Datasets
- 24 results
Search results
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B-PA_Code – Supplemental material for Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), figshare SAGE Publications, 2020
DOI: 10.25384/sage.12707343.v1, https://sage.figshare.com/articles/B-PA_Code_Supplemental_material_for_Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/12707343/1
Dataset
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Working memory predicts word learning (Gray et al., 2022)
Gray, S. I. (Creator), Levy, R. (Creator), Alt, M. (Creator), Hogan, T. P. (Creator) & Cowan, N. (Creator), ASHA journals, 2022
DOI: 10.23641/asha.19125911, https://asha.figshare.com/articles/dataset/Working_memory_predicts_word_learning_Gray_et_al_2022_/19125911
Dataset
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HolzingerSwinefore_Grant-White_19tests – Supplemental material for Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.12707346, https://sage.figshare.com/articles/HolzingerSwinefore_Grant-White_19tests_Supplemental_material_for_Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/12707346
Dataset
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Working memory predicts word learning (Gray et al., 2022)
Gray, S. I. (Creator), Levy, R. (Creator), Alt, M. (Creator), Hogan, T. P. (Creator) & Cowan, N. (Creator), ASHA journals, 2022
DOI: 10.23641/asha.19125911.v1, https://asha.figshare.com/articles/dataset/Working_memory_predicts_word_learning_Gray_et_al_2022_/19125911/1
Dataset
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Considerations for Fitting Dynamic Bayesian Networks With Latent Variables: A Monte Carlo Study
Reichenberg, R. E. (Creator), Levy, R. (Creator) & Clark, A. (Creator), SAGE Journals, 2022
DOI: 10.25384/sage.c.5875914, https://sage.figshare.com/collections/Considerations_for_Fitting_Dynamic_Bayesian_Networks_With_Latent_Variables_A_Monte_Carlo_Study/5875914
Dataset
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Dynamic Bayesian Network Modeling of Game-Based Diagnostic Assessments
Levy, R. (Creator), figshare Academic Research System, 2021
DOI: 10.6084/m9.figshare.14473873.v1, https://tandf.figshare.com/articles/dataset/Dynamic_Bayesian_Network_Modeling_of_Game-Based_Diagnostic_Assessments/14473873/1
Dataset
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Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.c.5072631, https://sage.figshare.com/collections/Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/5072631
Dataset
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HolzingerSwinefore_Grant-White_19tests – Supplemental material for Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), figshare SAGE Publications, 2020
DOI: 10.25384/sage.12707346.v1, https://sage.figshare.com/articles/HolzingerSwinefore_Grant-White_19tests_Supplemental_material_for_Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/12707346/1
Dataset
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Tests of Simple Slopes in Multiple Regression Models with an Interaction: Comparison of Four Approaches
Aiken, L. S. (Contributor), Liu, Y. (Contributor), West, S. G. (Contributor) & Levy, R. (Contributor), figshare Academic Research System, Jan 1 2017
DOI: 10.6084/m9.figshare.4960556.v1, https://doi.org/10.6084%2Fm9.figshare.4960556.v1
Dataset
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Considerations for Fitting Dynamic Bayesian Networks With Latent Variables: A Monte Carlo Study
Reichenberg, R. E. (Creator), Levy, R. (Creator) & Clark, A. (Creator), SAGE Journals, 2022
DOI: 10.25384/sage.c.5875914, https://sage.figshare.com/collections/Considerations_for_Fitting_Dynamic_Bayesian_Networks_With_Latent_Variables_A_Monte_Carlo_Study/5875914
Dataset
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B-PA_Code – Supplemental material for Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.12707343, https://sage.figshare.com/articles/B-PA_Code_Supplemental_material_for_Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/12707343
Dataset
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Considerations for Fitting Dynamic Bayesian Networks With Latent Variables: A Monte Carlo Study
Reichenberg, R. E. (Creator), Levy, R. (Creator) & Clark, A. (Creator), SAGE Journals, 2022
DOI: 10.25384/sage.c.5875914.v1, https://sage.figshare.com/collections/Considerations_for_Fitting_Dynamic_Bayesian_Networks_With_Latent_Variables_A_Monte_Carlo_Study/5875914/1
Dataset
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Considerations for Fitting Dynamic Bayesian Networks With Latent Variables: A Monte Carlo Study
Reichenberg, R. E. (Creator), Levy, R. (Creator) & Clark, A. (Creator), SAGE Journals, 2022
DOI: 10.25384/sage.c.5875914.v1, https://sage.figshare.com/collections/Considerations_for_Fitting_Dynamic_Bayesian_Networks_With_Latent_Variables_A_Monte_Carlo_Study/5875914/1
Dataset
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sj-pdf-1-apm-10.1177_01466216211066609 – Supplemental Material for Considerations for Fitting Dynamic Bayesian Networks With Latent Variables: A Monte Carlo Study
Reichenberg, R. E. (Creator), Levy, R. (Creator) & Clark, A. (Creator), SAGE Journals, 2022
DOI: 10.25384/sage.19307712.v1, https://sage.figshare.com/articles/journal_contribution/sj-pdf-1-apm-10_1177_01466216211066609_Supplemental_Material_for_Considerations_for_Fitting_Dynamic_Bayesian_Networks_With_Latent_Variables_A_Monte_Carlo_Study/19307712/1
Dataset
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Precluding Interpretational Confounding in Factor Analysis with a Covariate or Outcome via Measurement and Uncertainty Preserving Parametric Modeling
Levy, R. (Creator), Taylor & Francis, 2023
DOI: 10.6084/m9.figshare.22148777.v1, https://tandf.figshare.com/articles/dataset/Precluding_Interpretational_Confounding_in_Factor_Analysis_with_a_Covariate_or_Outcome_via_Measurement_and_Uncertainty_Preserving_Parametric_Modeling/22148777/1
Dataset
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Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), figshare SAGE Publications, 2020
DOI: 10.25384/sage.c.5072631.v1, https://sage.figshare.com/collections/Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/5072631/1
Dataset
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HolzingerSwinefore_Grant-White_19tests – Supplemental material for Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.12707346, https://sage.figshare.com/articles/HolzingerSwinefore_Grant-White_19tests_Supplemental_material_for_Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/12707346
Dataset
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HolzingerSwinefore_Grant-White_19tests – Supplemental material for Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.12707346.v1, https://sage.figshare.com/articles/HolzingerSwinefore_Grant-White_19tests_Supplemental_material_for_Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/12707346/1
Dataset
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Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.c.5072631, https://sage.figshare.com/collections/Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/5072631
Dataset
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B-PA_Code – Supplemental material for Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.12707343, https://sage.figshare.com/articles/B-PA_Code_Supplemental_material_for_Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/12707343
Dataset
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Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.c.5072631.v1, https://sage.figshare.com/collections/Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/5072631/1
Dataset
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B-PA_Code – Supplemental material for Incorporating Uncertainty Into Parallel Analysis for Choosing the Number of Factors via Bayesian Methods
Levy, R. (Creator), Xia, Y. (Creator) & Green, S. B. (Creator), SAGE Journals, 2020
DOI: 10.25384/sage.12707343.v1, https://sage.figshare.com/articles/B-PA_Code_Supplemental_material_for_Incorporating_Uncertainty_Into_Parallel_Analysis_for_Choosing_the_Number_of_Factors_via_Bayesian_Methods/12707343/1
Dataset
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Precluding Interpretational Confounding in Factor Analysis with a Covariate or Outcome via Measurement and Uncertainty Preserving Parametric Modeling
Levy, R. (Creator), Taylor & Francis, 2023
DOI: 10.6084/m9.figshare.22148777, https://tandf.figshare.com/articles/dataset/Precluding_Interpretational_Confounding_in_Factor_Analysis_with_a_Covariate_or_Outcome_via_Measurement_and_Uncertainty_Preserving_Parametric_Modeling/22148777
Dataset