Non-parametric stability measures for analysing non-normal data

A K PAUL; RANJIT KUMAR PAUL; SAMARENDRA DAS; S K BEHERA; A DHANDAPANI

doi:10.56093/ijas.v85i8.50857

Authors

A K PAUL Principal Scientist, Indian Agricultural Statistics Research Institute, New Delhi 110 012
RANJIT KUMAR PAUL Scientist, Indian Agricultural Statistics Research Institute, New Delhi 110 012
SAMARENDRA DAS Scientist, Indian Agricultural Statistics Research Institute, New Delhi 110 012
S K BEHERA Ex-Student, Indian Agricultural Statistics Research Institute, New Delhi 110 012
A DHANDAPANI Principal Scientist, NAARM, Hyderabad, Indian Agricultural Statistics Research Institute, New Delhi 110 012

https://doi.org/10.56093/ijas.v85i8.50857

Keywords:

Genotype-environment interaction, Non-parametric measures, Power of the test, Stability, Type-1 error

Abstract

In the present investigation, five different non-parametric stability measures are proposed based on the ranks of the genotypes to assess genotype-environment interaction, when the data does not satisfy the normality assumption. The behaviours of developed stability indices are studied by simulation technique under the assumption of normal as well as non-normal distributions such as log-normal, gamma, beta and t - distributions. These indices are compared empirically by using power of the test and type-I error. Results from the non-parametric analysis with the help of simulation study demonstrated that the proposed index A₄ outperformed other indices in normal as well as nonnormal data scenarios.

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