multrnks {sensitivitymv} | R Documentation |
Approximate scores for ranks.
Description
Of limited interest to most users, this function is sometimes called by senmv. The function calculates the large sample approximation to a rank score transformation in Lemma 1, expression (9) of Rosenbaum (2011). See also Rosenbaum (2014) and the sensitivitymw package.
Usage
multrnks(rk, m1 = 2, m2 = 2, m = 2)
Arguments
rk |
A vector of ranks that may include average ranks for ties. |
m1 |
One of three rank score parameters in Rosenbaum (2011), specifically m1 = underline(m). |
m2 |
One of three rank score parameters in Rosenbaum (2011), specifically m2 = overline(m). |
m |
One of three rank score parameters in Rosenbaum (2011), specifically m = m. |
Value
Vector of length(rk) containing the scores for the ranks in rk.
Author(s)
Paul R. Rosenbaum
References
Rosenbaum, P. R. (2011) <doi:10.1111/j.1541-0420.2010.01535.x> A new u-statistic with superior design sensitivity in matched observational studies. Biometrics 67, 1017-1027.
Rosenbaum, P. R. (2014) <doi:10.1080/01621459.2013.879261> Weighted M-statistics with superior design sensitivity in matched observational studies with multiple controls. Journal of the American Statistical Association, 109(507), 1145-1158.
Rosenbaum, P. R. (2024) <doi:10.1080/01621459.2023.2221402> Bahadur efficiency of observational block designs. Journal of the American Statistical Association, 119(547), 1871-1881.
Examples
multrnks(1:10)
multrnks(1:10,m1=12,m2=20,m=20)