Guolo, Annamaria Pesantez Cabrera, Tania Erika
Published in
The International Journal of Biostatistics
Bivariate random-effects models represent an established approach for meta-analysis of accuracy measures of a diagnostic test, which are typically given by sensitivity and specificity. A recent formulation of the classical model describes the test accuracy in terms of study-specific Receiver Operating Characteristics curves. In this way, the result...
Savy, Nicolas Moodie, Erica EM Drouet, Isabelle Chambaz, Antoine Falissard, Bruno Kosorok, Michael R. Krakow, Elizabeth F. Mayo, Deborah G. Senn, Stephen Van der Laan, Mark
...
Published in
The International Journal of Biostatistics
SMAC 2021 was a webconference organized in June 2021. The aim of this conference was to bring together data scientists, (bio)statisticians, philosophers, and any person interested in the questions of causality and Bayesian statistics, ranging from technical to philosophical aspects. This webconference consisted of keynote speakers and contributed s...
Rodriguez Duque, Daniel Moodie, Erica E. M. Stephens, David A.
Published in
The International Journal of Biostatistics
In this work, we examine recently developed methods for Bayesian inference of optimal dynamic treatment regimes (DTRs). DTRs are a set of treatment decision rules aimed at tailoring patient care to patient-specific characteristics, thereby falling within the realm of precision medicine. In this field, researchers seek to tailor therapy with the int...
Pantazis, Lucio José García, Rafael Antonio
Published in
The International Journal of Biostatistics
Many health care professionals and institutions manage longitudinal databases, involving follow-ups for different patients over time. Longitudinal data frequently manifest additional complexities such as high variability, correlated measurements and missing data. Mixed effects models have been widely used to overcome these difficulties. This work p...
Shirozhan, Masoumeh Mamode Khan, Naushad A. Kokonendji, Célestin C.
Published in
The International Journal of Biostatistics
This paper proposes a new flexible discrete triplet Lindley model that is constructed from the balanced discretization principle of the extended Lindley distribution. This model has several appealing statistical properties in terms of providing exact and closed form moment expressions and handling all forms of dispersion. Due to these, this paper e...
Moodie, Erica E. M.
Published in
The International Journal of Biostatistics
In this paper, we review some important early developments on causal inference in medical statistics and epidemiology that were inspired by questions in oncology. We examine two classical examples from the literature and point to a current area of ongoing methodological development, namely the estimation of optimal adaptive treatment strategies. Wh...
John, Majnu Lencz, Todd
Published in
The International Journal of Biostatistics
Current research suggests that hundreds to thousands of single nucleotide polymorphisms (SNPs) with small to modest effect sizes contribute to the genetic basis of many disorders, a phenomenon labeled as polygenicity. Additionally, many such disorders demonstrate polygenic overlap, in which risk alleles are shared at associated genetic loci. A simp...
Krakow, Elizabeth F.
Published in
The International Journal of Biostatistics
St-Pierre, Julien Oualkacha, Karim
Published in
The International Journal of Biostatistics
In genome wide association studies (GWAS), researchers are often dealing with dichotomous and non-normally distributed traits, or a mixture of discrete-continuous traits. However, most of the current region-based methods rely on multivariate linear mixed models (mvLMMs) and assume a multivariate normal distribution for the phenotypes of interest. H...
Pourmohammadi, Reza Abouei, Jamshid Anpalagan, Alagan
Published in
The International Journal of Biostatistics
Third generation sequencing technologies such as Pacific Biosciences and Oxford Nanopore provide faster, cost-effective and simpler assembly process generating longer reads than the ones in the next generation sequencing. However, the error rates of these long reads are higher than those of the short reads, resulting in an error correcting process ...
