Measurement error models with zero inflation and multiple sources of zeros, with applications to hard zeros.
Lifetime Data Anal
; 30(3): 600-623, 2024 Jul.
Article
em En
| MEDLINE
| ID: mdl-38806842
ABSTRACT
We consider measurement error models for two variables observed repeatedly and subject to measurement error. One variable is continuous, while the other variable is a mixture of continuous and zero measurements. This second variable has two sources of zeros. The first source is episodic zeros, wherein some of the measurements for an individual may be zero and others positive. The second source is hard zeros, i.e., some individuals will always report zero. An example is the consumption of alcohol from alcoholic beverages some individuals consume alcoholic beverages episodically, while others never consume alcoholic beverages. However, with a small number of repeat measurements from individuals, it is not possible to determine those who are episodic zeros and those who are hard zeros. We develop a new measurement error model for this problem, and use Bayesian methods to fit it. Simulations and data analyses are used to illustrate our methods. Extensions to parametric models and survival analysis are discussed briefly.
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Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Modelos Estatísticos
/
Teorema de Bayes
Limite:
Humans
Idioma:
En
Revista:
Lifetime Data Anal
/
Lifetime data anal
/
Lifetime data analysis
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
Estados Unidos