@article{fdi:010061841,
  title = {{S}tatistical decision from k test series with particular focus on population genetics tools : a {DIY} notice},
  author = {{D}e {M}eeûs, {T}hierry},
  editor = {},
  language = {{ENG}},
  abstract = {{I}n population genetics data analysis, researchers are often faced to the problem of decision making from a series of tests of the same null hypothesis. {T}his is the case when one wants to test differentiation between pathogens found on different host species sampled from different locations (as many tests as number of locations). {M}any procedures are available to date but not all apply to all situations. {F}inding which tests are significant or if the whole series is significant, when tests are independent or not do not require the same procedures. {I}n this note {I} describe several procedures, among the simplest and easiest to undertake, that should allow decision making in most (if not all) situations population geneticists (or biologists) should meet, in particular in host-parasite systems.},
  keywords = {{M}ultiple testing ; {B}onferroni correction ; {F}isher's procedure ; {S}touffer's {Z} ; {G}eneralized binomial procedure},
  booktitle = {},
  journal = {{I}nfection {G}enetics and {E}volution},
  volume = {22},
  numero = {},
  pages = {91--93},
  ISSN = {1567-1348},
  year = {2014},
  DOI = {10.1016/j.meegid.2014.01.005},
  URL = {https://www.documentation.ird.fr/hor/fdi:010061841},
}