scan: trend – R documentation

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trend

Trend analysis for single-cases data

Description

The trendSC function provides an overview of linear trends in single-case data. By default, it gives you the intercept and slope of a linear and a squared regression of measurement-time on scores. Models are computed separately for each phase and across all phases. For a more advanced application, you can add regression models using the R specific formula class.

Usage

trend(data, dvar, pvar, mvar, offset = -1, model = NULL)

trendSC(...)

Arguments

`data`	A single-case data frame. See `scdf` to learn about this format.
`dvar`	Character string with the name of the dependent variable. Defaults to the attributes in the scdf file.
`pvar`	Character string with the name of the phase variable. Defaults to the attributes in the scdf file.
`mvar`	Character string with the name of the measurement time variable. Defaults to the attributes in the scdf file.
`offset`	An offset for the first measurement-time of each phase (MT). If set `offset = 0`, the phase measurement is handled as MT 1. Default is `offset = -1`, setting the first value of MT to 0.
`model`	A string or a list of (named) strings each depicting one regression model. This is a formula expression of the standard R class. The parameters of the model are `values`, `mt` and `phase`.
`...`	Further arguments passed to the function.

Value

`trend`	A matrix containing the results (Intercept, B and beta) of separate regression models for phase A, phase B, and the whole data.
`offset`	Numeric argument from function call (see `Arguments` section).

Author(s)

Juergen Wilbert

Examples

## Compute the linear and squared regression for a random single-case
design <- design_rSC(slope = 0.5)
matthea <- rSC(design)
trendSC(matthea)

## Besides the linear and squared regression models compute two custom models:
## a) a cubic model, and b) the values predicted by the natural logarithm of the
## measurement time.
design <- design_rSC(slope = 0.3)
ben <- rSC(design)
trend(ben, offset = 0, model = c("Cubic" = values ~ I(mt^3), "Log Time" = values ~ log(mt)))

scan

Single-Case Data Analyses for Single and Multiple Baseline Designs

v0.51

GPL

Authors

Juergen Wilbert [aut, cre], Timo Lueke [aut]

Initial release

2021-2-11