Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
권호 표지

Nonparametric Methods for Analyzing Incomplete Ranking Data

  • Lim, Dong-Hoon (Department of Statistics, Gyeongsang National University)
  • Published : 1998.12.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper we consider the setting where a group of n judges are to independently rank a series of κ objects, but the intended complete rankings are not realized and we are faced with analyzing randomly incomplete rank vectors. We discuss some tests based on Friedman statistics on the designs completed through rank imputation schemes suggested by Lordo and Wolfe (1994) and evaluate them on the basis of simulated power studies, constructing their appropriate null distributions.

Keywords

References

  1. Journal of the American Statistical Association v.32 The use of ranks to avoid the assumption of normality implicit in the analysis of variance Friedman, M.
  2. Nonparametric Statistical Methods Hollander, M.;Wolfe, D.A.
  3. Journal of Royal Statistical Society Series D A screening analysis for incomplete ranking data. under examination for Lim, D.H.;Lordo, R.A.;Wolfe, D.A.
  4. Parisankhyan Samikkha v.1 Statistical methodology for incompletely ranked data Lordo, R.A.;Wolfe, D.A.
  5. Journal of Biopharmaceutical Statistics v.5 no.2 Some applications of the analysis of multivariate normal data with missing observations May, W.L.;Johnson, W.D.
  6. Journal of the American Statistical Association v.58 Ordered hypotheses for multiple treatments: a significance test for linear ranks Page, E.B.
  7. Multiple Imputation for Nonresponse in Surveys Rubin, D.B.