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期刊名:Journal of the american statistical association

缩写:J AM STAT ASSOC

ISSN:0162-1459

e-ISSN:1537-274X

IF/分区:3.0/Q1

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共收录本刊相关文章索引6
Clinical Trial Case Reports Meta-Analysis RCT Review Systematic Review
Classical Article Case Reports Clinical Study Clinical Trial Clinical Trial Protocol Comment Comparative Study Editorial Guideline Letter Meta-Analysis Multicenter Study Observational Study Randomized Controlled Trial Review Systematic Review
Aritra Halder,Sudipto Banerjee,Dipak K Dey Aritra Halder
Spatial process models are widely used for modeling point-referenced variables arising from diverse scientific domains. Analyzing the resulting random surface provides deeper insights into the nature of latent dependence within the studied ...
Alessandro Zito,Tommaso Rigon,Otso Ovaskainen et al. Alessandro Zito et al.
We aim at modeling the appearance of distinct tags in a sequence of labeled objects. Common examples of this type of data include words in a corpus or distinct species in a sample. These sequential discoveries are often summarized via accum...
Li Li,Alejandro Jara,María José García-Zattera et al. Li Li et al.
Motivated by data gathered in an oral health study, we propose a Bayesian nonparametric approach for population-averaged modeling of correlated time-to-event data, when the responses can only be determined to lie in an interval obtained fro...
Tsuyoshi Kunihama,David B Dunson Tsuyoshi Kunihama
In many applications, it is of interest to study trends over time in relationships among categorical variables, such as age group, ethnicity, religious affiliation, political party and preference for particular policies. At each time point,...
Francesco C Stingo,Michele Guindani,Marina Vannucci et al. Francesco C Stingo et al.
In this paper we present a Bayesian hierarchical modeling approach for imaging genetics, where the interest lies in linking brain connectivity across multiple individuals to their genetic information. We have available data from a functiona...
Soma S Dhavala,Sujay Datta,Bani K Mallick et al. Soma S Dhavala et al.
Massively Parallel Signature Sequencing (MPSS) is a high-throughput counting-based technology available for gene expression profiling. It produces output that is similar to Serial Analysis of Gene Expression (SAGE) and is ideal for building...