chameleons: Male Cape Dwarf Chameleons: Measured Traits and Contest...
In BradleyTerry2: Bradley-Terry Models

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Data as used in the study by Stuart-Fox et al. (2006). Physical measurements made on 35 male Cape dwarf chameleons, and the results of 106 inter-male contests.

1	chameleons

A list containing three data frames: chameleons$winner, chameleons$loser and chameleons$predictors.

The chameleons$winner and chameleons$loser data frames each have 106 observations (one per contest) on the following 4 variables:

ID: a factor with 35 levels C01, C02, ... , C43, the identity of the winning (or losing) male in each contest
prev.wins.1: integer (values 0 or 1), did the winner/loser of this contest win in an immediately previous contest?
prev.wins.2: integer (values 0, 1 or 2), how many of his (maximum) previous 2 contests did each male win?
prev.wins.all: integer, how many previous contests has each male won?

The chameleons$predictors data frame has 35 observations, one for each male involved in the contests, on the following 7 variables:

ch.res: numeric, residuals of casque height regression on SVL, i.e. relative height of the bony part on the top of the chameleons' heads
jl.res: numeric, residuals of jaw length regression on SVL
tl.res: numeric, residuals of tail length regression on SVL
mass.res: numeric, residuals of body mass regression on SVL (body condition)
SVL: numeric, snout-vent length (body size)
prop.main: numeric, proportion (arcsin transformed) of area of the flank occupied by the main pink patch on the flank
prop.patch: numeric, proportion (arcsin transformed) of area of the flank occupied by the entire flank patch

The published paper mentions 107 contests, but only 106 contests are included here. Contest number 16 was deleted from the data used to fit the models, because it involved a male whose predictor-variables were incomplete (and it was the only contest involving that lizard, so it is uninformative).

David Firth

The data were obtained by Dr Devi Stuart-Fox, https://devistuartfox.com/, and they are reproduced here with her kind permission.

These are the same data that were used in

Stuart-Fox, D. M., Firth, D., Moussalli, A. and Whiting, M. J. (2006) Multiple signals in chameleon contests: designing and analysing animal contests as a tournament. Animal Behaviour 71, 1263–1271.

##
## Reproduce Table 3 from page 1268 of the above paper:
##
summary(chameleon.model <- BTm(player1 = winner, player2 = loser,
  formula = ~ prev.wins.2 + ch.res[ID] + prop.main[ID] + (1|ID), id = "ID",
  data = chameleons))
head(BTabilities(chameleon.model))
##
## Note that, although a per-chameleon random effect is specified as in the
## above [the term "+ (1|ID)"], the estimated variance for that random
## effect turns out to be zero in this case.  The "prior experience"
## effect ["+ prev.wins.2"] in this analysis has explained most of the
## variation, leaving little for the ID-specific predictors to do.
## Despite that, two of the ID-specific predictors do emerge as
## significant.
##
## Test whether any of the other ID-specific predictors has an effect:
##
add1(chameleon.model, ~ . + jl.res[ID] + tl.res[ID] + mass.res[ID] +
  SVL[ID] + prop.patch[ID])