Pharmacodynamic Categorical Models

Categorical data poses many challenges in data analysis. One can think of categorical data as arising from continuous data, however instead of seeing the continuous data value, we can see only whether it is above or below certain values. So instead of modelling observed values we must model the probability of seeing a response in a given category. This requires fundamentally different mathematical models to continuous data.

Wright Dose Ltd can provide:-

• Integration of categorical data scales with standard PKPD models, include random effects for variable patient sensitivity
• Time series models for changes in the underlying data-generating process
• Poisson-type models for count data, including random effects, overdispersion and models for modified zero incidence
• Multivariate models for integrating multiple categorical measures such as different adverse events
• Customized marginal distributions for unusual data arising from a mixture of processes

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