similar to: how to run ANCOVA?

Displaying 20 results from an estimated 10000 matches similar to: "how to run ANCOVA?"

2012 Jul 21
2
car::Anova - Can it be used for ANCOVA with repeated-measures factors.
Dear list, I would like to run an ANCOVA using car::Anova with repeated measures factors, but I can't figure out how to do it. My (between-subjects) covariate always interacts with my within-subject factors. As far as I understand ANCOVA, covariates usually do not interact with the effects of interest but are simply additive (or am I wrong here?). More specifically, I can add a covariate as
2012 Jan 11
2
problems with glht for ancova
I've run an ancova, edadysexo is a factor with 3 levels,and log(lcc) is the covariate (continous variable) I get this results > ancova<-aov(log(peso)~edadysexo*log(lcc)) > summary(ancova) Df Sum Sq Mean Sq F value Pr(>F) edadysexo 2 31.859 15.9294 803.9843 <2e-16 *** log(lcc) 1 11.389 11.3887 574.8081 <2e-16 ***
2007 Nov 15
3
Ancova doesn't return test statistics
Dear all, I'm quite sure that this is a stupid question, but I'll ask anyway. I want to perform an ANCOVA with two continuous factors and three categorical factors. Plant population growth rate (GR) = dependent variable Seed reduction due to herbivory (SR) = continuous explanatory variable Herbivore species (HS, 2 levels) = categorical explanatory variable Population (Pop, 24 levels) =
2009 Feb 10
2
Mixed ANCOVA with between-Ss covariate?
Hi all, I have data from an experiment with 3 independent variables, 2 are within and 1 is between. In addition to the dependent variable, I have a covariate that is a single measure per subject. Below I provide an example generated data set and my approach to implementing the ANCOVA. However the output confuses me; why does the covariate only appear in the first strata? Presumably it should
2007 Jan 09
2
posthoc tests with ANCOVA
dear all, I want to perform a posthoc test for my ANCOVA: a1<-aov(seeds~treatment*length) With summary(glht(a1, linfct = mcp(treatment = "Tukey"))) R tells me: "covariate interactions found -- please choose appropriate contrast" How do I build these contrasts? Ideally, I would like to have the posthoc test for the ANCOVA including a block-effect
2012 Jul 04
2
Difference between two-way ANOVA and (two-way) ANCOVA
Hi! as my subject says I am struggling with the different of a two-way ANOVA and a (two-way) ANCOVA. I found the following examples from this webpage: http://www.statmethods.net/stats/anova.html # One Way Anova (Completely Randomized Design) fit <- aov(y ~ A, data=mydataframe) # Randomized Block Design (B is the blocking factor) fit <- aov(y ~ A + B, data=mydataframe) # Two Way
2008 May 04
4
improvement of Ancova analysis
Dear Helpers, I just started working with R and I'm a bit overloaded with information. My data is from marsupials reindroduced in a area. I have weight(wt), hind foot lenghts(pes) as continues variables and origin and gender as categorial. condition is just the residuals i took from the model. > names(dat1) [1] "wt" "pes" "origin" "gender"
2008 May 25
1
marginality principle / selecting the right type of SS for an interaction hypothesis
Hello, I have a problem with selecting the right type of sums of squares for an ANCOVA for my specific experimental data and hypotheses. I do have a basic understanding of the differences between Type-I, II, and III SSs, have read about the principle of marginality, and read Venable's "Exegeses on Linear Models" (http://www.stats.ox.ac.uk/pub/MASS3/Exegeses.pdf). I am pretty new to
2012 Feb 12
2
ANCOVA post-hoc test
Could you please help me on the following ANCOVA issue? This is a part of my dataset: sampling dist h 1 wi 200 0.8687212 2 wi 200 0.8812909 3 wi 200 0.8267464 4 wi 0 0.8554508 5 wi 0 0.9506721 6 wi 0 0.8112781 7 wi 400 0.8687212 8 wi 400 0.8414646 9 wi 400 0.7601675 10 wi 900 0.6577048 11 wi 900
2011 Dec 11
2
multiple comparison of interaction of ANCOVA
Hi there, The following data is obtained from a long-term experiments. > mydata <- read.table(textConnection(" + y year Trt + 9.37 1993 A + 8.21 1995 A + 8.11 1999 A + 7.22 2007 A + 7.81 2010 A + 10.85 1993 B + 12.83 1995 B + 13.21 1999 B + 13.70 2007 B + 15.15 2010 B + 5.69 1993 C + 5.76 1995 C + 6.39 1999
2008 Dec 09
1
ANCOVA
Hello,   Could you please help me in the following question: I have 16 persons 6 take 0.5 mg, 6 take 0.75 mg and 4 take placebo! Can I use the ANCOVA and t-test in this case? Is it possible in R?   Thank you in advance, Samuel [[alternative HTML version deleted]]
2004 Jan 15
1
nlme vs aov with Error() for an ANCOVA
Hi I compouted a multiple linear regression with repeated measures on one explanatory variable: BOLD peak (blood oxygenation) as dependent variable, and as independent variables I have: -age.group (binaray:young(0)/old(1)) -and task-difficulty measured by means of the reaction-time 'rt'. For 'rt' I have repeated measurements, since each subject did 12 different tasks. -> so
2006 Nov 20
1
Is there any R package to calcualte "Power" for ANCOVA
Dear list members: I searched the R-help for packages to calculate power for an ANCOVA problem I have. I have found power.t.test, power.anova.test. But it seems that I can not found one with ANCOVA. I have two datasetsets with variables: univariate response(one data with continous response and one with 0 and 1), treatment(two levels), covariates(x1,x2,x3). I would appreciate your help. Tony
2006 Jun 02
1
ANCOVA in S-plus/R?
Dear R user: I have a question about doing ANCOVA in S-plus or R. I know that many users use lm to do the regression and check the ANCOVA. But is there a way to get the traditional Table form of the ANCOVA test through S-plus (like what we would get from SPSS or SAS)? The problem I’m interested in is whether or not there is a treatment effect on some medical measurement. I will
2009 Aug 20
1
ANCOVA with defined error terms
I am trying to run an ANCOVA with defined error terms. Thus I have to use AOV and not lm. my response variable is proportion of mice paw prints on track plates. These plates were placed on plots that had vegetation and fruit manipulated to two levels each (present or absent), and were sampled monthly for 14 months (repeated measures). The fully crossed factor design was also blocked. My sample
2012 Nov 06
1
pivot table
Hello, I have a data which looks like below: Some of the patients have multiple diagnosis. ID(200 patients)   Diag (100 unique Diag-200 in general)   Proc (50 uniqe Proc)  DOB (200)   Gender (200)    a                           daig1 b                           diag2 c                            diag1 I want to reformat this data to : ID   diag1 diag 2 diag 3..  diagx   proc1   proc2  
2000 Feb 08
1
Ancova in R?
How to Ancova in R? I know this has got to be an FAQ, because I see it asked in the lists, but I haven't seen an answer to it. I see the R-sm has the ancova thing happening, but I kind of doubt that what I'm trying to do is "smoothing"... -- Pete Hurd phurd at uts.cc.utexas.edu http://www.zo.utexas.edu/research/phurd Section of Integrative Biology, University of Texas, Austin
2010 May 10
1
how to get p-value from ave
Hi there, I checked google for aov. usually one uses summary to see whether the p-value is small. but I want to put aov in my script. how can I get the p-value, (0.1115, 0.6665, 0.6665 in the following example)? thanks YU > datafilename="http://personality-project.org/r/datasets/R.appendix2.data" > data.example2=read.table(datafilename,header=T) > aov.ex2 =
2005 Dec 14
1
ANCOVA & Post-hoc test
Hello, Despite my search, I didn't find a post-hoc test for an ANCOVA. I used the functions aov() and lm() to run the ANCOVA then I tried TukeyHSD() but it didn't work (because of the covariable is a continuous variable?). Furthermore, I would like to plot the adjusted values (i.e. the values of the tested variable taking into account the covariable). Thanks for your help! N. Poulet
2009 Feb 18
2
[package-car:Anova] extracting residuals from Anova for Type II/III Repeated Measures ?
Hello dear R members. I have been learning the Anova syntax in order to perform an SS type III Anova with repeated measures designs (thank you Prof. John Fox!) And another question came up: where/what are the (between/within) residuals for my model? ############ Play code: phase <- factor(rep(c("pretest", "posttest", "followup"), c(5, 5, 5)),