nlme: comparePred – R documentation

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comparePred

Compare Predictions

Description

Predicted values are obtained at the specified values of primary for each object. If either object1 or object2 have a grouping structure (i.e. getGroups(object) is not NULL), predicted values are obtained for each group. When both objects determine groups, the group levels must be the same. If other covariates besides primary are used in the prediction model, their group-wise averages (numeric covariates) or most frequent values (categorical covariates) are used to obtain the predicted values. The original observations are also included in the returned object.

Usage

comparePred(object1, object2, primary, minimum, maximum,
    length.out, level, ...)

Arguments

`object1,object2`	fitted model objects, from which predictions can be extracted using the `predict` method.
`primary`	an optional one-sided formula specifying the primary covariate to be used to generate the augmented predictions. By default, if a covariate can be extracted from the data used to generate the objects (using `getCovariate`), it will be used as `primary`.
`minimum`	an optional lower limit for the primary covariate. Defaults to `min(primary)`, after `primary` is evaluated in the `data` used in fitting `object1`.
`maximum`	an optional upper limit for the primary covariate. Defaults to `max(primary)`, after `primary` is evaluated in the `data` used in fitting `object1`.
`length.out`	an optional integer with the number of primary covariate values at which to evaluate the predictions. Defaults to 51.
`level`	an optional integer specifying the desired prediction level. Levels increase from outermost to innermost grouping, with level 0 representing the population (fixed effects) predictions. Only one level can be specified. Defaults to the innermost level.
`...`	some methods for the generic may require additional arguments.

Value

a data frame with four columns representing, respectively, the values of the primary covariate, the groups (if object does not have a grouping structure, all elements will be 1), the predicted or observed values, and the type of value in the third column: the objects' names are used to classify the predicted values and original is used for the observed values. The returned object inherits from classes comparePred and augPred.

Note

This function is generic; method functions can be written to handle specific classes of objects. Classes which already have methods for this function include: gls, lme, and lmList.

Author(s)

José Pinheiro and Douglas Bates bates@stat.wisc.edu

Examples

fm1 <- lme(distance ~ age * Sex, data = Orthodont, random = ~ age)
fm2 <- update(fm1, distance ~ age)
comparePred(fm1, fm2, length.out = 2)

nlme

Linear and Nonlinear Mixed Effects Models

v3.1-152

GPL (>= 2) | file LICENCE

Authors

José Pinheiro [aut] (S version), Douglas Bates [aut] (up to 2007), Saikat DebRoy [ctb] (up to 2002), Deepayan Sarkar [ctb] (up to 2005), EISPACK authors [ctb] (src/rs.f), Siem Heisterkamp [ctb] (Author fixed sigma), Bert Van Willigen [ctb] (Programmer fixed sigma), Johannes Ranke [ctb] (varConstProp()), R-core [aut, cre]

Initial release

2021-02-03