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oai:figshare.com:article/34047767 2026-10-01T17:27:22Z category_21 category_272 category_734 category_811 category_106 category_135 portal_5 item_type_6 month_year_10_2026

<p>Multicollinearity diagnostics (variance inflation factors).</p> Grace Kakaire (22783476) Robert Too (822703) Gregory Kerich (10113145) Mathew Kosgei (10113142) Biotechnology Environmental Sciences not elsewhere classified Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Science Policy Computational Biology latent correlations among joint modeling yielded marginal effect estimates average marginal effects interacting risk factors integrated health interventions gaussian copula framework joint modeling approach joint modeling using conditions often co bivariate probit model malaria among children simultaneous modeling marginal probability probit margins model incorporated health outcomes environmental factors copula structure approach allowed study highlights study aims shared biological saharan africa level covariates interconnected nature findings support facilitate interpretation critical importance comorbidity patterns child morbidity <p>Variance inflation factors (VIFs) for all explanatory variables included in the joint Gaussian copula regression model, along with the mean VIF, used to assess multicollinearity.</p> <p>(DOCX)</p> 2026-10-01T17:27:19Z Text Journal contribution 10.1371/journal.pgph.0007387.s002 https://figshare.com/articles/journal_contribution/_p_Multicollinearity_diagnostics_variance_inflation_factors_p_/34047767 CC BY 4.0