Description Usage Arguments Details Value References Examples
View source: R/nonoverlapmeasures.R
Calculates the baselinecorrected Tau index (Tarlow 2017).
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A_data 
vector of numeric data for A phase. Missing values are dropped. 
B_data 
vector of numeric data for B phase. Missing values are dropped. 
condition 
vector identifying the treatment condition for each observation in the series. 
outcome 
vector of outcome data for the entire series. 
baseline_phase 
character string specifying which value of

improvement 
character string indicating direction of improvement. Default is "increase". 
SE 
character value indicating which formula to use for calculating the
standard error of TauBC, with possible values 
confidence 
confidence level for the reported interval estimate. Set to

pretest_trend 
significance level for the initial baseline trend test.
The raw data are corrected and 
report_correction 
logical value indicating whether to report the
baseline corrected slope and intercept values. Default is 
TauBC is an elaboration of the Tau
that includes a
correction for baseline trend. The calculation of TauBC involves two or
three steps, depending on the pretest_trend
argument.
If pretest_trend = FALSE
(the default), the first step involves
adjusting the outcomes for baseline trend estimated using TheilSen
regression. In the second step, the residuals from TheilSen regression are
used to calculate the Tau
(nonoverlap) index.
Alternately, pretest_trend
can be set equal to a significance level
between 0 and 1 (e.g. pretest_trend = .05
, as suggested by Tarlow,
2017). In this case, the first step involves a significance test for the
slope of the baseline trend based on Kendall's rank correlation. If the
slope is not significantly different from zero, then no baseline trend
adjustment is made and TauBC is set equal to Tau
. If the
slope is significantly different from zero, then in the second step, the
outcomes are adjusted for baseline trend using TheilSen regression and, in
the third step, the residuals from TheilSen regression are used to
calculate the Tau
(nonoverlap) index.
Note that the standard error formulas are based on the standard errors for
Tau
(nonoverlap) and they do not account for the additional
uncertainty due to use of the baseline trend correction (nor to the
pretest for statistical significance of baseline trend, if used).
A list containing the estimate, standard error, and/or confidence interval.
Tarlow, K. R. (2017). An improved rank correlation effect size statistic for singlecase designs: Baseline corrected Tau. Behavior modification, 41(4), 427467. doi:doi: 10.1177/0145445516676750
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