plot.powerMM {MCPMod} | R Documentation |
Plot method for powerMM objects
Description
This function plots the result of the powerMM
function call
in a trellis display.
Usage
## S3 method for class 'powerMM'
plot(x, superpose = TRUE, line.at = NULL, models = "all",
summ = NULL, perc = FALSE, xlab = NULL,
ylab = ifelse(perc, "Power (%)", "Power"), ...)
Arguments
x |
A powerMM object, i.e. a matrix with power values for different sample sizes and models |
superpose |
Logical, indicating if lines should be superposed. |
line.at |
A value, or a vector of values, between 0 and 1, to be drawn as horizontal line in the plot (default: not drawn). |
models |
Character determining which of the models should be included in the plot, "all" and "none" are accepted, else names (or numbers) of models. |
summ |
Summaries to be included in plot; by default the mean, the minimum and the maximum value are displayed. |
perc |
Logical indicating if power values should be in percentage. |
xlab |
Label for x-axis. |
ylab |
Label for y-axis. |
... |
Additional arguments for the |
References
Pinheiro, J. C., Bornkamp, B. and Bretz, F. (2006). Design and analysis of dose finding studies combining multiple comparisons and modeling procedures, Journal of Biopharmaceutical Statistics, 16, 639–656
See Also
Examples
## Not run:
# Example from JBS paper
doses <- c(0,10,25,50,100,150)
models <- list(linear = NULL, emax = 25,
logistic = c(50, 10.88111), exponential= 85,
betaMod=matrix(c(0.33,2.31,1.39,1.39), byrow=TRUE, nrow=2))
pM <- powerMM(models, doses, base = 0, maxEff = 0.4, sigma = 1,
lower = 10, upper = 100, step = 20, scal = 200)
pM
plot(pM)
plot(pM, line.at = 0.8, model = c("emax", "linear"), summ = "mean")
plot(pM, line.at = 0.8, model = "none", summ = c("median", "min"))
## End(Not run)