Description Usage Arguments Details Value Note Author(s) See Also Examples
View source: R/model.frame.mixmeta.R
These method functions return the model frame and design matrix for meta-analytical models represented in objects of class "mixmeta"
.
1 2 3 4 5 | ## S3 method for class 'mixmeta'
model.frame(formula, ...)
## S3 method for class 'mixmeta'
model.matrix(object, ...)
|
object, formula |
an object of class |
... |
further arguments passed to or from other methods. |
The model frame is produced by mixmeta
when fitting the meta-analytical model, and stored in the mixmeta
object if argument model=TRUE
. Alternatively, the model frame is directly returned from a call to mixmeta
with argument method="model.frame"
. The method function model.frame
simply extracts the saved model frame if available, or otherwise evaluates a call to mixmeta
when method="model.frame"
.
The method function model.matrix
extracts the design matrix for the fixed-effects part of a fitted meta-analytical model. It first extract the model frame by calling model.frame
, and then passes the call to the default method.
Note that the model frame of mixmeta
models consist of terms for both the fixed and random-effects parts, the latter including also the grouping factors. This information can be used to reconstruct the proper model frame or matrix for each part.
These methods functions are similar to those provided for regression objects lm
and lm
.
For model.frame
, a data.frame with special attributes (see the default method model.frame
) and the additional class "data.frame.mixmeta"
.
For model.matrix
, the design matrix used to fit the model.
The reason why these specific method functions are made available for class mixmeta
, and in particular why a new class "data.frame.mixmeta"
has been defined for model frames, lies in the special handling of missing values in multivariate meta-analysis models fitted with mixmeta
. Methods na.omit
and na.exclude
for class "data.frame.mixmeta"
are useful for properly accounting for missing values when fitting these models.
Antonio Gasparrini <antonio.gasparrini@lshtm.ac.uk>
See the default methods model.frame
and model.matrix
. See na.omit
and na.exclude
on the handling of missing values. See mixmeta-package
for an overview of the package and modelling framework.
1 2 3 4 5 6 7 8 9 10 11 12 | # RUN THE MODEL AND SUMMARIZE THE RESULTS
model <- mixmeta(cbind(PD,AL) ~ pubyear, S=berkey98[5:7], data=berkey98,
method="ml")
# MODEL FRAME
model$model
model.frame(model)
update(model, method="model.frame")
class(model.frame(model))
# MODEL MATRIX
model.matrix(model)
|
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