therapyMonitor(dat = NULL, design="AB", statistic="|A-B|", conditionColumn = NULL, variableColumn = NULL, timeColumn = NULL, conditionMoment = NULL, limit=NULL, lines=NULL, ylab=NULL, xlab=NULL, outputFile = NULL, outputFormats = c('svg', 'png'), plotTitle = "therapyMonitor results", plotWidth=25, plotHeight=15)
therapyMonitor.multi(dat = NULL, variableColumn = NULL, conditionColumn = NULL, conditionMoment = NULL, minLevels = 5, outputFiles = FALSE, outputFilePath = getwd(), outputFormats = c('svg', 'png'), silent=FALSE, ...)
getData
function is used to present a
dialog to the user.
pvalue.systematic
in the
SCRT-package
for more information. Note that currently,
this function always assumes an "AB" design; changing this only changes
the way pvalue.systematic
is called.
pvalue.systematic
in the
SCRT-package
for more information. Note that currently,
this function always assumes the "|A-B|" statistic; changing this only
changes the way pvalue.systematic
is called.therapyMonitor
, this must be a single value: the name of the
variable to analyse as dependent variable. For therapyMonitor.multi
,
this can be a vector, in which case all the specified variables are
analysed sequentially. In any case, the variable(s) specified here must
have the 'interval' measurement level (i.e. be roughly continuous). For
therapyMonitor.multi
, if this argument is empty, all variables
are used, provided they have at least minLevels
levels.
pvalue.systematic
).
dat
dataframe to use.
outputFormats
argument.
outputFiles
is TRUE, the path where to store the output files.
therapyMonitor.multi
are passed on to
therapyMonitor
.
This function started as a wrapper to the pvalue.systematic
function in the SCRT-package
, but it now also does some extra
stuff.
### Explore and plot the weight of a chick in the ChickWeight dataset
therapyMonitor(ChickWeight, variableColumn='weight',
conditionMoment=6, lines=1:12);
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