Search Results - "FOX, P. J."

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  1. 1

    A Multivariate Multilevel Approach to the Modeling of Accuracy and Speed of Test Takers by Klein Entink, R. H., Fox, J.-P., van der Linden, W. J.

    Published in Psychometrika (01-03-2009)
    “…Response times on test items are easily collected in modern computerized testing. When collecting both (binary) responses and (continuous) response times on…”
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  2. 2

    Shearing Behavior of Interfaces between Tire-Derived Aggregate and Three Soil Materials by Ghaaowd, I, Fox, P. J, McCartney, J. S

    Published in Journal of materials in civil engineering (01-06-2020)
    “…AbstractWhen tire derived aggregate (TDA) is used as a lightweight monolithic fill in civil engineering applications, such as embankments and retaining walls,…”
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  3. 3

    Bayesian tests of measurement invariance by Verhagen, A. J., Fox, J. P.

    “…Random item effects models provide a natural framework for the exploration of violations of measurement invariance without the need for anchor items. Within…”
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  4. 4

    Cannabinoids in multiple sclerosis (CAMS) study: safety and efficacy data for 12 months follow up by Zajicek, J P, Sanders, H P, Wright, D E, Vickery, P J, Ingram, W M, Reilly, S M, Nunn, A J, Teare, L J, Fox, P J, Thompson, A J

    “…Objective: To test the effectiveness and long term safety of cannabinoids in multiple sclerosis (MS), in a follow up to the main Cannabinoids in Multiple…”
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  5. 5

    Mixture randomized item-response modeling: a smoking behavior validation study by Fox, J.-P., Avetisyan, M., van der Palen, J.

    Published in Statistics in medicine (30-11-2013)
    “…Misleading response behavior is expected in medical settings where incriminating behavior is negatively related to the recovery from a disease. In the present…”
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  6. 6

    Getting the measure of spasticity in multiple sclerosis: the Multiple Sclerosis Spasticity Scale (MSSS-88) by Hobart, J. C., Riazi, A., Thompson, A. J., Styles, I. M., Ingram, W., Vickery, P. J., Warner, M., Fox, P. J., Zajicek, J. P.

    Published in Brain (London, England : 1878) (01-01-2006)
    “…Spasticity is most commonly defined as an inappropriate, velocity dependent, increase in muscle tonic stretch reflexes, due to the amplified reactivity of…”
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  7. 7

    Multilevel IRT using dichotomous and polytomous response data by Fox, J. -P.

    “…A structural multilevel model is presented where some of the variables cannot be observed directly but are measured using tests or questionnaires. Observed…”
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  8. 8

    A Box-Cox normal model for response times by Entink, R. H. Klein, van der Linden, W. J., Fox, J.-P.

    “…The log‐transform has been a convenient choice in response time modelling on test items. However, motivated by a dataset of the Medical College Admission Test…”
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  9. 9

    A Mixed Effects Randomized Item Response Model by Fox, J.-P., Wyrick, Cheryl

    “…The randomized response technique ensures that individual item responses, denoted as true item responses, are randomized before observing them and so-called…”
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    Volcanic growth faults and the origin of Pacific abyssal hills by Macdonald, Ken C, Fox, P. J, Alexander, Russ T, Pockalny, Robert, Gente, Pascal

    Published in Nature (London) (14-03-1996)
    “…Abyssal hills characterize more than 30% of the ocean floor. Research suggests that Pacific abyssal hills are created on the flanks of the East Pacific Rise as…”
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  13. 13

    Artifactual formylation of the secondary amine of duloxetine hydrochloride by acetonitrile in the presence of titanium dioxide: Implications for HPLC method development by Skibic, M.J., King, L.A., Khan, M., Fox, P.J., Winger, B.E., Baertschi, S.W.

    “…Duloxetine hydrochloride, a secondary amine containing pharmaceutical, currently marketed as Cymbalta™, is shown to undergo N-formylation as an artifact of…”
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  14. 14

    Stochastic EM for estimating the parameters of a multilevel IRT model by Fox, J.-P.

    “…An item response theory (IRT) model is used as a measurement error model for the dependent variable of a multilevel model. The dependent variable is latent but…”
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  15. 15

    Latent growth modeling of IRT versus CTT measured longitudinal latent variables by Gorter, R, Fox, J-P, Riet, G Ter, Heymans, MW, Twisk, JWR

    Published in Statistical methods in medical research (01-04-2020)
    “…Latent growth models are often used to measure individual trajectories representing change over time. The characteristics of the individual trajectories depend…”
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  16. 16

    A pore-scale numerical model for flow through porous media by Zhu, Yi, Fox, Patrick J., Morris, Joseph P.

    “…A pore‐scale numerical model based on Smoothed Particle Hydrodynamics (SPH) is described for modelling fluid flow phenomena in porous media. Originally…”
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  17. 17

    Hierarchical process modeling: Describing within-run and between-run variations by Klein Entink, R.H., Fox, J.-P., Betlem, B.H.L., Roffel, B.

    Published in Journal of process control (01-04-2007)
    “…Run-to-run variability is a common problem for modeling batch-wise and semi-continuous operated processes. Although observed reactor runs show the same trends…”
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  18. 18

    Missing item responses in latent growth analysis: Item response theory versus classical test theory by Gorter, R, Fox, J-P, Eekhout, I, Heymans, MW, Twisk, JWR

    Published in Statistical methods in medical research (01-04-2020)
    “…In medical research, repeated questionnaire data is often used to measure and model latent variables across time. Through a novel imputation method, a direct…”
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  19. 19

    A reliable, compact, and low-cost Michelson wavemeter for laser wavelength measurement by Fox, P. J., Scholten, R. E., Walkiewicz, M. R., Drullinger, R. E.

    Published in American journal of physics (01-07-1999)
    “…We describe the construction and operation of a simple, compact, and cost effective Michelson wavemeter with picometer accuracy. The low cost of the device…”
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  20. 20

    Interaction of Soft Condensed Materials with Living Cells: Phenotype/Transcriptome Correlations for the Hydrophobic Effect by Allen, Lorcan T., Edward J. P. Fox, Blute, Irena, Kelly, Zoe D., Rochev, Yuri, Keenan, Alan K., Dawson, Kenneth A., Gallagher, William M.

    “…The assessment of biomaterial compatibility relies heavily on the analysis of macroscopic cellular responses to material interaction. However, new technologies…”
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