cushny              package:robustbase              R Documentation

_C_u_s_h_n_y _a_n_d _P_e_e_b_l_e_s _P_r_o_l_o_n_g_a_t_i_o_n _o_f _S_l_e_e_p _D_a_t_a

_D_e_s_c_r_i_p_t_i_o_n:

     The original data set was bivariate and recorded for ten subjects
     the prolongation of sleep caused by two different drugs.  These
     data were used by Student as the first illustration of the paired
     t-test which only needs the _differences_ of the two measurements.
      These differences are the values of 'cushny'.

_U_s_a_g_e:

     data(cushny)

_F_o_r_m_a_t:

     numeric vector, sorted increasingly:
      0 0.8 1 1.2 1.3 1.3 1.4 1.8 2.4 4.6

_S_o_u_r_c_e:

     Cushny, A.R. and Peebles, A.R. (1905) The action of optical
     isomers. {II}. Hyoscines. _J. Physiol._ *32*, 501-510.

     These data were used by Student(1908) as the first illustration of
     the paired t-test, see also 'sleep'; then cited by Fisher (1925)
     and thereforth copied in numerous books as an example of a
     normally distributed sample, see, e.g., Anderson (1958).

_R_e_f_e_r_e_n_c_e_s:

     Student (1908) The probable error of a mean. _Biometrika_ *6*,
     1-25.

     Fisher, R.A. (1925) _Statistical Methods for Research Workers_;
     Oliver & Boyd, Edinburgh.

     Anderson, T.W. (1958) _An Introduction to Multivariate Statistical
     Analysis_; Wiley, N.Y.

     Hampel, F., Ronchetti, E., Rousseeuw, P. and Stahel, W.  (1986)
     _Robust Statistics: The Approach Based on Influence Functions_;
     Wiley, N.Y.

_E_x_a_m_p_l_e_s:

     data(cushny)

     plot(cushny,  rep(0, 10), pch = 3, cex = 3,
          ylab = "", yaxt = "n")
     plot(jitter(cushny),  rep(0, 10), pch = 3, cex = 2,
          main = "'cushny' data (n= 10)", ylab = "", yaxt = "n")
     abline(h=0, col="gray", lty=3)
     myPt <- function(m, lwd = 2, ..., e = 1.5*par("cxy")[2])
       segments(m, +e, m, -e, lwd = lwd, ...)
     myPt(  mean(cushny), col = "pink3")
     myPt(median(cushny), col = "light blue")
     legend("topright", c("mean", "median"), lwd = 2,
            col = c("pink3", "light blue"), inset = .01)

     ## The 'sleep' data from the standard 'datasets' package:
     d.sleep <- local({ gr <- with(datasets::sleep, split(extra, group))
                        gr[[2]] - gr[[1]] })
     stopifnot(all.equal(cushny,
                         sort(d.sleep), tol=1e-15))

