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To replicate, or not to replicate – that should not be a question
Author(s) -
Chalcraft David R.
Publication year - 2019
Publication title -
ecology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.852
H-Index - 265
eISSN - 1461-0248
pISSN - 1461-023X
DOI - 10.1111/ele.13286
Subject(s) - replicate , replication (statistics) , metric (unit) , computer science , ecology , data science , biology , statistics , mathematics , engineering , virology , operations management
Recent simulations suggest that ecologists can enhance the predictive ability of models by designing experiments that maximise the number of levels of an experimental factor by sacrificing replication. Here, I describe how these simulations were based on a faulty metric of prediction success and reinforce the importance of replication.