Inferring the Timing of Antiretroviral Therapy by Zero-Inflated Random Change Point Models Using Longitudinal Data Subject to Left-Censoring

We propose a new random change point model that utilizes routinely recorded individual-level HIV viral load data to estimate the timing of antiretroviral therapy (ART) initiation in people living with HIV. The change point distribution is assumed to follow a zero-inflated exponential distribution fo...

Celý popis

Uložené v:

Podrobná bibliografia
Vydané v:	Algorithms Ročník 18; číslo 6; s. 346
Hlavní autori:	Zhang, Hongbin, Robertson, McKaylee, Braunstein, Sarah L., Hanna, David B., Felsen, Uriel R., Waldron, Levi, Nash, Denis
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI AG 01.06.2025
Predmet:	Algorithms Analysis Antiretroviral drugs Antiviral agents censored data Drug therapy Gibbs sampler Highly active antiretroviral therapy HIV HIV patients Human immunodeficiency virus nonlinear mixed-effects model Normal distribution Probability distribution functions random change point model Random variables Samplers Stochastic EM Surveillance zero-inflated exponential distribution New York United States
ISSN:	1999-4893, 1999-4893
On-line prístup:	Získať plný text
Tagy:	Pridať tag Žiadne tagy, Buďte prvý, kto otaguje tento záznam!

Buďte prvý, kto okomentuje tento záznam!