View source: R/non-overlap-measures.R
PAND | R Documentation |
Calculates the percentage of all non-overlapping data index (Parker, Hagan-Burke, & Vannest, 2007; Parker, Vannest, & Davis, 2011).
PAND(
A_data,
B_data,
condition,
outcome,
baseline_phase = NULL,
intervention_phase = NULL,
improvement = "increase"
)
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
|
intervention_phase |
character string specifying which value of
|
improvement |
character string indicating direction of improvement. Default is "increase". |
For an outcome where increase is desirable, PAND is calculated as the proportion of observations remaining after removing the fewest possible number of observations from either phase so that the highest remaining point from the baseline phase is less than the lowest remaining point from the treatment phase. For an outcome where decrease is desirable, PAND is calculated as the proportion of observations remaining after removing the fewest possible number of observations from either phase so that the lowest remaining point from the baseline phase is greater than the highest remaining point from the treatment phase. The range of PAND depends on the number of observations in each phase.
Numeric value
Parker, R. I., Hagan-Burke, S., & Vannest, K. J. (2007). Percentage of all non-overlapping data (PAND): An alternative to PND. The Journal of Special Education, 40(4), 194–204. doi:\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/00224669070400040101")}
Parker, R. I., Vannest, K. J., & Davis, J. L. (2011). Effect size in single-case research: A review of nine nonoverlap techniques. Behavior Modification, 35(4), 303–22. doi:\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1177/0145445511399147")}
A <- c(20, 20, 26, 25, 22, 23)
B <- c(28, 25, 24, 27, 30, 30, 29)
PAND(A_data = A, B_data = B)
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