- Abstract:
-
Simultaneous modelling of dense and sparse pharmacokinetic data is possible with a population approach. To determine the number of individuals required to detect the effect of a covariate, simulation-based power calculation methodologies can be employed. The Monte Carlo Mapped Power method (a simulation-based power calculation methodology using the likelihood ratio test) was extended in the current study to perform sample size calculations for mixed pharmacokinetic studies (i.e. both sparse a...
Expand abstract - Publication status:
- Published
- Publisher copy:
- 10.1208/s12248-014-9641-4
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- Journal:
- The AAPS journal
- Volume:
- 16
- Issue:
- 5
- Pages:
- 1110-1118
- Publication date:
- 2014-09-05
- DOI:
- EISSN:
-
1550-7416
- ISSN:
-
1550-7416
- URN:
-
uuid:fa709f50-dd2a-432e-a8f1-e5e2ef91df69
- Source identifiers:
-
475823
- Local pid:
- pubs:475823
- Copyright date:
- 2014
Journal article
Statistical power calculations for mixed pharmacokinetic study designs using a population approach.
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