type=pearson
).
The fitted values at level i are obtained by adding together
the population fitted values
(based only on the fixed effects estimates)
and the estimated contributions of the random effects
to the fitted values at grouping levels less or equal to i.
residuals(object, level, type, asList)
glme
,
representing a fitted generalized linear mixed-effects model.
object
.
Level values increase from outermost to innermost grouping,
with level zero corresponding to the population residuals.
Defaults to the highest or innermost level of grouping.
"response"
,
the "raw" residuals (observed - fitted);
"pearson"
, the standardized residuals
(raw residuals divided by the corresponding standard errors);
"normalized"
, the normalized residuals
(standardized residuals pre-multiplied by the inverse square-root
factor of the estimated error correlation matrix);
"deviance"
and
"link"
.
Partial matching of arguments is used,
so only the first character needs to be provided.
Defaults to
"response"
.
TRUE
and a single value is given
in
level
,
the returned object is a list with the residuals split by groups;
else the returned value is either a vector or a data frame,
according to the length of
level
.
Defaults to
FALSE
.
level
,
the returned value is either a list with the residuals split by groups
(
asList=TRUE
) or a vector with the residuals
(
asList=FALSE
);
else, when multiple grouping levels are specified
in
level
,
the returned object is a data frame with columns given by the residuals
at different levels and the grouping factors.
Bates, D. M. and Pinheiro, J. C. (1998). Computational methods for multilevel models. Available in PostScript or PDF formats at http://franz.stat.wisc.edu/pub/NGLME/
fm1 <- glme(resp ~ trt, Clinic, ~ 1 | clinic, family=binomial, disp=0) residuals(fm1, level=0:1, type="d")