texreg (version 1.34)

plotreg: Create coefficient plots from statistical model output

Description

Create coefficient plots from statistical model output.

Usage

plotreg(l, file = NULL, custom.model.names = NULL, 
    custom.coef.names = NULL, custom.note = NULL, 
    override.coef = 0, override.se = 0, override.pval = 0, 
    override.ci.low = 0, override.ci.up = 0, 
    omit.coef = NULL, reorder.coef = NULL, ci.level = 0.95, 
    use.se = FALSE, mfrow = TRUE, xlim = NULL, cex = 2.5, 
    lwd.zerobar = 4, lwd.vbars = 1, lwd.inner = 7, 
    lwd.outer = 5, signif.light = "#fbc9b9", 
    signif.medium = "#f7523a", signif.dark = "#bd0017", 
    insignif.light = "#c5dbe9", insignif.medium = "#5a9ecc", 
    insignif.dark = "#1c5ba6", ...)
coefplot(labels, estimates, lower.inner = NULL, 
    upper.inner = NULL, lower.outer = NULL, 
    upper.outer = NULL, signif.outer = TRUE, 
    xlab = "Coefficients and confidence intervals", 
    main = "Coefficient plot", xlim = NULL, 
    cex = 2.5, lwd.zerobar = 4, lwd.vbars = 1, 
    lwd.inner = 7, lwd.outer = 5, signif.light = "#fbc9b9", 
    signif.medium = "#f7523a", signif.dark = "#bd0017", 
    insignif.light = "#c5dbe9", insignif.medium = "#5a9ecc", 
    insignif.dark = "#1c5ba6", ...)

Arguments

l

A statistical model or a list of statistical models. Lists of models can be specified as l = list(model.1, model.2, ...). Different object types can also be mixed.

file

Using this argument, the resulting table is written to a file rather than to the R prompt. The file name can be specified as a character string. The file extension is automatically recognized. pdf, ps, png, bmp

custom.model.names

A character vector of labels for the models. By default, the models are named Model 1, Model 2, etc. Specifying model.names = c("My name 1", "My name 2") etc. overrides the default behavior.

custom.coef.names

By default, plotreg uses the coefficient names which are stored in the models. The custom.coef.names argument can be used to replace them by other character strings in the order of appearance. For example, if a model shows a tota

custom.note

With this argument, a replacement text for the xlab note below the diagram can be provided. If an empty character object is provided (custom.note = ""), the note will be omitted completely.

override.coef

Set custom values for the coefficients. New coefficients are provided as a list of numeric vectors. The list contains vectors of coefficients for each model. There must be as many vectors of coefficients as there are models. For example, if there are two

override.se

Set custom values for the standard errors. This only has an effect where standard errors are converted into confidence intervals because no other CIs are present. New standard errors are provided as a list of numeric vectors. The list contains vectors of

override.pval

Set custom values for the p values. This only has an effect where standard errors are converted into confidence intervals because no other CIs are present. In this case, significance is derived from the p values rather than the confidence intervals. New p

override.ci.low

Set custom lower confidence interval bounds. This works like the other override arguments, with one exception: if confidence intervals are provided here and in the override.ci.up argument, the standard errors and p values as well as the

override.ci.up

Set custom upper confidence interval bounds. This works like the other override arguments, with one exception: if confidence intervals are provided here and in the override.ci.low argument, the standard errors and p values as well as the

omit.coef

A character string which is used as a regular expression to remove coefficient rows from the table. For example, omit.coef = "group" deletes all coefficient rows from the diagram where the name of the coefficient contains the character sequen

reorder.coef

Reorder the rows of the coefficient block of the resulting table in a custom way. The argument takes a vector of the same length as the number of coefficients. For example, if there are three coefficients, reorder.coef = c(3, 2, 1) will put t

ci.level

If standard errors are converted to confidence intervals (because a model does not natively support CIs), what confidence level should be used for the outer confidence interval? By default, 0.95 is used (i.e., an alpha value of 0.05).

use.se

Use one standard error for the inner horizontal bar and two standard errors from the estimate for the outer horizontal bar (instead of confidence intervals). Only available if standard errors can be extracted from the model using the respective

mfrow

If multiple models are handed over as the l argument, several plots are produced. If mfrow = TRUE is set, multiple diagrams are aligned on the same page. If mfrow = FALSE is set, each diagram per model comes out as a

xlim

Horizontal limits. In the coefplot function, they must be provided as a vector with two numeric, e.g., xlim = c(-5, 5) for displaying a range from -5 to +5. In the plotreg function, they can

lwd.zerobar

Line width of the vertical gray bar at the x value of 0. To remove the line, set lwd.zerobar = 0.

lwd.vbars

Line width of the thin vertical gray bars. To remove them completely, set lwd.vbars = 0.

labels

The names of the model terms. They are arranged on the left axis.

estimates

The coefficients (point estimates) of the model terms. They are depicted as bold dots in the coefficient plot.

lower.inner

The lower bounds of the inner confidence intervals, provided as a vector. Inner CI means more relaxed (lower confidence level, higher alpha) because fewer observations have to fall into the CI, therefore the CI gets smaller.

upper.inner

The upper bounds of the inner confidence intervals, provided as a vector. Inner CI means more relaxed (lower confidence level, higher alpha) because fewer observations have to fall into the CI, therefore the CI gets smaller.

lower.outer

The lower bounds of the outer confidence intervals, provided as a vector. Outer CI means stricter or narrower (higher confidence level, lower alpha) because more observations have to fall into the CI, therefore the CI gets larger.

upper.outer

The upper bounds of the outer confidence intervals, provided as a vector. Outer CI means stricter or narrower (higher confidence level, lower alpha) because more observations have to fall into the CI, therefore the CI gets larger.

signif.outer

Different colors are used for significant estimates and confidence intervals. If signif.outer = TRUE, the outer CIs are used to evaluate significance, otherwise the inner CIs are used.

xlab

The label of the x axis.

main

The main title or heading of the plot.

cex

Size of the point representing the estimate.

lwd.inner

Line width of the inner confidence interval.

lwd.outer

Line width of the outer confidence interval.

signif.light

Color of outer confidence intervals for significant model terms.

signif.medium

Color of inner confidence intervals for significant model terms.

signif.dark

Color of point estimates and labels for significant model terms.

insignif.light

Color of outer confidence intervals for insignificant model terms.

insignif.medium

Color of inner confidence intervals for insignificant model terms.

insignif.dark

Color of point estimates and labels for insignificant model terms.

...

Custom options to be passed on to the extract function or the graphics device. See the help entries of extract and extract-methods for more information.

Details

The coefplot function produces coefficient plots (i.e., forest plots applied to point estimates and confidence intervals). It accepts raw data (the lower and upper bounds of inner and outer confidence intervals as well as the point estimates and their names) as input data. Significant coefficients and intervals can be plotted in a different color.

The plotreg function is a wrapper for the coefplot function and works much like the screenreg, texreg, and htmlreg functions. It accepts a single or multiple statistical models as input and internally extracts the relevant data from the models. If confidence intervals are not defined in the extract method of a statistical model (see extract and extract-methods), the default standard errors are converted to confidence intervals. Most of the arguments work either like in the screenreg, texreg, and htmlreg functions, or they work like in the coefplot function.

See Also

texreg-package extract extract-methods texreg

Examples

#example from the 'lm' help file:
ctl <- c(4.17,5.58,5.18,6.11,4.50,4.61,5.17,4.53,5.33,5.14)
trt <- c(4.81,4.17,4.41,3.59,5.87,3.83,6.03,4.89,4.32,4.69)
group <- gl(2,10,20, labels = c("Ctl","Trt"))
weight <- c(ctl, trt)
lm.D9 <- lm(weight ~ group)
screenreg(lm.D9)  # print model output to the R console
plotreg(lm.D9)    # plot model output as a diagram