ArticleJournal of pharmacokinetics and pharmacodynamics2021
Improved numerical stability for the bounded integer model.
Article in Journal of pharmacokinetics and pharmacodynamics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- A tutorial on pharmacometric Markov models.CPT: pharmacometrics & systems pharmacology · 2025Article
- Comparison of the power and type 1 error of total score models for drug effect detection in clinical trials.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Bounded integer model-based analysis of psoriasis area and severity index in patients with moderate-to-severe plaque psoriasis receiving BI 730357.CPT: pharmacometrics & systems pharmacology · 2023Article
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Authors and funding
2 authors.
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Abstract
This article highlights some numerical challenges when implementing the bounded integer model for composite score modeling and suggests an improved implementation. The improvement is based on an approximation of the logarithm of the error function. After presenting the derivation of the improved implementation, the article compares the performance of the algorithm to a naive implementation of the log-likelihood using both simulations and a real data example. In the simulation setting, the improved algorithm yielded more precise and less biased parameter estimates when the within-subject variability was small and estimation was performed using the Laplace algorithm. The estimation results did not differ between implementations when the SAEM algorithm was used. For the real data example, bootstrap results differed between implementations with the improved implementation producing identical or better objective function values. Based on the findings in this article, the improved implementation is suggested as the new default log-likelihood implementation for the bounded integer model.
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