![]() ![]() Since BSV and BSVR are estimated from the base and full covariate models, respectively, then BSVP = BSV-BSVR. As BSVP increases, the remaining unpredictable (or random) between subject variability (BSVR) decreases since BSV = BSVP + BSVR, and BSV is a constant in any given data set. The predictable component of BSV (termed BSVP) is explained by covariates, individual characteristics e.g. Both these variances can further be split into random and predictable components. The overall variability in a parameter within a population termed population parameter variance (PPV) consists of within subject variance (WSV) and BSV. It generally consists of two model hierarchies: a model for residual error and a model for heterogeneity termed between subject variance (BSV). Population pharmacokinetic-pharmacodynamic analysis involves nonlinear hierarchical modelling where the mean response in a population and the variability in response from different sources are studied. ![]()
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