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multi-level logistic regression model  (SAS institute)

 
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    SAS institute multi-level logistic regression model
    Characteristics of the longitudinal included studies.
    Multi Level Logistic Regression Model, supplied by SAS institute, 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/result/multi-level logistic regression model/product/SAS institute
    Average 90 stars, based on 1 article reviews
    multi-level logistic regression model - by Bioz Stars, 2026-04
    90/100 stars

    Images

    1) Product Images from "The influence of peer’s social networks on adolescent’s cannabis use: a systematic review of longitudinal studies"

    Article Title: The influence of peer’s social networks on adolescent’s cannabis use: a systematic review of longitudinal studies

    Journal: Frontiers in Psychiatry

    doi: 10.3389/fpsyt.2023.1306439

    Characteristics of the longitudinal included studies.
    Figure Legend Snippet: Characteristics of the longitudinal included studies.

    Techniques Used: Cannabis, Selection, Software, Isolation, Variant Assay, Control



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    Image Search Results


    Characteristics of the longitudinal included studies.

    Journal: Frontiers in Psychiatry

    Article Title: The influence of peer’s social networks on adolescent’s cannabis use: a systematic review of longitudinal studies

    doi: 10.3389/fpsyt.2023.1306439

    Figure Lengend Snippet: Characteristics of the longitudinal included studies.

    Article Snippet: PROSPER (Promoting School-Community-University Partnerships to Enhance Resilience) (USA) , Osgood et al. (2014) ( ) , 5 waves n = 9,500 Mean age: 6th through 9th grades 51.5% female , Cannabis last month into 5 levels: from 1 = “Not at all” to 5 = “More than once a week.” , 27 school friendship networks , Peer Influence Effects: Indegree (own popularity; friendship nominations an individual received, i.e., number of other students who named the respondent) , Multi-level logistic regression model/a routine programmed themselves (SAS).

    Techniques: Cannabis, Selection, Software, Isolation, Variant Assay, Control