F) factor(time)4 56.789 14.197 3.0613 0.05925 . clip.cage 1 14.149 14.149 3.0509 0.10621 plant 1 3.251 3.251 0.7010 0.41880 factor(time):clip.cage 1 0.304 0.304 0.0655 0.80240 clip.cage:plant 1 17.114 17.114 3.6903 0.07880 . Residuals 12 55.652 4.638 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Error: Within Df Sum Sq Mean Sq F value Pr(F) factor(time) 16 340.83 21.30 11.5222 2e-16 *** factor(time):clip.cage16 27.341.71 0.9242 0.54195 factor(time):plant16 46.362.90 1.5673 0.07783 . factor(time):clip.cage:plant 16 24.501.53 0.8281 0.65304 Residuals255 471.441.85 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 I don't understand why I have the factor(time) inmy between subject results, whereas with a similar set of data I don't. Thank you very much, Julien Pompon. -- View this message in context: http://www.nabble.com/repeated-measures-tp25531110p25531110.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. -- -- My contact information: Tal Galili Phone number: 972-50-3373767 FaceBook: Tal Galili My Blogs: http://www.r-statistics.com/ http://www.talgalili.com http://www.biostatistics.co.il [[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.
[R] re peated measures
Hi, I am performing a repeated measures 2-way ANOVA to assess the influence of plant and leaf on aphid fecundity. Fecundity is measured for each aphid on a single leaf. Here is what I typed. wingless - reshape(Wingless, varying = list(c(d0,d1,d2,d3,d4,d5,d6,d7,d8,d9,d10,d11,d12,d13,d14,d15,d16)), v.names = c(fecundity), timevar = time, direction = long) wingless.aov - aov(fecundity ~ factor(time) * clip.cage * plant + Error(factor(id)), data = wingless) summary(wingless.aov) and I obtained Error: factor(id) Df Sum Sq Mean Sq F value Pr(F) factor(time)4 56.789 14.197 3.0613 0.05925 . clip.cage 1 14.149 14.149 3.0509 0.10621 plant 1 3.251 3.251 0.7010 0.41880 factor(time):clip.cage 1 0.304 0.304 0.0655 0.80240 clip.cage:plant 1 17.114 17.114 3.6903 0.07880 . Residuals 12 55.652 4.638 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Error: Within Df Sum Sq Mean Sq F value Pr(F) factor(time) 16 340.83 21.30 11.5222 2e-16 *** factor(time):clip.cage16 27.341.71 0.9242 0.54195 factor(time):plant16 46.362.90 1.5673 0.07783 . factor(time):clip.cage:plant 16 24.501.53 0.8281 0.65304 Residuals255 471.441.85 --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 I don't understand why I have the factor(time) inmy between subject results, whereas with a similar set of data I don't. Thank you very much, Julien Pompon. -- View this message in context: http://www.nabble.com/repeated-measures-tp25531110p25531110.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.
[R] Re peated Measures (lme?)
Hello, I have a general data analysis question. I recently visited a lab where they are testing a new treatment and they had done the experiment several times on different dates. They repeated the experiment 3-5 times per day. And then for practical reasons they repeated the whole procedure for 5 days.(they wanted a large sample size but practically they couldn't handle more than 5-10 experiments per day). However there might have been some extra variation between different days because the experimenter changed, although same procedure was being followed. Below are the data: Control data: Cday1=c(5,2,5,3,4); Cday2=c(2,1,3,1); Cday3=c(7,6,4,11,10); Cday4=c(5,13,8,4,10,6); Cday5=c(21,8, 5, 5,11); Treatment data: Tday1=c(17,11,25,21,16); Tday2=c(17,7,12); Tday3=c(16,18,4,20,18,25); Tday4=c(17,20,29,17,19); Tday5=c(14,31,28,34); Then they decided to do a paired t.test on the mean per day to measure whether they can detect a difference between the Control and the Treatment, something like: t.test(c(3.8,1.75,7.6,7.66,10),c(18,12,16.83,20.4,26.75),paired=T) But I thought there was something wrong in that procedure, something missing but I couldn't figure out what exactly, my feeling was that they were not capturing the variability in the measurements taken within one day. I thought maybe the solution could be in linear mixed effects models (lme) but could that be used to have some sort of a p-value (or other) to say there is a difference or not between the 2 conditions. Or maybe other procedures? Any ideas? Thanks -- View this message in context: http://www.nabble.com/Repeated-Measures-%28lme-%29-tp16012010p16012010.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.
