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multinomial probit regression  (MathWorks Inc)


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    MathWorks Inc multinomial probit regression
    Multinomial Probit Regression, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/multinomial+probit+regression/pmc10756195__pnas__2315515120__sapp-143-1-26
    Average 90 stars, based on 1 article reviews
    multinomial probit regression - by Bioz Stars, 2026-10
    90/100 stars

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    Article Title: Supporting Information for Anion efflux mediates transduction in the hair cells of the zebrafish lateral line
    Article Snippet: .. First, multinomial probit regression was used to implement an omnibus test that detects differences between the experimental and control groups while integrating information across stimulus intensities (Mathworks, MATLAB R2020b). .. Second, pairwise differences between the experimental and control groups at specific stimulus intensities were detected using Fisher’s exact test with false discovery rate control implemented using the Benjamini-Hochberg procedure (Mathworks, MATLAB R2020b).



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    Full and Final Model of Potential Risk Factors Using Independent Multinomial Probit Regression: Lesion Remained Unchanged ( U ) and Deteriorated ( D ) a

    Journal: Journal of Dental Research

    Article Title: Risk Score Algorithm for Treatment of Persistent Apical Periodontitis

    doi: 10.1177/0022034514549559

    Figure Lengend Snippet: Full and Final Model of Potential Risk Factors Using Independent Multinomial Probit Regression: Lesion Remained Unchanged ( U ) and Deteriorated ( D ) a

    Article Snippet: The independent multinomial probit stepwise regression procedure (Stata 12.1, StataCorp LP, USA) was selected since outcome categories were discrete variables with more than 2 outcome categories that did not have a natural ordering, and outcome categories were identified per radiographic evaluation of lesion progression.

    Techniques:

    Full and Final Model of Potential Risk Factors Using Independent Multinomial Probit Regression: Lesion Remained Unchanged ( U ) and Deteriorated ( D ) a

    Journal: Journal of Dental Research

    Article Title: Risk Score Algorithm for Treatment of Persistent Apical Periodontitis

    doi: 10.1177/0022034514549559

    Figure Lengend Snippet: Full and Final Model of Potential Risk Factors Using Independent Multinomial Probit Regression: Lesion Remained Unchanged ( U ) and Deteriorated ( D ) a

    Article Snippet: Model Building and Risk Score Algorithm The independent multinomial probit stepwise regression procedure (Stata 12.1, StataCorp LP, USA) was selected since outcome categories were discrete variables with more than 2 outcome categories that did not have a natural ordering, and outcome categories were identified per radiographic evaluation of lesion progression.

    Techniques: