LenthPlot {BsMD}R Documentation

Lenth's Plot of Effects


Plot of the factor effects with significance levels based on robust estimation of contrast standard errors.


LenthPlot(obj, alpha = 0.05, plt = TRUE, limits = TRUE,
    xlab = "factors", ylab = "effects", faclab = NULL, cex.fac = par("cex.lab"),
    cex.axis=par("cex.axis"), adj = 1, ...)



object of class lm or vector with the factor effects.


numeric. Significance level used for the margin of error (ME) and simultaneous margin of error (SME). See Lenth(1989).


logical. If TRUE, a spikes plot with the factor effects is displayed. Otherwise, no plot is produced.


logical. If TRUE ME and SME limits are displayed and labeled.


character string. Used to label the x-axis. "factors" as default.


character string. Used to label the y-axis. "effects" as default.


list with components idx (numeric vector) and lab (character vector). The idx entries of effects vector (taken from obj) are labelled as lab. The rest of the effect names are blanked. If NULL all factors are labelled using the coefficients' name.


numeric. Character size used for the factor labels.


numeric. Character size used for the axis.


numeric between 0 and 1. Determines where to place the "ME" (margin of error) and the "SME" (simultaneous margin of error) labels (character size of 0.9*cex.axis). 0 for extreme left hand side, 1 for extreme right hand side.


extra parameters passed to plot.


If obj is of class lm, 2*coef(obj) is used as factor effect with the intercept term removed. Otherwise, obj should be a vector with the factor effects. Robust estimate of the contrasts standard error is used to calculate marginal (ME) and simultaneous margin of error (SME) for the provided significance (1 - alpha) level. See Lenth(1989). Spikes are used to display the factor effects. If faclab is NULL, factors are labelled with the effects or coefficient names. Otherwise, those faclab\$idx factors are labelled as faclab\$lab. The rest of the factors are blanked.


The function is called mainly for its side effect. It returns a vector with the value of alpha used, the estimated PSE, ME and SME.


Ernesto Barrios. Extension provided by Kjetil Kjernsmo (2013).


Lenth, R. V. (1989). "Quick and Easy Analysis of Unreplicated Factorials". Technometrics Vol. 31, No. 4. pp. 469–473.

See Also

DanielPlot, BsProb and plot.BsProb


### Tensile Strength Experiment. Taguchi and Wu. 1980
# Data
data(BM86.data,package="BsMD")     # Design matrix and responses
print(BM86.data)    # from Box and Meyer (1986)

# Model Fitting. Box and Meyer (1986) example 2.
tensileStrength.lm <- lm(y2 ~ X1 + X2 + X3 + X4 + X5 + X6 + X7 + X8 + X9 +
                    X10 + X11 + X12 + X13 + X14 + X15, data = BM86.data)
print(coef(tensileStrength.lm)) # Model coefficients

DanielPlot(tensileStrength.lm, main = "Daniel Plot")
LenthPlot(tensileStrength.lm, main = "Lenth's Plot")

[Package BsMD version 2023.920 Index]