vit {MBESS}R Documentation

Visualize individual trajectories

Description

A function to help visualize individual trajectories in a longitudinal (i.e., analysis of change) context.

Usage

vit(id = "", occasion = "", score = "", Data = NULL, group = NULL, 
subset.ids = NULL, pct.rand = NULL, number.rand = NULL, 
All.in.One = TRUE, ylab = NULL, xlab = NULL, same.scales = TRUE, 
plot.points = TRUE, save.pdf = FALSE, save.eps = FALSE,
 save.jpg = FALSE, file = "", layout = c(3, 3), col = NULL, 
 pch = 16, cex = 0.7, ...)

Arguments

id string variable of the column name of id
occasion string variable of the column name of time variable
score string variable of the column name where the score (i.e., dependent variable) is located
Data data set with named column variables (see above)
group if plotting parameters should be conditional on group membership
subset.ids id values for a selected subset of individuals
pct.rand percentage of random trajectories to be plotted
number.rand number of random trajectories to be plotted
All.in.One should trajectories be in a single or multiple plots
ylab label for the ordinate (i.e., y-axis; see par)
xlab label for the abscissa (i.e., x-axis; see par)
same.scales should the y-axes have the same scales
plot.points should the points be plotted
save.pdf save a pdf file
save.eps save a postscript file
save.jpg save a jpg file
file file name and file path for the graph(s) to save, if file="" a file would be saved in the current working directory
layout define the per-page layout when All.in.One==FALSE
col color(s) of the line(s) and points
pch plotting character(s); see par
cex size of the points (1 is the R default; see par)
... optional plotting specifications

Details

This function makes visualizing individual trajectories simple. Data should be in the "univariate format" (i.e., the same format as lmer and nlme data.)

Value

Returns a plot of individual trajectories with the specifications provided.

Author(s)

Ken Kelley (University of Notre Dame; KKelley@ND.Edu) and Po-Ju Wu (Indiana University; pojwu@indiana.edu)

See Also

par, nlme, vit.fitted,

Examples


data(Gardner.LD)

# Although many options are possible, a simple call to
# 'vit' is of the form:
# vit(id="ID", occasion= "Trial", score= "Score", Data=Gardner.LD)

# Now color is conditional on group membership.
# vit(id="ID", occasion= "Trial", score="Score", Data=Gardner.LD, 
# group="Group")

# Now randomly selects 50
# vit(id="ID", occasion= "Trial", score="Score", Data=Gardner.LD, 
# pct.rand=50, group="Group")

# Specified individuals are plotted (by group)
# vit(id="ID", occasion= "Trial", score="Score", Data=Gardner.LD, 
# subset.ids=c(1, 4, 8, 13, 17, 21), group="Group")

# Now colors for groups are changed .
# vit(id="ID", occasion= "Trial", score="Score", Data=Gardner.LD, 
# group="Group",subset.ids=c(1, 4, 8, 13, 17, 21), col=c("Green", "Blue"))

# Now each individual specified is plotted seperately.
# vit(id="ID", occasion= "Trial", score="Score", Data=Gardner.LD, 
# group="Group",subset.ids=c(1, 4, 8, 13, 17, 21), col=c("Green", "Blue"),
# All.in.One=FALSE)


[Package MBESS version 2.0.0 Index]