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      Exploring the development of face recognition across childhood via logistic mixed-effects modelling of the standardised Cambridge Face Memory Test

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          Abstract

          Individual differences in face identity recognition abilities are present across the lifespan but require developmentally differentiated methods of assessment. Here, we examine the empirical validity of a widely used face identity recognition measure, the Cambridge Face Memory Test for Children (CFMT-C). Logistic mixed-effects modelling of a large data set (607 children, 5–12 years) replicates and extends the findings of the only previous normative study of the CFMT-C (Croydon et al., Neuropsychologia, 62, 60–67, 2014). This novel, analytical approach enables us to take into account sources of variability typically overlooked in a classical analysis. We consider variability introduced by the task, alongside variability across children, to provide the first comprehensive characterisation of the interactive effects of factors inherent to participants (e.g. age, gender, and ethnicity), and the test (stage: face learning, simple recognition, harder recognition) on face memory performance. In line with past findings, we clearly observed age-related improvement in the task. Additionally, and for the first time, we report that this developmental effect is significantly more pronounced in the later, harder stages of the task; that there is an effect of gender, with females having better performance; and that consideration of participant ethnicity or testing context did not alter the best fitting model of these data. These results highlight the value of applying multilevel statistical models to characterise the factors driving performance variability, providing evidence of the divergence in recognition abilities across genders and confirming the stability of the CFMT-C in assessing face recognition abilities across variable experimental contexts and with diverse participant groups.

          Supplementary information

          The online version contains supplementary material available at 10.3758/s13428-025-02629-y.

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          Fitting Linear Mixed-Effects Models Usinglme4

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            Random effects structure for confirmatory hypothesis testing: Keep it maximal.

            Linear mixed-effects models (LMEMs) have become increasingly prominent in psycholinguistics and related areas. However, many researchers do not seem to appreciate how random effects structures affect the generalizability of an analysis. Here, we argue that researchers using LMEMs for confirmatory hypothesis testing should minimally adhere to the standards that have been in place for many decades. Through theoretical arguments and Monte Carlo simulation, we show that LMEMs generalize best when they include the maximal random effects structure justified by the design. The generalization performance of LMEMs including data-driven random effects structures strongly depends upon modeling criteria and sample size, yielding reasonable results on moderately-sized samples when conservative criteria are used, but with little or no power advantage over maximal models. Finally, random-intercepts-only LMEMs used on within-subjects and/or within-items data from populations where subjects and/or items vary in their sensitivity to experimental manipulations always generalize worse than separate F 1 and F 2 tests, and in many cases, even worse than F 1 alone. Maximal LMEMs should be the 'gold standard' for confirmatory hypothesis testing in psycholinguistics and beyond.
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              Categorical Data Analysis

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                Author and article information

                Contributors
                l.ewing@uea.ac.uk
                Journal
                Behav Res Methods
                Behav Res Methods
                Behavior Research Methods
                Springer US (New York )
                1554-351X
                1554-3528
                10 March 2025
                10 March 2025
                2025
                : 57
                : 4
                : 113
                Affiliations
                [1 ]School of Psychology, University of East Anglia, Norwich Research Park, ( https://ror.org/026k5mg93) Norwich, NR4 7TJ UK
                [2 ]School of Psychology, University of Surrey, ( https://ror.org/00ks66431) Guildford, GU2 7XH UK
                [3 ]Centre for Genomics and Child Health, Blizard Institute, Queen Mary, University of London, ( https://ror.org/026zzn846) London, UK
                [4 ]William James Centre for Research, ISPA – Instituto Universitário, ( https://ror.org/019yg0716) Lisboa, Portugal
                [5 ]School of Psychological Science, Birkbeck College, University of London, ( https://ror.org/02mb95055) London, UK
                Author information
                http://orcid.org/0000-0001-5263-1267
                Article
                2629
                10.3758/s13428-025-02629-y
                11893692
                40064748
                dc5d9dfc-a1d4-4d31-a691-bb2767f563e7
                © The Author(s) 2025

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 18 February 2025
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000275, Leverhulme Trust;
                Award ID: RPG-2013-019
                Award ID: RPG-2016- 021
                Funded by: Fundação para a Ciencia e Técnologia
                Award ID: ID/04810/2020
                Funded by: FundRef http://dx.doi.org/10.13039/501100005032, Fundação Bial;
                Award ID: 129/20
                Categories
                Original Manuscript
                Custom metadata
                © The Psychonomic Society, Inc. 2025

                Clinical Psychology & Psychiatry
                face recognition,face memory,development,children,gender,multilevel methods,cfmt

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