further object specifications (see details), as well as named
parameters that will be passed to
An object of class
"anova" inheriting from class
The columns are as follows:
The residual number of degrees of freedom in the model.
The increase in residual degrees of freedom with respect to the model in the row above.
The adjusted likelihood ratio statistic.
The p-value of the test that the model above is a "significantly better" model as the one in the current row.
The standard method is to compare the fitted model object
object with the
.... Instead of passing the fitted models into
specifications are possible. Note that the types of specifications cannot be
mixed, except between numerics/characters. The type of the second object
supplied determines the algorithm used.
"chantrics" objects: When
supplying two or more
"chantrics" objects, they will be sorted as in
anova.chantrics(). Then, the ALRTS will be computed consecutively between
the two neighbouring models. Note that all models must be nested. For
details refer to
"numeric": If the second
corresponding element in
attr(terms(object1), "term.labels") will be
turned into their corresponding
"character" element and will be handled
"character": If the second object is
"character", then the
"character" objects are
consecutively included in an update formula like
update(object1, . ~ . - object2)
"formula": If the second object is a
the second model will be computed as
Then, the adjusted likelihood ratio test statistic (ALRTS), as described in
Section 3.5 of Chandler and Bate
(2007), is computed by
If a single unnamed object is passed in
..., sequential ANOVA is
R. E. Chandler and S. Bate, Inference for clustered data using the independence loglikelihood, Biometrika, 94 (2007), pp. 167–183. doi: 10.1093/biomet/asm015 .