BTm finds variables passed to
outcome, player1 etc, so that it works when
run in a separate environment.anova.BTm now respects test and
dispersion arguments for models that inherit from
glm.anova.BTmlist affecting models where ability
is modelled by predictors but ability is estimated separately for some
players due to missing values.glmmPQL affecting models with .
in formula and either offset or weights specified.Diff() that gave warning under R-devel.if statements where argument could be
> 1.qvcalc.BTabilitiespredict.BTm to estimate abilities with non-player abilities
set to non-zero values (for models with a fixed reference
category).qvcalc.BTabilities moved over from package
qvcalc.level in predict.BTm and
predict.glmmPQL is 0 if a fixed effects model has been
fitted, 1 otherwise.BTabilities now works (again) for models where the reference
category is not the first player. Players are kept in their original
order (levels of player1 and player2), but the
abilities are returned with the appropriate reference.
BTabilities now works when ability is modelled by covariates and
some parameters are inestimable (e.g. as in
chameleons.model on ?chameleons).
predict.BTglmmPQL now works for models with
inestimable parameters
BTabilities now returns NA for
unidentified abilitiesplayer1 and player2 factors. Also handle
unidentified coefficients correctly.glmmPQL object BTglmmPQL to avoid
conflict with lme4 (which loads
MASS).BTm so that it is able to find variables when
called inside another function (stackoverflow.com question
14911525).fixed anova.BTmlist to work for models with random
effects
allow models to be specified with no fixed effects
fixed offset argument to work as documented
corrected documentation for citations data
predict.BTm now works for models with no random effects
and handles new individuals with missing values in predictors.BTm.setup causing problems in finding
variables when BTm nested within another function.