Plots the results of robustness test
csRobustnessPlot(cs1, cs2, group = NULL, data = NULL,
alternative = "two.sided", conf.level = 0.95, mu = 0,
rscaleSens = c("medium", "wide", "ultrawide"), BF01 = TRUE, ylimz = c(0,
10), sensitivity = FALSE)
a numeric vector of values. If the data
argument is
defined, it can refer to either the column index or the column name of
the data object. See Details
for more information.
a numeric vector of values. If the data
argument is
defined, it can refer to either the column index or the column name of
the data object. See Details
for more information.
column index or name that contain the group data. See
Details
for more information.
numeric matrix or data frame that contains the relevant data.
a character string for the speficication of
the alternative hypothesis. Possible values: "two.sided"
(default),
"greater"
or "less"
.
Interval's confidence level.
a numeric value for the mean value or mean difference.
the scale factor for the prior used in the Bayesian t.test
Should the BF01 be plotted (default is set to TRUE). If FALSE, the BF10 is plotted.
the limits of the y-axis.
Should the sensitivity results be returned (default is set to FALSE).
This plot template is influenced by the JASP way
(https://jasp-stats.org/) for plotting sensitivity analysis results. On the
x-axis or the width of the Cauchy's Scale is plotted. On the y-axis either
BF01 is plotted (if BF01
is set to TRUE) or
BF10 (if BF01
is set to FALSE).
Krypotos, A.-M., Klugkist, I., & Engelhard, I. M. (submitted).Bayesian Hypothesis Testing for Human Threat Conditioning Research: An introduction and the condir R package.
# NOT RUN {
csRobustnessPlot(cs1 = rnorm(n = 100, mean = 10),
cs2 = rnorm(n = 100, mean = 9))
# }
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