Evaluation of negative binomial and zero-inflated negative binomial models for the analysis of zero-inflated count data: application to the telemedicine for children with medical complexity trial
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
1 Online-Ressource.
- Sprache
-
Englisch
- Erschienen in
-
Evaluation of negative binomial and zero-inflated negative binomial models for the analysis of zero-inflated count data: application to the telemedicine for children with medical complexity trial ; volume:24 ; number:1 ; day:27 ; month:9 ; year:2023 ; pages:1-11 ; date:12.2023
Trials ; 24, Heft 1 (27.9.2023), 1-11, 12.2023
- Urheber
-
Lee, Kyung Hyun
Pedroza, Claudia
Avritscher, Elenir B. C.
Mosquera, Ricardo A.
Tyson, Jon E.
- Beteiligte Personen und Organisationen
-
SpringerLink (Online service)
- DOI
-
10.1186/s13063-023-07648-8
- URN
-
urn:nbn:de:101:1-2024020515451321160694
- Rechteinformation
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
- 15.08.2025, 07:31 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Lee, Kyung Hyun
- Pedroza, Claudia
- Avritscher, Elenir B. C.
- Mosquera, Ricardo A.
- Tyson, Jon E.
- SpringerLink (Online service)
Ähnliche Objekte (12)
Early warning and predicting of COVID-19 using zero-inflated negative binomial regression model and negative binomial regression model
Bayesian negative binomial logit hurdle and zero-inflated model for characterizing smoking intensity
NBZIMM: negative binomial and zero-inflated mixed models, with application to microbiome/metagenomics data analysis
Modeling of Parking Violations Using Zero-Inflated Negative Binomial Regression – A Case Study for Berlin
Statistical analysis of variability in TnSeq data across conditions using zero-inflated negative binomial regression
Multiple arbitrarily inflated negative binomial regression model and its application
Multiple inflated negative binomial regression for correlated multivariate count data
MOMENT RECURRENCE RELATIONS FOR THE INFLATED NEGATIVE BINOMIAL, POISSON AND GEOMETRIC DISTRIBUTIONS
A comparison of zero-inflated and hurdle models for modeling zero-inflated count data
Mediation analysis for zero-inflated mediators
On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
Robust estimation of zero-inflated count models
Early warning and predicting of COVID-19 using zero-inflated negative binomial regression model and negative binomial regression model
Bayesian negative binomial logit hurdle and zero-inflated model for characterizing smoking intensity
NBZIMM: negative binomial and zero-inflated mixed models, with application to microbiome/metagenomics data analysis
Modeling of Parking Violations Using Zero-Inflated Negative Binomial Regression – A Case Study for Berlin
Statistical analysis of variability in TnSeq data across conditions using zero-inflated negative binomial regression
Multiple arbitrarily inflated negative binomial regression model and its application
Multiple inflated negative binomial regression for correlated multivariate count data
MOMENT RECURRENCE RELATIONS FOR THE INFLATED NEGATIVE BINOMIAL, POISSON AND GEOMETRIC DISTRIBUTIONS
A comparison of zero-inflated and hurdle models for modeling zero-inflated count data
Mediation analysis for zero-inflated mediators
On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods
Robust estimation of zero-inflated count models
Early warning and predicting of COVID-19 using zero-inflated negative binomial regression model and negative binomial regression model
Bayesian negative binomial logit hurdle and zero-inflated model for characterizing smoking intensity
NBZIMM: negative binomial and zero-inflated mixed models, with application to microbiome/metagenomics data analysis
Modeling of Parking Violations Using Zero-Inflated Negative Binomial Regression – A Case Study for Berlin
Statistical analysis of variability in TnSeq data across conditions using zero-inflated negative binomial regression
Multiple arbitrarily inflated negative binomial regression model and its application
Multiple inflated negative binomial regression for correlated multivariate count data
MOMENT RECURRENCE RELATIONS FOR THE INFLATED NEGATIVE BINOMIAL, POISSON AND GEOMETRIC DISTRIBUTIONS
A comparison of zero-inflated and hurdle models for modeling zero-inflated count data
Mediation analysis for zero-inflated mediators
On the equivalence of one‐inflated zero‐truncated and zero‐truncated one‐inflated count data likelihoods