pairs.lme {nlme} | R Documentation

## Pairs Plot of an lme Object

### Description

Diagnostic plots for the linear mixed-effects fit are obtained. The `form` argument gives considerable flexibility in the type of plot specification. A conditioning expression (on the right side of a `|` operator) always implies that different panels are used for each level of the conditioning factor, according to a Trellis display. The expression on the right hand side of the formula, before a `|` operator, must evaluate to a data frame with at least two columns. If the data frame has two columns, a scatter plot of the two variables is displayed (the Trellis function `xyplot` is used). Otherwise, if more than two columns are present, a scatter plot matrix with pairwise scatter plots of the columns in the data frame is displayed (the Trellis function `splom` is used).

### Usage

    ## S3 method for class 'lme':
    pairs(x, form, label, id, idLabels, grid, ...)

### Arguments

`x` | an object inheriting from class `lme`, representing a fitted linear mixed-effects model.
`form` | an optional one-sided formula specifying the desired type of plot. Any variable present in the original data frame used to obtain `x` can be referenced. In addition, `x` itself can be referenced in the formula using the symbol `"."`. Conditional expressions on the right of a `|` operator can be used to define separate panels in a Trellis display. The expression on the right hand side of `form`, and to the left of the `|` operator, must evaluate to a data frame with at least two columns. Default is `~ coef(.)` , corresponding to a pairs plot of the coefficients evaluated at the innermost level of nesting.
`label` | an optional character vector of labels for the variables in the pairs plot.
`id` | an optional numeric value, or one-sided formula. If given as a value, it is used as a significance level for an outlier test based on the Mahalanobis distances of the estimated random effects. Groups with random effects distances greater than the 1-value percentile of the appropriate chi-square distribution are identified in the plot using `idLabels`. If given as a one-sided formula, its right hand side must evaluate to a logical, integer, or character vector which is used to identify points in the plot. If missing, no points are identified.
`idLabels` | an optional vector, or one-sided formula. If given as a vector, it is converted to character and used to label the points identified according to `id`. If given as a one-sided formula, its right hand side must evaluate to a vector which is converted to character and used to label the identified points. Default is the innermost grouping factor.
`grid` | an optional logical value indicating whether a grid should be added to plot. Default is `FALSE`.
`...` | optional arguments passed to the Trellis plot function.

### Value

a diagnostic Trellis plot.

### Author(s)

Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu

### See Also

`lme`, `pairs.compareFits`, `pairs.lmList`, `xyplot`, `splom`

### Examples

    fm1 <- lme(distance ~ age, Orthodont, random = ~ age | Subject)
    # scatter plot of coefficients by gender, identifying unusual subjects
    pairs(fm1, ~coef(., augFrame = TRUE) | Sex, id = 0.1, adj = -0.5)
    # scatter plot of estimated random effects
    ## Not run:
    pairs(fm1, ~ranef(.))
    ## End(Not run)

[Package nlme version 3.1-83 Index]