The signed Kolmogorov-Smirnov test: why it should not be used

The two-sample Kolmogorov-Smirnov (KS) test is often used to decide whether two random samples have the same statistical distribution. A popular modification of the KS test is to use a signed version of the KS statistic to infer whether the values of one sample are statistically larger than the valu...

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Detalhes bibliográficos
Autor: Filion, Guillaume
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2015
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10230/25083
Acesso em linha:http://hdl.handle.net/10230/25083
http://dx.doi.org/10.1186/s13742-015-0048-7
Access Level:acceso abierto
Palavra-chave:Estadística
Biologia computacional
Kolmogorov-smirnov test
P-hacking
P-value
Statistics
Descrição
Resumo:The two-sample Kolmogorov-Smirnov (KS) test is often used to decide whether two random samples have the same statistical distribution. A popular modification of the KS test is to use a signed version of the KS statistic to infer whether the values of one sample are statistically larger than the values of the other. The underlying hypotheses of the KS test are intrinsically incompatible with this approach and the test can produce false positives supported by extremely low p-values. This potentially makes the signed KS test a tool of p-hacking, which should be discouraged by replacing it with standard tests such as the t-test and by providing confidence intervals instead of p-values.