On the analysis of sequential designs without a specified number of observations

Fuente: arXiv
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Main Authors: Klimova, Anna, Rudas, Tamás
Format: Preprint
Published: 2025
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author Klimova, Anna
Rudas, Tamás
author_facet Klimova, Anna
Rudas, Tamás
contents The paper focuses on sequential experiments for categorical responses in which whether or not a further observation is made depends on the outcome of a previous experiment. Examples include subsequent medical interventions being performed or not depending on the result of a previous intervention, data about offsprings, life tables, and repeated educational retraininig until a certain proficiency level is achieved. Such experiments do not lead to data with a full Cartesian product structure and, despite a prespecified initial sample size, the total number of observations, or interventions, made cannot be determined in advance. The paper investigates the distributional assumptions behind such data and describes a parameterization of the distribution that arises and the respective model class to analyze it. Both the data structure resulting from such an experiment and the model class are special examples of staged trees in algebraic statistics. The properties of the resulting parameter estimates and test statistics are obtained and illustrated using hypothetical and real data.
format Preprint
id arxiv_https___arxiv_org_abs_2507_02580
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle On the analysis of sequential designs without a specified number of observations
Klimova, Anna
Rudas, Tamás
Methodology
The paper focuses on sequential experiments for categorical responses in which whether or not a further observation is made depends on the outcome of a previous experiment. Examples include subsequent medical interventions being performed or not depending on the result of a previous intervention, data about offsprings, life tables, and repeated educational retraininig until a certain proficiency level is achieved. Such experiments do not lead to data with a full Cartesian product structure and, despite a prespecified initial sample size, the total number of observations, or interventions, made cannot be determined in advance. The paper investigates the distributional assumptions behind such data and describes a parameterization of the distribution that arises and the respective model class to analyze it. Both the data structure resulting from such an experiment and the model class are special examples of staged trees in algebraic statistics. The properties of the resulting parameter estimates and test statistics are obtained and illustrated using hypothetical and real data.
title On the analysis of sequential designs without a specified number of observations
topic Methodology
url https://arxiv.org/abs/2507.02580