Journal ArticleDOI
Modelling and generating correlated binary variables
Samuel D. Oman,David M. Zucker +1 more
TLDR
This work presents an alternative class of correlation models which reflect the binary nature of the responses and allow for simple simulation of observations from these models.Citations
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Journal ArticleDOI
A family of multivariate binary distributions for simulating correlated binary variables with specified marginal means and correlations
TL;DR: This work introduces a family of multivariate binary distributions with certain conditional linear property that is particularly useful for efficient and easy simulation of correlated binary variables with a given marginal mean vector and correlation matrix.
Journal ArticleDOI
Spatial-temporal rainfall simulation using generalized linear models
TL;DR: In this article, the problem of simulating sequences of daily rainfall at a network of sites in such a way as to reproduce a variety of properties realistically over a range of spatial scales is considered.
Journal ArticleDOI
Sequential Monte Carlo on large binary sampling spaces
Christian Schäfer,Nicolas Chopin +1 more
TL;DR: In this paper, the authors present a parametric family for adaptive sampling on high dimensional binary spaces, which takes correlations into account, analogously to the multivariate normal distribution on continuous spaces.
Journal ArticleDOI
Range of correlation matrices for dependent Bernoulli random variables
N. Rao Chaganty,Harry Joe +1 more
TL;DR: In this article, necessary and sufficient conditions for compatibility for structured and unstructured correlation matrices are studied. But they do not consider the non-parametric binary models of Emrich & Piedmonte (1991) and Qaqish (2003) which allow a good range of correlations between binary variables.
Journal ArticleDOI
Imputation strategies for missing continuous outcomes in cluster randomized trials.
TL;DR: It is shown that cluster mean imputation yields valid inferences and given its simplicity, may be an attractive option in some large community intervention trials which are subject to individual-level attrition only; however, it may yield less powerful inferences than alternative procedures which pool across clusters especially when the cluster sizes are small and cluster follow-up rates are highly variable.
References
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Journal ArticleDOI
Longitudinal data analysis using generalized linear models
Kung Yee Liang,Scott L. Zeger +1 more
TL;DR: In this article, an extension of generalized linear models to the analysis of longitudinal data is proposed, which gives consistent estimates of the regression parameters and of their variance under mild assumptions about the time dependence.
Journal ArticleDOI
Longitudinal data analysis for discrete and continuous outcomes.
Scott L. Zeger,Kung-Yee Liang +1 more
TL;DR: A class of generalized estimating equations (GEEs) for the regression parameters is proposed, extensions of those used in quasi-likelihood methods which have solutions which are consistent and asymptotically Gaussian even when the time dependence is misspecified as the authors often expect.
Journal ArticleDOI
Correlated binary regression with covariates specific to each binary observation.
TL;DR: It is argued that binary response models that condition on some or all binary responses in a given "block" are useful for studying certain types of dependencies, but not for the estimation of marginal response probabilities or pairwise correlations.
Journal ArticleDOI
Modelling multivariate binary data with alternating logistic regressions
TL;DR: This article proposed an alternative approach, alternating logistic regressions, for simultaneously regressing the response on explanatory variables as well as modelling the association among responses in terms of pairwise odds ratios.