plotLMER.fnc: plot a mer object

Description

Plot partial effects of a (generalized) linear mixed-effects model fit with lmer (compatible with package lme4 version > 1.0).

Usage

plotLMER.fnc(model, xlabel = NA, xlabs = NA, ylabel = NA, 
ylimit = NA, ilabel = NA, fun = NA, pred = NA, control = NA, 
ranefs = NA, n = 100, intr = NA,lockYlim = TRUE, addlines = FALSE, 
withList = FALSE, cexsize = 0.5, linecolor = 1, 
addToExistingPlot = FALSE, verbose = TRUE, ...)

Arguments

model

a mer model object

xlabel

label for X-axis (if other than the variable name in the original model formula)

xlabs

character vector with labels for X-axes in multipanel plot (if other than the variable names in the original model formula); if used, xlabel should not be specified

ylabel

label for Y-axis (if other than the variable name of the dependent variable in the original model formula)

ylimit

range for vertical axis; if not specified, this range will be chosen such that all data points across all subplots, including HPD intervals, will be accommodated

ilabel

label for the interaction shown in the lower right-hand margin of the plot, overriding the original variable name in the model formula

fun

a function to be applied for transforming the dependent variable, if NA, no transformation is applied; for models with family = "binomial", fun is set to plogis by default; this can be disabled by setting fun=function(x)return(x).

pred

character string with name of predictor; if specified, a single plot will produced for the partial effect of this specific predictor

control

a two-element list list(predictor, val) specifying a predictor the value of which has to be set to val in the partial effect plot(s); the predictor name should be exactly as specified in names(model@fixef). It is up to the user to make sure that name and value make sense, the code here hands full 'control' to the user.

ranefs

a four-element list Group, Level, Predictor, specifying a random-effect Group (e.g. Subject), a level (e.g., S10) and a value (e.g., LogFrequency) for which partial effects have to be calibrated.

integer denoting number of points for the plot, chosen at equally spaced intervals across the empirical range of the predictor variable

intr

a list specifying an interaction to be graphed; obligatory arguments are (1) the name of the interaction variable, followed by (2) a vector of values for that variable, followed by (3) the position for interaction labels ('"beg"', '"mid"', or '"end"', or 'NA' if no labels are desired), optionally followed by (4) a list with as first element a vector of colors and as second element a vector of line types. The number of elements in both vectors should match the number of values specified under (2) for the interaction predictor.

lockYlim

logical specifying whether all subplots should have the same range of values for the vertical axis; if TRUE, this range will be chosen to accomodate all fitted values including HDP intervals for all predictors across all plots

addlines

if TRUE, adds line(s) between levels of same factor(s)

withList

logical, if TRUE, a list will be output with all data frames for the subplots

cexsize

character expansion size (cex) for additional information in the plot for interactions

linecolor

color of lines in the plot, by default set to 1 (black)

addToExistingPlot

default FALSE, if set to TRUE, plot will be added to previous plot, but only if pred is specified

verbose

if TRUE (default), effect sizes and default transformations are reported

...

further graphical parameters to be passed down; warning: col, pch, lty and cex will often generate an error as they are internally already fully specified for specialized subplots

Value

A plot is produced on the graphical device.

Details

When no predictor is specified, a series of plots is produced for the partial effects of each predictor. The graphs are shown for the reference level for factors and are adjusted for the median value for the other numerical predicors in the model. Interactions are not shown. The user should set up the appropriate number of subplots on the graphics device before running plotLMER.fnc().

Instead of showing all predictors jointly, plotLMER.fnc() can also be used to plot the partial effect of a specific predictor. When a specific predictor is specified (with pred = ...), a single plot is produced for that predictor. In this case, the intr argument can be used to specify a single second predictor that enters into an interaction with the selected main predictor.

Polynomials have to be fitted with poly(..., degree, raw=TRUE) and restricted cubic splines with rcs() from the rms package.

Note that any MCMC capabilities available in the languageR version of this function are not available in this version.

Examples

Run this code

# NOT RUN {
# see example in LMERConvenienceFunctions help page.
# }