search for: hpdutra

Displaying 8 results from an estimated 8 matches for "hpdutra".

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2008 Jul 19
1
wroung groupedData despite reading Bates and Pinheiro 3 times
Hi everyone. I am trying to add a formula to my data using the groupedData function. My experiment consists of randomized block design using fruits, vegetation and time as factors. The idea is to see if fruits, vegetation and time explain the abundance of mice. I am using tree density as a covariate. So I tried to fit the following structure to my data. >
2008 Aug 02
4
RE SHAPE package question.
Hi there, I am trying to reorganized my data sets so that it is easy for MARK to read it. Basically I have the encounter histories of 1837 butterflies The data looks like this the first 4 columns are the occasions and the last two code for male and female > t1 t2 t3 t4 M F > 1 0 0 0 1 0 male capture on time1 but not seen on time 2, 3 > and 4 > 1 0 0 0
2008 Jul 06
1
What is my replication unit? Lmer for binary longitudinal data with blocks and two treaments.
First I would like to say thank you for taking the time to read it.Here is my problem. I am running a lmer analysis for binary longitudinal (repeated measures) data. Basically, I manipulated fruits and vegetation to two levels each(present and absent) and I am trying to access how these factors affect mice foraging behavior. The design consist of 12 plots, divided in 3 blocks. So each block
2008 Jul 06
2
Error: cannot use PQL when using lmer
> library(MASS) > attach(bacteria) > table(y) y n y 43 177 > y<-1*(y=="y") > table(y,trt) trt y placebo drug drug+ 0 12 18 13 1 84 44 49 > library(lme4) > model1<-lmer(y~trt+(week|ID),family=binomial,method="PQL") Error in match.arg(method, c("Laplace", "AGQ")) : 'arg' should be one of
2010 Mar 12
1
simple plot in ggplot2, wrong error bars
I was wondering if anyone could help me with this, simple problem. I am essentially following the example on Hadley's webpage (http://had.co.nz/ggplot2/geom_errorbar.html), but it still doesn't make any sense to me. df <- data.frame(trt = factor(c("intact", "intact", "removed", "removed")), coon = c(0.093, 0.06, 0.057, 0.09), group =
2008 Jul 03
0
post hoc comparisons on NLME for longitudinal data
I am trying to fit a non linear mixed effect model but I also want to do a post hoc comparison. My data is binary and consist of recording mice track prints on plates plates in plots that submited to one of 4 different treatments (fruits and vegetation complexity manipulated for two levels each. The design is random blocks repeated measures with presence or absence of track prints as a response
2008 Jul 11
0
GroupedData for three way randomized block. LME
I am trying to fit a formula to my data, but I just can't find the right way to do it. My experiment consists of manipulating FRUITS and VEGETATION to two levels each(intact or removed) on 12 experimental plots. This leaves me with 4 treatment combinations Fruit intact Vegetation removed Fruit int. Veget int. Fruit rem. Veget rem. Fruit rem. Veget. intac those treatements are distributed
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