Serge-?tienne Parent, ing., Ph.D.
Professeur adjoint
D?partement des sols et de g?nie agroalimentaire
Facult? des sciences de l'agriculture et de l'alimentation
Pavillon Paul-Comtois
2425, rue de l'Agriculture
Local 2301
Qu?bec (Qu?bec) G1V 0A6
Canada
+1 418-656-2131 poste 3798
Le Tue 7 Mar 2017 ? 4:56, Thierry Onkelinx <thierry.onkelinx at inbo.be>
a ?crit :
> Dear Mariano,
>
> The logit transformation will fail in case the damage is 0% or 100%.
> The
> correct distribution for ratios between 0 and 1 is a beta
> distribution.
> When 0 or 1 is present you'll need a zero and/or one-inflated beta
> distribution. This is currently non available in lme4.
> It looks like you measure the damage in steps of 5%. So you use the
> binomial distribution as a workaround. That is: assume that each
> leave has
> 20 'trials' (20 * 5% = 100%), each 5% damage is one successful trial.
>
> glmer(cbind(dam / 5, 20 - dam / 5) ~ treat + day + (1|pair/plant),
> data=gaston, family = binomial)
>
> Best regards,
>
> ir. Thierry Onkelinx
> Instituut voor natuur- en bosonderzoek / Research Institute for
> Nature and
> Forest
> team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
> Kliniekstraat 25
> 1070 Anderlecht
> Belgium
>
> To call in the statistician after the experiment is done may be no
> more
> than asking him to perform a post-mortem examination: he may be able
> to say
> what the experiment died of. ~ Sir Ronald Aylmer Fisher
> The plural of anecdote is not data. ~ Roger Brinner
> The combination of some data and an aching desire for an answer does
> not
> ensure that a reasonable answer can be extracted from a given body of
> data.
> ~ John Tukey
>
> 2017-03-06 21:17 GMT+01:00 Mariano Devoto <mdevoto at agro.uba.ar>:
>
>> Hello again. This is a query which follows up on the very useful
>> answer
>> provided by Drew Tyre who suggested creating new variables and
>> adding the
>> random term you'll see in the model below.
>> Quick reminder: the analysis aims at understanding how the presence
>> of
>> "bodyguard" ants regulates leaf damage caused by lepidopteran
>> herbivores on
>> a focal plant species.
>> For this, I set up fourteen pairs of plants in a nature reserve and
>> then
>> assigned each plant in each pair to one of two treatments, either
>> "with
>> ants" or "without ants", by applying a physical barrier at the base
>> of the
>> plant.
>> In the following nine weeks I measured four response variables once
>> a week
>> on a subsample of ten randomly chosen leaves of each plant. I thus
>> have
>> nine repeated measures on each plant.
>>
>> >From analyses done over the weekend I know excluding ants from the
>> plants
>> (variable "treat" in the dataset) has a positive effect on the
>> number of
>> butterfly eggs and larvae found on plants.
>> Now I want to know if this results in a reduced damage to the leafs
>> (variable "dam" in the data set), which is measured as the
>> percentage of
>> the area eaten by herbivores.
>>
>> My response variables are:
>> ants: number of ants (this was measured just to check the physical
>> barrier
>> had worked OK)
>> eggs: number of butterfly eggs
>> larve: number of butterfly larvae
>> dam: percent leaf damage (percentage eaten by larvae)
>>
>> My explanatory variables are:
>> treat: treatment (two levels: "con" and "sin" mean with and without
>> ants,
>> respectively)
>> pair: plant pair
>> date
>>
>> #I provide a workable example below
>> require(lme4); require(tidyverse); require(lubridate)
>>
>> #read data from Google drive
>> id <- "0Bzd8I1jr8z_iU0h6R0hxaElseDA" # google file ID
>> gaston <- read.table(sprintf("
>> https://docs.google.com/uc?id=%s&export=download", id), head=T)
>>
>> #create variables following suggestion by Drew Tyre
>> gaston <- mutate(gaston,
>> plant = paste0(pair,treat),
>> date = dmy(date),
>> day = as.numeric((date - min(date))))
>>
>> #After a few hours of scavenging through books, articles, blogs and
>> R-lists
>> I ended up with the following model which turns the % damage into a
>> proportion and then logit transforms it so I can use lmer.
>>
>> M1 <- lmer(logit(dam/100) ~ treat + day + (1|pair/plant),
>> data=gaston)
>> summary(M1)
>>
>> #Am I headed in the right direction? Any advice would be greatly
>> appreciated.
>>
>> Best,
>>
>> Mariano
>>
>> *Dr. Mariano Devoto*
>>
>> Profesor Adjunto - C?tedra de Bot?nica General, Facultad de
>> Agronom?a de la
>> UBA
>> Investigador Adjunto del CONICET
>>
>> Av. San Mart?n 4453 - C1417DSE - C. A. de Buenos Aires - Argentina
>> +5411 4524-8069
>> http://www.agro.uba.ar/users/mdevoto/
>>
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>>
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