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In this study, we investigated a cohort of HIV-infected individuals on ART in the Coping with HIV/AIDS in Tanzania (CHAT) to describe which predictors are associated with the outcome of death.
Therefore, a baseline for comparing relative w+ i across predictors is required to ascertain which predictors are relevant.
Note that only the degree of shrinkage of a parameter is modified, not the correlation between a target, TF pair, nor the order in which predictors are selected by the model.
Focussing on the LQTS model because of the much larger training set available, we investigated which predictors are the most informative, and assessed the biological plausibility of estimated effect sizes.
Since clinical expertise is expected to complement statistically derived prognostic models, this study aimed to reach clinical consensus on which predictors are most important for predicting persistent shoulder pain.
Furthermore, our study illustrates that extending the network buffer from 10 min to 15 min walking distance has the effect of changing which predictors are significantly associated with VFI.
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Model comparison was made using Akaike's Information Criterion AICC) to evaluate which predictors were more closely associated with the outcome [33, 34].
We modelled candidate predictors as univariates and determined which predictors were significant (p<0.20).
The Wald test was conducted to find which predictors were significant in the model.
A multivariate logistic regression analysis was undertaken to address which predictors were associated with increased in-hospital mortality.
In a sensitivity analysis, we investigated which predictors were associated with the individual dimensions of the EQ-5D.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com