similar to: comparing ancova models: summary

Hello, all. I've got what is probably a simple question about comparison of models using anova, specifically about the situations in which it's valid. I understand, I think, what's going on when the models are strictly nested (as most are in the demo(lm) examples). My question involves what happens when the models aren't strictly nested. In my particular case, I'm doing

Hello, I am VERY new to R, just picking it up infact. I have got my head around the basics of ANOVA with post hoc tests but I am struggling with regression, especially with ANCOVAs. I have two sets of data, one of type A, one of type B. Both have been placed in a wind tunnel and sampled every week. The co variate is of course the days since the start. An example is day A B 0 10.0 10.0 7 9.0

I'm trying to perform ANCOVAs in R 1.14, on a Mac OS X, but I can't figure out what I am doing wrong. Essentially, I'm testing whether a number of quantitative dental measurements (the response variables in each ANCOVA) show sexual dimorphism (the sexes are the groups) independently of the animal's size (the concomitant variable). I have attached a 13-column matrix as a data

Hi, all. I'm trying to use some linear regression models in which both the dependent and independent variables are measured with some error. To make things worse, while the errors in the dependent variable are uniform, the errors in the independent (or explanatory, or "x") variables can be heteroskedastic. I've been looking at the book _Measurement Error Models_ by Fuller

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

Hello! I have measurements (length and volume) of fish collected in two years. I want to know if the the relationship between length and volume is the same for both years. The number of fish measured is different for each year. I don't know whether lm or aov is more appropriate to use. Here are the two output options: Call: lm(formula = Volume ~ Length * Year) Residuals: Min 1Q

Matthew Wiener <mcw@ln.nimh.nih.gov> writes: > t1 <- data.frame(matrix(rnorm(16), nc=4)) > t1$X1 <- 1 > t1$X2 <- 2 > print(t1) > Error: dim<- length of dims do not match the length of object Well, it is prototype-compatible. Splus 5.3 does likewise. A way out is t1<-data.frame(unclass(t1)) However, we do seem to have a bug in the area: > t1 <-

Matthew Wiener <mcw@ln.nimh.nih.gov> writes: > t1 <- data.frame(matrix(rnorm(16), nc=4)) > t1$X1 <- 1 > t1$X2 <- 2 > print(t1) > Error: dim<- length of dims do not match the length of object Well, it is prototype-compatible. Splus 5.3 does likewise. A way out is t1<-data.frame(unclass(t1)) However, we do seem to have a bug in the area: > t1 <-

Matthew Wiener <mcw@ln.nimh.nih.gov> writes: > > parameters (xxdefun in gram.y calls lang4). The arg count got changed > > from 0.64.2 to 0.65.0 (from 3 to 4) to accommodate the stored source > > attribute. I suppose that a function stored in a saved workspace might > > cause some kind of mess when restored. > > > > If I understand this correctly, it

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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 ***

Hi, what would be a good way of enhancing the ancova function from the HH package when using a 2 factor ANCOVA? The current behaviour for the "ancova" function from package HH is: ---------------------------------------------- | P1 || P1 || P3 || P4 | | PS | <- the lattice strip ---------------------------------------------- | x|| x ||x ||x | |

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

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

I have some data with two categorises plus/minus (p53) and a particular time (Time) and the outcome is a continuous vairable (Result). I set up a maximum model. ancova <- lm(Result~Time*p53) > summary(ancova) .. Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.05919 0.55646 0.106 0.916 Time -0.02134 0.01785 -1.195 0.241 p53plus

I want to run deconvolution of a time series by an impulse or point-spread function through Wiener filter, regularized filter, Lucy-Richardson method, or any other approaches. I searched the CRAN website and the mailing list archive, but could not find any package for such a deconvolution analysis. Does anybody know an existing R function for deconvolution? TIA, Gang

I initially posted this question to one of the StackExchange sites, and they suggested that I repost my problem here. After using ezANOVA as my primary way of specifying mixed ANOVAs, I've hit a stumbling block when it come to adding a covariate to the model. I am using an ANCOVA in order to determine if there is a developmental trajectory in my data; namely, I need to be able to see the

Hi R-Users, I am working with sm.ancova (in the package sm) and I have two problems with the graph, which is automatically generated when sm.ancova() is run. 1-Besides of the fitted lines, the observed data appeared automatically in the graph. I prefer that only fitted lines appear. I check the sm.options, but I could not find the way that the observed data do not appear in the graph. 2-I

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

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