Displaying 5 results from an estimated 5 matches for "facb".
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2006 Jan 26
1
How to make two side-by side trellis plots same size
...t workaround uses a guessed factor.
Any way to improve this?
Dieter
library(lattice)
n1 = 20
# I cannot rbind df1 and df2, because the x-dimensions are
# different and must be scaled individually
df1 = data.frame(y=rnorm(4*n1),x=rep(1:n1,4),
facA=rep(c("A","B"),each=2*n1),facB=rep(c("C","D"),each=n1))
# I add a dummy facB here, to make sure panels have same structure
df2 = data.frame(y=rnorm(2*n1),z=rep(100*(1:n1),2),
facA=rep(c("A","B"),each=n1),facB="C")
# Note: aspect = 1 is required
p1 = xyplot(y~x|facA*facB,data...
2008 Oct 29
0
reporting interactions of factors in linear mixed effects models
Hi,
I have a question about how I should report the results for a linear
mixed effects model where the model includes as predictors three
factors (facA, facB and facC), one of which (facA) interacts with the
other two. facA and facB have two levels and facC has 3 levels. There
are also several other continuous predictors (e.g. varA, varB, varC).
My mixed model is specified with the following formula:
model <- lmer(RT~ facA*facB*facC - facA:facB:facC...
2004 Sep 09
2
Skipping panels in Lattice
...of previous r-help queries
and the example given in Pinheiro & Bates. But I must be missing something...
Here's an example (running R 1.9.1 on Win2k):
# generate some data
df1 <- data.frame(expand.grid(obsnum=seq(1, 15, 1), faca=c("A1", "A2", "A3"),
facb=c("B1","B2", "B3", "B4"), facc=c("C1","C2")), dv=rpois(15*3*4*2,10))
# now get rid of the cell B4 & C1 to simulate a missing treatment combination
df2 <- df1[df1$facb !="B4" | df1$facc !="C1", ]
# plain vanill...
2006 Feb 21
2
indexing within panels in xyplot
...idea:
---<---------------cut here---------------start-------------->---
toydf <- expand.grid(1:100, c("A", "B"),
c("pop1", "pop2", "pop3", "pop4", "pop5"))
toydf <- data.frame(facA = toydf[[3]], facB = toydf[[2]],
x = toydf[[1]], y = rnorm(1000))
xyplot(y ~ x | facA, groups = facB, data = toydf,
panel.groups = function(x, y, subscripts, ...) {
panel.xyplot(x, y, ...)
lindx <- which(y[subscripts] == max(y[subscripts], na.rm = TRUE))
xleft...
2010 Jun 30
1
Interpretation of gam intercept parameter
Dear All:
I apologize for asking such an elementary question, but I could not find an adequate response on line. I am hoping to receive some help with the interpretation of the Intercept coefficient in the gam model below.
I1 through I3 are dummy coded "Item difficulty" parameters in a data set that includes 4 items. If the Intercept is the value of Y when all other terms are 0, am I