Samiran Sinha
Texas A&M University
51 Papers
232 Citations
Samiran Sinha is an academic researcher from Texas A&M University. The author has contributed to research in topics: Covariate & Estimator. The author has an hindex of 13, co-authored 43 publications. Previous affiliations of Samiran Sinha include University of Florida.
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Papers
Prediction Error of Small Area Predictors Shrinking Both Means and Variances
TL;DR: In this article, a new approach for small area estimation based on a joint modelling of mean and variances is proposed, where model parameters are estimated via expectation-maximization algorithm and the conditional mean squared error is used to evaluate the prediction error.
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CXCL11-CXCR3 Axis Mediates Tumor Lymphatic Cross Talk and Inflammation-Induced Tumor, Promoting Pathways in Head and Neck Cancers.
Subhashree Kumaravel,Sumeet Singh,Sukanya Roy,Lavanya Venkatasamy,Tori White,Samiran Sinha,Shannon Glaser,Stephen Safe,Sanjukta Chakraborty +8 more
TL;DR: A novel mechanism for crosstalk between the LECs and HNSCC tumors through the CXCR3-CXCL11 axis is suggested and the role the triterpenoid CF3 DODA-Me in abrogating several of these tumor promoting pathways is elucidated.
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Bayesian Analysis of Case-Control Studies
TL;DR: A review of existing Bayesian work for analyzing case-control data, some recent advancements and possibilities for future research can be found in this article, with a focus on the use of hierarchical models.
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Two Wrongs Make a Right: Addressing Underreporting in Binary Data from Multiple Sources.
TL;DR: A novel maximum likelihood estimator is proposed that corrects for misclassification in data arising from multiple sources of media-based event data and regularly outperforms current strategies that either neglect mis classification, the unique features of the data-generating process, or both.
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Analysis of cohort studies with multivariate and partially observed disease classification data
TL;DR: Methods for analysis of disease incidence in cohort studies incorporating data on multiple disease traits using a two-stage semiparametric Cox proportional hazards regression model that allows one to examine the heterogeneity in the effect of the covariates by the levels of the different disease traits are developed.
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