JTRCI: compute and plot Jacobson-Truax or reliable change indices

In AWKruijt/JT-RCI: obtain and plot Jacobson-Truax and reliable change indices

Description

The JTRCI() function is the main function in the JTRCI package. It requires data in wide format (one row per individual) and an estimate of the measure reliability to be given through parameter 'reliability ='.

Usage

JTRCI(data = NA, pre = NA, post = NA, ppid = NA, group = NA,
  reliability = NA, higherIsBetter = F, indextype = "JT",
  JTcrit = "auto", normM = NA, normSD = NA, dysfM = NA,
  dysfSD = NA, plot = T, table = T, ...)

Arguments

data	name of the dataframe containing pre and post data
pre	name of the variable containing data at pre/baseline
post	name of the variable containing data at post
ppid	optional: name of variable containing participant identifying info. If not provided, the function will number participants/rows from 1: number of rows
group	optional: name of variable containing grouping information (e.g. groups 1/2 or experimental/control)
reliability	the value of the reliability estimate
higherIsBetter	logical: if 'higherIsBetter = TRUE' the function assumes that a higher score indicates a better/more healthy/functional state
indextype	choice of "JT" or "RCI". Indicates whether to obtain Jacobson-Truax clinicial significant change or reliable change indices respectively
JTcrit	choice of "auto", "A", "B", "C". Indicates which criterion to use when obtaining Jacobson-Truax indices. When 'JTcrit = "auto"' the function will determine which criteria is likely the best fitting based on the available information (e.g. whether function/dysfunctional norm distributions are provided and whether these distributions overlap or not). When no norm-distributions are provided, 'JTcrit = "auto"' will result in the function using criterion A with the baseline distribution as a proxy for the dysfunctional distribution. Also note that when JTcrit is set to "B" or "C" but their required norm-data inputs are missing, it will output criterion A. When B or C is chosen but the other is a better fit, the function will create a message to inform the user about this.
normM	mean value of the functional/healthy norm distribution
normSD	SD value of the functional/healthy norm distribution
dysfM	mean value of the dysfunctional norm distribution
dysfSD	SD value of the dysfunctional norm distribution
plot	logical, if plot = T a plot will be generated
table	logical, if table = T a table will be generated
...	further arguments to be passed by JTRCI() to the table or plot functions (i.e. you can enter all their parameters directly into JTRCI())

Details

The reliability estimate can be based on norm data. Alternatively, the internal reliability of the measure observed in the current data can be used. In that case, the user will first need to obtain their estimate of choice (alpha, omega, x-random splits splithalf reliability) using the raw (item level) data.

Obtaining reliable change indices is pretty straightforward: run the function with parameter 'indextype = "RCI"'. The JTRCI function's default setting is to obtain Jacobson-Truax indices ('indextype = "JT"'). The function is designed to provide guidance through the various choices a researcher has to make when applying the Jacobson-Truax method. It is recommended to pay attention to the various output messages.

Value

JTRCIdf - a dataframe containing all values and results of the JT or RCI calculations

Examples

JTRCI(data = df, ppid = "ppid", pre = "pre", post = "post",  reliability = .8, indextype = "JT", JTcrit = "auto")

AWKruijt/JT-RCI documentation built on July 9, 2019, 3:54 p.m.