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The plotter shows you exactly when levels drop below the therapeutic threshold, helping you anticipate when appetite may return
A Bayesian hierarchical model was fitted using the brms framework, specifying percent weight change as a Gaussian outcome with (i) drug-specific smooth dose effects (splines by drug), (ii) treatment duration included as a covariate to account for variability in follow-up time across trials, and (iii) a study-level random intercept to account for between-trial heterogeneity
To analyze the interaction between the factors, multiple linear regression was performed
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