compar.gee {ape} | R Documentation |
This function performs the comparative analysis using generalized estimating equations as described by Paradis and Claude (2002).
compar.gee(formula, data = NULL, family = "gaussian", phy, scale.fix = FALSE, scale.value = 1)
formula |
a formula giving the model to be fitted. |
data |
the name of the data frame where the variables in
formula are to be found; by default, the variables are looked
for in the global environment. |
family |
a character string specifying the distribution assumed
for the response; by default a Gaussian distribution (with link
identity) is assumed (see ?family for details on specifying
the distribution, and on changing the link function). |
phy |
an object of class "phylo" . |
scale.fix |
logical, indicates whether the scale parameter should be fixed (TRUE) or estimated (FALSE, the default). |
scale.value |
if scale.fix = TRUE , gives the value for the
scale (default: scale.value = 1 ). |
If a data frame is specified for the argument data
and that
data frame has rownames, then its values are matched to the tip labels
of phy
, otherwise its values are taken to be in the same order
than the tip labels of phy
.
If data = NULL
, then it is assumed that the variables are in
the same order than the tip labels of phy
.
an object of class "compar.gee" with the following components:
call |
the function call, including the formula. |
nobs |
the number of observations. |
coefficients |
the estimated coefficients (or regression parameters). |
residuals |
the regression residuals. |
family |
a character string, the distribution assumed for the response. |
link |
a character string, the link function used for the mean function. |
scale |
the scale (or dispersion parameter). |
W |
the variance-covariance matrix of the estimated coefficients. |
dfP |
the phylogenetic degrees of freedom (see Paradis and Claude for details on this). |
Emmanuel Paradis paradis@isem.univ-montp2.fr
Paradis, E. and Claude J. (2002) Analysis of comparative data using generalized estimating equations. Journal of theoretical Biology, 216, 000–000.
### The example in Phylip 3.5c (originally from Lynch 1991) ### (the same analysis than in help(pic)...) cat("((((Homo:0.21,Pongo:0.21):0.28,", "Macaca:0.49):0.13,Ateles:0.62):0.38,Galago:1.00);", file = "ex.tre", sep = "\n") tree.primates <- read.tree("ex.tre") X <- c(4.09434, 3.61092, 2.37024, 2.02815, -1.46968) Y <- c(4.74493, 3.33220, 3.36730, 2.89037, 2.30259) ### Both regressions... the results are quite close to those obtained ### with pic(). compar.gee(X ~ Y, phy = tree.primates) compar.gee(Y ~ X, phy = tree.primates) ### Now do the GEE regressions through the origin: the results are quite ### different! compar.gee(X ~ Y - 1, phy = tree.primates) compar.gee(Y ~ X - 1, phy = tree.primates) unlink("ex.tre") # delete the file "ex.tre"