gamlss: par.plot – R documentation

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par.plot

A function to plot parallel plot for repeated measurement data

Description

This function can be used to plot parallel plots for each individual in a repeated measurement study. It is based on the coplot() function of R.

Usage

par.plot(formula = NULL, data = NULL, subjects = NULL, 
          color = TRUE, show.given = TRUE, ...)

Arguments

`formula`	a formula describing the form of conditioning plot. A formula of the form `y ~ x \| a` indicates that plots of `y` versus `x` should be produced conditional on the variable `a`. A formula of the form `y ~ x\| a * b` indicates that plots of `y` versus `x` should be produced conditional on the two variables `a` and `b`.
`data`	a data frame containing values for any variables in the formula. This argument is compulsory.
`subjects`	a factor which distinguish between the individual participants
`color`	whether the parallel plot are shown in colour, `color=TRUE` (the default) or not `color=FALSE`
`show.given`	logical (possibly of length 2 for 2 conditioning variables): should conditioning plots be shown for the corresponding conditioning variables (default 'TRUE')
`...`	for extra arguments

Value

It returns a plot.

Note

Note that similar plot can be fount in the library nlme by Pinheiro and Bates

Author(s)

Mikis Stasinopoulos d.stasinopoulos@londonmet.ac.uk

References

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), App. Statist., 54, part 3, pp 507-554.

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in https://www.gamlss.com/.

Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, https://www.jstatsoft.org/v23/i07/.

Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.

(see also https://www.gamlss.com/).

Examples

library(nlme)
data(Orthodont)
par.plot(distance~age,data=Orthodont,subject=Subject)
par.plot(distance~age|Sex,data=Orthodont,subject=Subject)
par.plot(distance~age|Subject,data=Orthodont,subject=Subject,show.given=FALSE)

gamlss

Generalised Additive Models for Location Scale and Shape

v5.3-4

GPL-2 | GPL-3

Authors

Mikis Stasinopoulos [aut, cre, cph], Bob Rigby [aut], Vlasios Voudouris [ctb], Calliope Akantziliotou [ctb], Marco Enea [ctb], Daniil Kiose [ctb]

Initial release

2021-03-31