corrected_tau: Baseline corrected tau

In scan: Single-Case Data Analyses for Single and Multiple Baseline Designs

Baseline corrected tau

Description

Kendall's tau correlation for the dependent variable and the phase variable is calculated after correcting for a baseline trend.

Usage

## S3 method for class 'sc_bctau'
print(x, nice = TRUE, digits = "auto", ...)

## S3 method for class 'sc_bctau'
export(
  object,
  caption = NA,
  footnote = NA,
  filename = NA,
  nice = TRUE,
  round = 2,
  ...
)

corrected_tau(
  data,
  dvar,
  pvar,
  mvar,
  phases = c(1, 2),
  alpha = 0.05,
  continuity = FALSE,
  repeated = FALSE,
  tau_method = c("b", "a")
)

Arguments

x	An object returned by corrected_tau()
nice	If set TRUE (default) output values are rounded and optimized for publication tables.
digits	The minimum number of significant digits to be use. If set to "auto" (default), values are predefined.
...	Further parameters passed to the print function
object	An scdf or an object exported from a scan function.
caption	Character string with table caption. If left NA (default) a caption will be created based on the exported object.
footnote	Character string with table footnote. If left NA (default) a footnote will be created based on the exported object.
filename	String containing the file name. If a filename is given the output will be written to that file.
round	Integer passed to the digits argument used to round values.
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.
phases	A vector of two characters or numbers indicating the two phases that should be compared. E.g., phases = c("A","C") or phases = c(2,4) for comparing the second to the fourth phase. Phases could be combined by providing a list with two elements. E.g., phases = list(A = c(1,3), B = c(2,4)) will compare phases 1 and 3 (as A) against 2 and 4 (as B). Default is phases = c(1,2).
alpha	Sets the p-value at and below which a baseline correction is applied.
continuity	If TRUE applies a continuity correction for calculating p
repeated	If TRUE applies the repeated median method for calculating slope and intercept.
tau_method	Character with values "a" or "b" (default) indicating whether Kendall Tau A or Kendall Tau B is applied.

Details

This method has been proposed by Tarlow (2016). The baseline data are checked for a significant autocorrelation (based on Kendall's Tau). If so, a non-parametric Theil-Sen regression is applied for the baseline data where the dependent values are regressed on the measurement time. The resulting slope information is then used to predict data of the B-phase. The dependent variable is now corrected for this baseline trend and the residuals of the Theil-Sen regression are taken for further calculations. Finally, Kendall's tau is calculated for the dependent variable and the dichotomous phase variable. The function here provides two extensions to this procedure: The more accurate Siegel repeated median regression is applied when repeated = TRUE and a continuity correction is applied when continuity = TRUE.

Functions

• print(sc_bctau): Print results

• export(sc_bctau): Export results as html

References

Tarlow, K. R. (2016). An Improved Rank Correlation Effect Size Statistic for Single-Case Designs: Baseline Corrected Tau. Behavior Modification, 41(4), 427–467. https://doi.org/10.1177/0145445516676750

See Also

Other regression functions: bplm(), hplm(), mplm(), plm(), print.sc_ac(), trend()

Examples

dat <- scdf(c(A = 33,25,17,25,14,13,15, B = 15,16,16,5,7,9,6,5,3,3,8,11,7))
corrected_tau(dat)

scan documentation built on Sept. 11, 2025, 5:12 p.m.