Model selection using information criteria, but is the "best" model any good?

R. Mac Nally, R.P. Duncan, James R. Thomson, J.D.L. Yen

    Research output: Contribution to journalComment/debate

    28 Citations (Scopus)

    Abstract

    1. Information criteria (ICs) are used widely for data summary and model building in ecology, especially in applied ecology and wildlife management. Although ICs are useful for distinguishing among rival candidate models, ICs do not necessarily indicate whether the “best” model (or a model-averaged version) is a good representation of the data or whether the model has useful “explanatory” or “predictive” ability.
    2. As editors and reviewers, we have seen many submissions that did not evaluate whether the nominal “best” model(s) found using IC is a useful model in the above sense.
    3. We scrutinized six leading ecological journals for papers that used IC to compare models. More than half of papers using IC for model comparison did not evaluate the adequacy of the best model(s) in either “explaining” or “predicting” the data.
    4. Synthesis and applications. Authors need to evaluate the adequacy of the model identified as the “best” model by using information criteria methods to provide convincing evidence to readers and users that inferences from the best models are useful and reliable.
    Original languageEnglish
    Pages (from-to)1441-1444
    Number of pages4
    JournalJournal of Applied Ecology
    Volume55
    Issue number3
    DOIs
    Publication statusPublished - May 2018

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    wildlife management
    ecology
    comparison
    method
    applied ecology

    Cite this

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    Model selection using information criteria, but is the "best" model any good? / Mac Nally, R.; Duncan, R.P.; Thomson, James R.; Yen, J.D.L.

    In: Journal of Applied Ecology, Vol. 55, No. 3, 05.2018, p. 1441-1444.

    Research output: Contribution to journalComment/debate

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    AU - Mac Nally, R.

    AU - Duncan, R.P.

    AU - Thomson, James R.

    AU - Yen, J.D.L.

    N1 - cited By 0; Article in Press

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    N2 - 1. Information criteria (ICs) are used widely for data summary and model building in ecology, especially in applied ecology and wildlife management. Although ICs are useful for distinguishing among rival candidate models, ICs do not necessarily indicate whether the “best” model (or a model-averaged version) is a good representation of the data or whether the model has useful “explanatory” or “predictive” ability.2. As editors and reviewers, we have seen many submissions that did not evaluate whether the nominal “best” model(s) found using IC is a useful model in the above sense.3. We scrutinized six leading ecological journals for papers that used IC to compare models. More than half of papers using IC for model comparison did not evaluate the adequacy of the best model(s) in either “explaining” or “predicting” the data.4. Synthesis and applications. Authors need to evaluate the adequacy of the model identified as the “best” model by using information criteria methods to provide convincing evidence to readers and users that inferences from the best models are useful and reliable.

    AB - 1. Information criteria (ICs) are used widely for data summary and model building in ecology, especially in applied ecology and wildlife management. Although ICs are useful for distinguishing among rival candidate models, ICs do not necessarily indicate whether the “best” model (or a model-averaged version) is a good representation of the data or whether the model has useful “explanatory” or “predictive” ability.2. As editors and reviewers, we have seen many submissions that did not evaluate whether the nominal “best” model(s) found using IC is a useful model in the above sense.3. We scrutinized six leading ecological journals for papers that used IC to compare models. More than half of papers using IC for model comparison did not evaluate the adequacy of the best model(s) in either “explaining” or “predicting” the data.4. Synthesis and applications. Authors need to evaluate the adequacy of the model identified as the “best” model by using information criteria methods to provide convincing evidence to readers and users that inferences from the best models are useful and reliable.

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