Search Results - Brinkhuis, Matthieu J. S.

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  1. 1
    Tracking with (Un)Certainty

    Tracking with (Un)Certainty by Hofman, Abe D, Brinkhuis, Matthieu J S, Bolsinova, Maria, Klaiber, Jonathan, Maris, Gunter, van der Maas, Han L J

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  2. 2
    The effect of estimation method and sample size in multilevel structural equation modeling

    The effect of estimation method and sample size in multilevel structural equation modeling by Hox, Joop J., Maas, Cora J. M., Brinkhuis, Matthieu J. S.

    Published in Statistica Neerlandica
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  3. 3
    Dynamic estimation in the extended marginal Rasch model with an application to mathematical computer‐adaptive practice

    Dynamic estimation in the extended marginal Rasch model with an application to mathematical computer‐adaptive practice by Brinkhuis, Matthieu J.S., Maris, Gunter

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  4. 4
    Cognitive Diagnostic Assessment in University Statistics Education: Valid and Reliable Skill Measurement for Actionable Feedback Using Learning Dashboards

    Cognitive Diagnostic Assessment in University Statistics Education: Valid and Reliable Skill Measurement for Actionable Feedback Using Learning Dashboards by Maas, Lientje, Brinkhuis, Matthieu J. S., Kester, Liesbeth, Wijngaards-de Meij, Leoniek

    Published in Applied sciences
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  5. 5
    Filtering Data for Detecting Differential Development

    Filtering Data for Detecting Differential Development by Brinkhuis, Matthieu J. S., Bakker, Marjan, Maris, Gunter

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  6. 6
    Tracking a multitude of abilities as they develop

    Tracking a multitude of abilities as they develop by Bolsinova, Maria, Brinkhuis, Matthieu J. S., Hofman, Abe D., Maris, Gunter

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  7. 7
    Urnings: A new method for tracking dynamically changing parameters in paired comparison systems

    Urnings: A new method for tracking dynamically changing parameters in paired comparison systems by Bolsinova, Maria, Maris, Gunter, Hofman, Abe D., van der Maas, Han L. J., Brinkhuis, Matthieu J. S.

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  8. 8
    Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening

    Combining Supervised and Unsupervised Machine Learning Methods for Phenotypic Functional Genomics Screening by Omta, Wienand A., van Heesbeen, Roy G., Shen, Ian, de Nobel, Jacob, Robers, Desmond, van der Velden, Lieke M., Medema, René H., Siebes, Arno P.J.M., Feelders, Ad J., Brinkkemper, Sjaak, Klumperman, Judith S., Spruit, Marco René, Brinkhuis, Matthieu J.S., Egan, David A.

    Published in SLAS discovery
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  9. 9
    Distinguishing Fast and Slow Processes in Accuracy - Response Time Data

    Distinguishing Fast and Slow Processes in Accuracy - Response Time Data by Coomans, Frederik, Hofman, Abe, Brinkhuis, Matthieu, van der Maas, Han L J, Maris, Gunter

    Published in PloS one
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  10. 10
    Speed–Accuracy Trade-Off? Not So Fast: Marginal Changes in Speed Have Inconsistent Relationships With Accuracy in Real-World Settings

    Speed–Accuracy Trade-Off? Not So Fast: Marginal Changes in Speed Have Inconsistent Relationships With Accuracy in Real-World Settings by Domingue, Benjamin W., Kanopka, Klint, Stenhaug, Ben, Sulik, Michael J., Beverly, Tanesia, Brinkhuis, Matthieu, Circi, Ruhan, Faul, Jessica, Liao, Dandan, McCandliss, Bruce, Obradović, Jelena, Piech, Chris, Porter, Tenelle, Consortium, Project iLEAD, Soland, James, Weeks, Jon, Wise, Steven L., Yeatman, Jason

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