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Showing 1 - 200 of 370 Journals sorted alphabetically
Acta Biochimica et Biophysica Sinica     Hybrid Journal   (Followers: 6, SJR: 0.881, h-index: 38)
Adaptation     Hybrid Journal   (Followers: 8, SJR: 0.111, h-index: 4)
Aesthetic Surgery J.     Hybrid Journal   (Followers: 6, SJR: 1.538, h-index: 35)
African Affairs     Hybrid Journal   (Followers: 57, SJR: 1.512, h-index: 46)
Age and Ageing     Hybrid Journal   (Followers: 82, SJR: 1.611, h-index: 107)
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American Entomologist     Full-text available via subscription   (Followers: 6)
American Historical Review     Hybrid Journal   (Followers: 129, SJR: 0.652, h-index: 43)
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American J. of Jurisprudence     Hybrid Journal   (Followers: 15)
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Bioscience Horizons : The National Undergraduate Research J.     Open Access   (Followers: 1, SJR: 0.213, h-index: 9)
Biostatistics     Hybrid Journal   (Followers: 16, SJR: 1.955, h-index: 55)
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Brain     Hybrid Journal   (Followers: 61, SJR: 6.097, h-index: 264)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 45, SJR: 4.086, h-index: 73)
Briefings in Functional Genomics     Hybrid Journal   (Followers: 4, SJR: 1.771, h-index: 50)
British J. for the Philosophy of Science     Hybrid Journal   (Followers: 33, SJR: 1.267, h-index: 38)
British J. of Aesthetics     Hybrid Journal   (Followers: 25, SJR: 0.217, h-index: 18)
British J. of Criminology     Hybrid Journal   (Followers: 510, SJR: 1.373, h-index: 62)
British J. of Social Work     Hybrid Journal   (Followers: 79, SJR: 0.771, h-index: 53)
British Medical Bulletin     Hybrid Journal   (Followers: 7, SJR: 1.391, h-index: 84)
British Yearbook of Intl. Law     Hybrid Journal   (Followers: 27)
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Cambridge J. of Economics     Hybrid Journal   (Followers: 56, SJR: 0.957, h-index: 59)
Cambridge J. of Regions, Economy and Society     Hybrid Journal   (Followers: 9, SJR: 1.067, h-index: 22)
Cambridge Quarterly     Hybrid Journal   (Followers: 10, SJR: 0.1, h-index: 7)
Capital Markets Law J.     Hybrid Journal  
Carcinogenesis     Hybrid Journal   (Followers: 2, SJR: 2.439, h-index: 167)
Cardiovascular Research     Hybrid Journal   (Followers: 11, SJR: 2.897, h-index: 175)
Cerebral Cortex     Hybrid Journal   (Followers: 39, SJR: 4.827, h-index: 192)
CESifo Economic Studies     Hybrid Journal   (Followers: 16, SJR: 0.501, h-index: 19)
Chemical Senses     Hybrid Journal   (Followers: 1, SJR: 1.436, h-index: 76)
Children and Schools     Hybrid Journal   (Followers: 6, SJR: 0.211, h-index: 18)
Chinese J. of Comparative Law     Hybrid Journal   (Followers: 3)
Chinese J. of Intl. Law     Hybrid Journal   (Followers: 21, SJR: 0.737, h-index: 11)
Chinese J. of Intl. Politics     Hybrid Journal   (Followers: 8, SJR: 1.238, h-index: 15)
Christian Bioethics: Non-Ecumenical Studies in Medical Morality     Hybrid Journal   (Followers: 11, SJR: 0.191, h-index: 8)
Classical Receptions J.     Hybrid Journal   (Followers: 17, SJR: 0.1, h-index: 3)
Clinical Infectious Diseases     Hybrid Journal   (Followers: 58, SJR: 4.742, h-index: 261)
Clinical Kidney J.     Open Access   (Followers: 4, SJR: 0.338, h-index: 19)
Community Development J.     Hybrid Journal   (Followers: 24, SJR: 0.47, h-index: 28)
Computer J.     Hybrid Journal   (Followers: 7, SJR: 0.371, h-index: 47)
Conservation Physiology     Open Access   (Followers: 2)
Contemporary Women's Writing     Hybrid Journal   (Followers: 11, SJR: 0.111, h-index: 3)
Contributions to Political Economy     Hybrid Journal   (Followers: 6, SJR: 0.313, h-index: 10)
Critical Values     Full-text available via subscription  
Current Legal Problems     Hybrid Journal   (Followers: 25)
Current Zoology     Full-text available via subscription   (SJR: 0.999, h-index: 20)
Database : The J. of Biological Databases and Curation     Open Access   (Followers: 11, SJR: 1.068, h-index: 24)
Digital Scholarship in the Humanities     Hybrid Journal   (Followers: 12)
Diplomatic History     Hybrid Journal   (Followers: 18, SJR: 0.296, h-index: 22)
DNA Research     Open Access   (Followers: 4, SJR: 2.42, h-index: 77)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 3)
Early Music     Hybrid Journal   (Followers: 14, SJR: 0.124, h-index: 11)
Economic Policy     Hybrid Journal   (Followers: 54, SJR: 2.052, h-index: 52)
ELT J.     Hybrid Journal   (Followers: 25, SJR: 1.26, h-index: 23)
English Historical Review     Hybrid Journal   (Followers: 46, SJR: 0.311, h-index: 10)
English: J. of the English Association     Hybrid Journal   (Followers: 13, SJR: 0.144, h-index: 3)
Environmental Entomology     Full-text available via subscription   (Followers: 11, SJR: 0.791, h-index: 66)
Environmental Epigenetics     Open Access   (Followers: 1)
Environmental History     Hybrid Journal   (Followers: 25, SJR: 0.197, h-index: 25)
EP-Europace     Hybrid Journal   (Followers: 2, SJR: 2.201, h-index: 71)
Epidemiologic Reviews     Hybrid Journal   (Followers: 10, SJR: 3.917, h-index: 81)
ESHRE Monographs     Hybrid Journal  
Essays in Criticism     Hybrid Journal   (Followers: 15, SJR: 0.1, h-index: 6)
European Heart J.     Hybrid Journal   (Followers: 47, SJR: 6.997, h-index: 227)
European Heart J. - Cardiovascular Imaging     Hybrid Journal   (Followers: 9, SJR: 2.044, h-index: 58)
European Heart J. - Cardiovascular Pharmacotherapy     Full-text available via subscription   (Followers: 1)
European Heart J. - Quality of Care and Clinical Outcomes     Hybrid Journal  
European Heart J. Supplements     Hybrid Journal   (Followers: 8, SJR: 0.152, h-index: 31)
European J. of Cardio-Thoracic Surgery     Hybrid Journal   (Followers: 8, SJR: 1.568, h-index: 104)
European J. of Intl. Law     Hybrid Journal   (Followers: 149, SJR: 0.722, h-index: 38)
European J. of Orthodontics     Hybrid Journal   (Followers: 4, SJR: 1.09, h-index: 60)
European J. of Public Health     Hybrid Journal   (Followers: 22, SJR: 1.284, h-index: 64)
European Review of Agricultural Economics     Hybrid Journal   (Followers: 12, SJR: 1.549, h-index: 42)
European Review of Economic History     Hybrid Journal   (Followers: 27, SJR: 0.628, h-index: 24)
European Sociological Review     Hybrid Journal   (Followers: 39, SJR: 2.061, h-index: 53)
Evolution, Medicine, and Public Health     Open Access   (Followers: 11)
Family Practice     Hybrid Journal   (Followers: 12, SJR: 1.048, h-index: 77)
Fems Microbiology Ecology     Hybrid Journal   (Followers: 8, SJR: 1.687, h-index: 115)
Fems Microbiology Letters     Hybrid Journal   (Followers: 20, SJR: 1.126, h-index: 118)
Fems Microbiology Reviews     Hybrid Journal   (Followers: 25, SJR: 7.587, h-index: 150)
Fems Yeast Research     Hybrid Journal   (Followers: 13, SJR: 1.213, h-index: 66)
Foreign Policy Analysis     Hybrid Journal   (Followers: 21, SJR: 0.859, h-index: 10)
Forestry: An Intl. J. of Forest Research     Hybrid Journal   (Followers: 16, SJR: 0.903, h-index: 44)
Forum for Modern Language Studies     Hybrid Journal   (Followers: 6, SJR: 0.108, h-index: 6)
French History     Hybrid Journal   (Followers: 30, SJR: 0.123, h-index: 10)
French Studies     Hybrid Journal   (Followers: 19, SJR: 0.119, h-index: 7)
French Studies Bulletin     Hybrid Journal   (Followers: 10, SJR: 0.102, h-index: 3)
Gastroenterology Report     Open Access   (Followers: 2)
Genome Biology and Evolution     Open Access   (Followers: 10, SJR: 3.22, h-index: 39)
Geophysical J. Intl.     Hybrid Journal   (Followers: 31, SJR: 1.839, h-index: 119)
German History     Hybrid Journal   (Followers: 25, SJR: 0.437, h-index: 13)
GigaScience     Open Access   (Followers: 3)
Global Summitry     Hybrid Journal  
Glycobiology     Hybrid Journal   (Followers: 14, SJR: 1.692, h-index: 101)
Health and Social Work     Hybrid Journal   (Followers: 46, SJR: 0.505, h-index: 40)
Health Education Research     Hybrid Journal   (Followers: 12, SJR: 0.814, h-index: 80)
Health Policy and Planning     Hybrid Journal   (Followers: 21, SJR: 1.628, h-index: 66)
Health Promotion Intl.     Hybrid Journal   (Followers: 20, SJR: 0.664, h-index: 60)
History Workshop J.     Hybrid Journal   (Followers: 27, SJR: 0.313, h-index: 20)
Holocaust and Genocide Studies     Hybrid Journal   (Followers: 23, SJR: 0.115, h-index: 13)
Human Molecular Genetics     Hybrid Journal   (Followers: 9, SJR: 4.288, h-index: 233)
Human Reproduction     Hybrid Journal   (Followers: 79, SJR: 2.271, h-index: 179)
Human Reproduction Update     Hybrid Journal   (Followers: 19, SJR: 4.678, h-index: 128)
Human Rights Law Review     Hybrid Journal   (Followers: 58, SJR: 0.7, h-index: 21)
ICES J. of Marine Science: J. du Conseil     Hybrid Journal   (Followers: 54, SJR: 1.233, h-index: 88)
ICSID Review     Hybrid Journal   (Followers: 9)
ILAR J.     Hybrid Journal   (Followers: 1, SJR: 1.099, h-index: 51)
IMA J. of Applied Mathematics     Hybrid Journal   (SJR: 0.329, h-index: 26)
IMA J. of Management Mathematics     Hybrid Journal   (Followers: 2, SJR: 0.351, h-index: 20)
IMA J. of Mathematical Control and Information     Hybrid Journal   (Followers: 2, SJR: 0.661, h-index: 28)
IMA J. of Numerical Analysis - advance access     Hybrid Journal   (SJR: 2.032, h-index: 44)
Industrial and Corporate Change     Hybrid Journal   (Followers: 8, SJR: 1.37, h-index: 81)
Industrial Law J.     Hybrid Journal   (Followers: 29, SJR: 0.184, h-index: 15)
Information and Inference     Free  
Integrative and Comparative Biology     Hybrid Journal   (Followers: 8, SJR: 1.911, h-index: 90)
Interacting with Computers     Hybrid Journal   (Followers: 10, SJR: 0.529, h-index: 59)
Interactive CardioVascular and Thoracic Surgery     Hybrid Journal   (Followers: 4, SJR: 0.743, h-index: 35)
Intl. Affairs     Hybrid Journal   (Followers: 51, SJR: 1.264, h-index: 53)
Intl. Data Privacy Law     Hybrid Journal   (Followers: 27)
Intl. Health     Hybrid Journal   (Followers: 4, SJR: 0.835, h-index: 15)
Intl. Immunology     Hybrid Journal   (Followers: 3, SJR: 1.613, h-index: 111)
Intl. J. for Quality in Health Care     Hybrid Journal   (Followers: 32, SJR: 1.593, h-index: 69)
Intl. J. of Constitutional Law     Hybrid Journal   (Followers: 59, SJR: 0.613, h-index: 19)
Intl. J. of Epidemiology     Hybrid Journal   (Followers: 126, SJR: 4.381, h-index: 145)
Intl. J. of Law and Information Technology     Hybrid Journal   (Followers: 3, SJR: 0.247, h-index: 8)
Intl. J. of Law, Policy and the Family     Hybrid Journal   (Followers: 28, SJR: 0.307, h-index: 15)
Intl. J. of Lexicography     Hybrid Journal   (Followers: 8, SJR: 0.404, h-index: 18)
Intl. J. of Low-Carbon Technologies     Open Access   (Followers: 1, SJR: 0.457, h-index: 12)
Intl. J. of Neuropsychopharmacology     Open Access   (Followers: 3, SJR: 1.69, h-index: 79)
Intl. J. of Public Opinion Research     Hybrid Journal   (Followers: 8, SJR: 0.906, h-index: 33)
Intl. J. of Refugee Law     Hybrid Journal   (Followers: 32, SJR: 0.231, h-index: 21)
Intl. J. of Transitional Justice     Hybrid Journal   (Followers: 13, SJR: 0.833, h-index: 12)
Intl. Mathematics Research Notices     Hybrid Journal   (Followers: 1, SJR: 2.052, h-index: 42)
Intl. Political Sociology     Hybrid Journal   (Followers: 30, SJR: 1.339, h-index: 19)
Intl. Relations of the Asia-Pacific     Hybrid Journal   (Followers: 17, SJR: 0.539, h-index: 17)
Intl. Studies Perspectives     Hybrid Journal   (Followers: 7, SJR: 0.998, h-index: 28)
Intl. Studies Quarterly     Hybrid Journal   (Followers: 36, SJR: 2.184, h-index: 68)
Intl. Studies Review     Hybrid Journal   (Followers: 17, SJR: 0.783, h-index: 38)
ISLE: Interdisciplinary Studies in Literature and Environment     Hybrid Journal   (Followers: 1, SJR: 0.155, h-index: 4)
ITNOW     Hybrid Journal   (Followers: 2, SJR: 0.102, h-index: 4)
J. of African Economies     Hybrid Journal   (Followers: 15, SJR: 0.647, h-index: 30)
J. of American History     Hybrid Journal   (Followers: 39, SJR: 0.286, h-index: 34)
J. of Analytical Toxicology     Hybrid Journal   (Followers: 13, SJR: 1.038, h-index: 60)
J. of Antimicrobial Chemotherapy     Hybrid Journal   (Followers: 17, SJR: 2.157, h-index: 149)
J. of Antitrust Enforcement     Hybrid Journal   (Followers: 1)
J. of Applied Poultry Research     Hybrid Journal   (Followers: 3, SJR: 0.563, h-index: 43)
J. of Biochemistry     Hybrid Journal   (Followers: 43, SJR: 1.341, h-index: 96)
J. of Chromatographic Science     Hybrid Journal   (Followers: 16, SJR: 0.448, h-index: 42)
J. of Church and State     Hybrid Journal   (Followers: 11, SJR: 0.167, h-index: 11)
J. of Competition Law and Economics     Hybrid Journal   (Followers: 34, SJR: 0.442, h-index: 16)
J. of Complex Networks     Hybrid Journal   (Followers: 1, SJR: 1.165, h-index: 5)
J. of Conflict and Security Law     Hybrid Journal   (Followers: 12, SJR: 0.196, h-index: 15)
J. of Consumer Research     Full-text available via subscription   (Followers: 41, SJR: 4.896, h-index: 121)
J. of Crohn's and Colitis     Hybrid Journal   (Followers: 9, SJR: 1.543, h-index: 37)
J. of Cybersecurity     Hybrid Journal   (Followers: 3)
J. of Deaf Studies and Deaf Education     Hybrid Journal   (Followers: 8, SJR: 0.69, h-index: 36)
J. of Design History     Hybrid Journal   (Followers: 15, SJR: 0.166, h-index: 14)
J. of Economic Entomology     Full-text available via subscription   (Followers: 6, SJR: 0.894, h-index: 76)
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J. of Financial Econometrics     Hybrid Journal   (Followers: 21, SJR: 1.314, h-index: 27)
J. of Global Security Studies     Hybrid Journal   (Followers: 2)
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J. of Hindu Studies     Hybrid Journal   (Followers: 7, SJR: 0.186, h-index: 3)
J. of Hip Preservation Surgery     Open Access  
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J. of Infectious Diseases     Hybrid Journal   (Followers: 40, SJR: 4, h-index: 209)
J. of Insect Science     Open Access   (Followers: 9, SJR: 0.388, h-index: 31)

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Journal Cover Biostatistics
  [SJR: 1.955]   [H-I: 55]   [16 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1465-4644 - ISSN (Online) 1468-4357
   Published by Oxford University Press Homepage  [370 journals]
  • Biostatistics Reviewer List 2016
    • First page: 195
      Abstract: Aalen, Odd
      PubDate: 2017-01-18
      DOI: 10.1093/biostatistics/kxw058
  • Prediction of cancer drug sensitivity using high-dimensional omic features
    • Authors: Chen T; Sun W.
      First page: 1
      Abstract: SummaryA large number of cancer drugs have been developed to target particular genes/pathways that are crucial for cancer growth. Drugs that share a molecular target may also have some common predictive omic features, e.g., somatic mutations or gene expression. Therefore, it is desirable to analyze these drugs as a group to identify the associated omic features, which may provide biological insights into the underlying drug response. Furthermore, these omic features may be robust predictors for any drug sharing the same target. The high dimensionality and the strong correlations among the omic features are the main challenges of this task. Motivated by this problem, we develop a new method for high-dimensional bilevel feature selection using a group of response variables that may share a common set of predictors in addition to their individual predictors. Simulation results show that our method has a substantially higher sensitivity and specificity than existing methods. We apply our method to two large-scale drug sensitivity studies in cancer cell lines. Both within-study and between-study validation demonstrate the good efficacy of our method.
      PubDate: 2016-06-20
      DOI: 10.1093/biostatistics/kxw022
  • On the choice of time scales in competing risks predictions
    • Authors: Lee M; Gouskova NA, Feuer EJ, et al.
      First page: 15
      Abstract: In the standard analysis of competing risks data, proportional hazards models are fit to the cause-specific hazard functions for all causes on the same time scale. These regression analyses are the foundation for predictions of cause-specific cumulative incidence functions based on combining the estimated cause-specific hazard functions. However, in predictions arising from disease registries, where only subjects with disease enter the database, disease-related mortality may be more naturally modeled on the time since diagnosis time scale while death from other causes may be more naturally modeled on the age time scale. The single time scale methodology may be biased if an incorrect time scale is employed for one of the causes and an alternative methodology is not available. We propose inferences for the cumulative incidence function in which regression models for the cause-specific hazard functions may be specified on different time scales. Using the disease registry data, the analysis of other cause mortality on the age scale requires left truncating the event time at the age of disease diagnosis, complicating the analysis. In addition, standard Martingale theory is not applicable when combining regression models on different time scales. We establish that the covariate conditional predictions are consistent and asymptotically normal using empirical process techniques and propose consistent variance estimators for constructing confidence intervals. Simulation studies show that the proposed two time scales method performs well, outperforming the single time-scale predictions when the time scale is misspecified. The methods are illustrated with stage III colon cancer data obtained from the Surveillance, Epidemiology, and End Results program of National Cancer Institute.
      PubDate: 2016-06-22
      DOI: 10.1093/biostatistics/kxw024
  • A Bayesian nonparametric approach to marginal structural models for point
           treatments and a continuous or survival outcome
    • Authors: Roy J; Lum KJ, Daniels MJ.
      First page: 32
      Abstract: Marginal structural models (MSMs) are a general class of causal models for specifying the average effect of treatment on an outcome. These models can accommodate discrete or continuous treatments, as well as treatment effect heterogeneity (causal effect modification). The literature on estimation of MSM parameters has been dominated by semiparametric estimation methods, such as inverse probability of treatment weighted (IPTW). Likelihood-based methods have received little development, probably in part due to the need to integrate out confounders from the likelihood and due to reluctance to make parametric modeling assumptions. In this article we develop a fully Bayesian MSM for continuous and survival outcomes. In particular, we take a Bayesian nonparametric (BNP) approach, using a combination of a dependent Dirichlet process and Gaussian process to model the observed data. The BNP approach, like semiparametric methods such as IPTW, does not require specifying a parametric outcome distribution. Moreover, by using a likelihood-based method, there are potential gains in efficiency over semiparametric methods. An additional advantage of taking a fully Bayesian approach is the ability to account for uncertainty in our (uncheckable) identifying assumption. To this end, we propose informative prior distributions that can be used to capture uncertainty about the identifying “no unmeasured confounders” assumption. Thus, posterior inference about the causal effect parameters can reflect the degree of uncertainty about this assumption. The performance of the methodology is evaluated in several simulation studies. The results show substantial efficiency gains over semiparametric methods, and very little efficiency loss over correctly specified maximum likelihood estimates. The method is also applied to data from a study on neurocognitive performance in HIV-infected women and a study of the comparative effectiveness of antihypertensive drug classes.
      PubDate: 2016-06-26
      DOI: 10.1093/biostatistics/kxw029
  • Nonparametric binary instrumental variable analysis of competing risks
    • Authors: Richardson A; Hudgens MG, Fine JP, et al.
      First page: 48
      Abstract: In both observational studies and randomized trials with noncompliance, unmeasured confounding may exist which may bias treatment effect estimates. Instrumental variables (IV) are a popular technique for addressing such confounding, enabling consistent estimation of causal effects. This paper proposes nonparametric IV estimators for censored time to event data that may be subject to competing risks. A simple, plug-in estimator is introduced using nonparametric estimators of the cumulative incidence function, with confidence intervals derived using asymptotic theory. To provide an overall test of the treatment effect, an integrated weighted difference statistic is suggested, which is applicable to data with and without competing risks. Simulation studies demonstrate that the methods perform well with realistic samples sizes. The methods are applied to assess the effect of infant or maternal antiretroviral therapy on transmission of HIV from mother to child via breastfeeding using data from a large, recently completed randomized trial in Malawi where noncompliance with assigned treatment may confound treatment effect estimates.
      PubDate: 2016-06-26
      DOI: 10.1093/biostatistics/kxw023
  • Semiparametric density ratio modeling of survival data from a prevalent
    • Authors: Zhu H; Ning J, Shen Y, et al.
      First page: 62
      Abstract: In this article, we consider methods for assessing covariate effects on survival outcome in the target population when data are collected under prevalent sampling. We investigate a flexible semiparametric density ratio model without the constraints of the constant disease incidence rate and discrete covariates as required in Shen and others 2012. For inference, we introduce two likelihood approaches with distinct computational algorithms. We first develop a full likelihood approach to obtain the most efficient estimators by an iterative algorithm. Under the density ratio model, we exploit the invariance property of uncensored failure times from the prevalent cohort and also propose a computationally convenient estimation procedure that uses a conditional pairwise likelihood. The empirical performance and efficiency of the two approaches are evaluated through simulation studies. The proposed methods are applied to the Surveillance, Epidemiology, and End Results Medicare linked data for women diagnosed with stage IV breast cancer.
      PubDate: 2016-06-26
      DOI: 10.1093/biostatistics/kxw028
  • A fully nonparametric estimator of the marginal survival function based on
           case–control clustered age-at-onset data
    • Authors: Gorfine M; Bordo N, Hsu L.
      First page: 76
      Abstract: SummaryConsider a popular case–control family study where individuals with a disease under study (case probands) and individuals who do not have the disease (control probands) are randomly sampled from a well-defined population. Possibly right-censored age at onset and disease status are observed for both probands and their relatives. For example, case probands are men diagnosed with prostate cancer, control probands are men free of prostate cancer, and the prostate cancer history of the fathers of the probands is also collected. Inherited genetic susceptibility, shared environment, and common behavior lead to correlation among the outcomes within a family. In this article, a novel nonparametric estimator of the marginal survival function is provided. The estimator is defined in the presence of intra-cluster dependence, and is based on consistent smoothed kernel estimators of conditional survival functions. By simulation, it is shown that the proposed estimator performs very well in terms of bias. The utility of the estimator is illustrated by the analysis of case–control family data of early onset prostate cancer. To our knowledge, this is the first article that provides a fully nonparametric marginal survival estimator based on case–control clustered age-at-onset data.
      PubDate: 2016-07-19
      DOI: 10.1093/biostatistics/kxw032
  • Weighted false discovery rate controlling procedures for clinical trials
    • Authors: Benjamini Y; Cohen R.
      First page: 91
      Abstract: SummaryHaving identified that the lack of replicability of results in earlier phases of clinical medical research stems largely from unattended selective inference, we offer a new hierarchical weighted false discovery rate controlling testing procedure alongside the single-level weighted procedure. These address the special structure of clinical research, where the comparisons of treatments involve both primary and secondary endpoints, by assigning weights that reflect the relative importance of the endpoints in the error being controlled. In the hierarchical method, the primary endpoints and a properly weighted intersection hypothesis that represents all secondary endpoints are tested. Should the intersection hypothesis be among the rejected, individual secondary endpoints are tested. We identify configurations where each of the two procedures has the advantage. Both offer higher power than competing hierarchical (gatekeeper) familywise error-rate controlling procedures being used for drug approval. By their design, the advantage of the proposed methods is the increased power to discover effects on secondary endpoints, without giving up the rigor of addressing their multiplicity.
      PubDate: 2016-07-21
      DOI: 10.1093/biostatistics/kxw030
  • Generated effect modifiers (GEM’s) in randomized clinical trials
    • Authors: Petkova E; Tarpey T, Su Z, et al.
      First page: 105
      Abstract: In a randomized clinical trial (RCT), it is often of interest not only to estimate the effect of various treatments on the outcome, but also to determine whether any patient characteristic has a different relationship with the outcome, depending on treatment. In regression models for the outcome, if there is a non-zero interaction between treatment and a predictor, that predictor is called an “effect modifier”. Identification of such effect modifiers is crucial as we move towards precision medicine, that is, optimizing individual treatment assignment based on patient measurements assessed when presenting for treatment. In most settings, there will be several baseline predictor variables that could potentially modify the treatment effects. This article proposes optimal methods of constructing a composite variable (defined as a linear combination of pre-treatment patient characteristics) in order to generate an effect modifier in an RCT setting. Several criteria are considered for generating effect modifiers and their performance is studied via simulations. An example from a RCT is provided for illustration.
      PubDate: 2016-07-27
      DOI: 10.1093/biostatistics/kxw035
  • A unified powerful set-based test for sequencing data analysis of GxE
    • Authors: Su Y; Di C, Hsu L, et al.
      First page: 119
      Abstract: SummaryThe development of next-generation sequencing technologies has allowed researchers to study comprehensively the contribution of genetic variation particularly rare variants to complex diseases. To date many sequencing analyses of rare variants have focused on marginal genetic effects and have not explored the potential role environmental factors play in modifying genetic risk. Analysis of gene–environment interaction (GxE) for rare variants poses considerable challenges because of variant rarity and paucity of subjects who carry the variants while being exposed. To tackle this challenge, we propose a hierarchical model to jointly assess the GxE effects of a set of rare variants for example, in a gene or regulatory region, leveraging the information across the variants. Under this model, GxE is modeled by two components. The first component incorporates variant functional information as weights to calculate the weighted burden of variant alleles across variants, and then assess their GxE interaction with the environmental factor. Since this information is a priori known, this component is fixed effects in the model. The second component involves residual GxE effects that have not been accounted for by the fixed effects. In this component, the residual GxE effects are postulated to follow an unspecified distribution with mean 0 and variance $\tau^2$. We develop a novel testing procedure by deriving two independent score statistics for the fixed effects and the variance component separately. We propose two data-adaptive combination approaches for combining these two score statistics and establish the asymptotic distributions. An extensive simulation study shows that the proposed approaches maintain the correct type I error and the power is comparable to or better than existing methods under a wide range of scenarios. Finally we illustrate the proposed methods by a exome-wide GxE analysis with NSAIDs use in colorectal cancer.
      PubDate: 2016-07-28
      DOI: 10.1093/biostatistics/kxw034
  • A quantile regression model for failure-time data with time-dependent
    • Authors: Gorfine M; Goldberg Y, Ritov Y.
      First page: 132
      Abstract: SummarySince survival data occur over time, often important covariates that we wish to consider also change over time. Such covariates are referred as time-dependent covariates. Quantile regression offers flexible modeling of survival data by allowing the covariates to vary with quantiles. This article provides a novel quantile regression model accommodating time-dependent covariates, for analyzing survival data subject to right censoring. Our simple estimation technique assumes the existence of instrumental variables. In addition, we present a doubly-robust estimator in the sense of Robins and Rotnitzky (1992, Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell, N. P., Dietz, K. and Farewell, V. T. (editors), AIDS Epidemiology. Boston: Birkhaäuser, pp. 297–331.). The asymptotic properties of the estimators are rigorously studied. Finite-sample properties are demonstrated by a simulation study. The utility of the proposed methodology is demonstrated using the Stanford heart transplant dataset.
      PubDate: 2016-08-02
      DOI: 10.1093/biostatistics/kxw036
  • Simultaneous detection and estimation of trait associations with genomic
    • Authors: Morrison J; Simon N, Witten D.
      First page: 147
      Abstract: SummaryGenomic phenotypes, such as DNA methylation and chromatin accessibility, can be used to characterize the transcriptional and regulatory activity of DNA within a cell. Recent technological advances have made it possible to measure such phenotypes very densely. This density often results in spatial structure, in the sense that measurements at nearby sites are very similar. In this article, we consider the task of comparing genomic phenotypes across experimental conditions, cell types, or disease subgroups. We propose a new method, Joint Adaptive Differential Estimation (JADE), which leverages the spatial structure inherent to genomic phenotypes. JADE simultaneously estimates smooth underlying group average genomic phenotype profiles and detects regions in which the average profile differs between groups. We evaluate JADE’s performance in several biologically plausible simulation settings. We also consider an application to the detection of regions with differential methylation between mature skeletal muscle cells, myotubes, and myoblasts.
      PubDate: 2016-08-05
      DOI: 10.1093/biostatistics/kxw033
  • Integrative clustering of multi-level omics data for disease subtype
           discovery using sequential double regularization
    • Authors: Kim S; Oesterreich S, Kim S, et al.
      First page: 165
      Abstract: SummaryWith the rapid advances in technologies of microarray and massively parallel sequencing, data of multiple omics sources from a large patient cohort are now frequently seen in many consortium studies. Effective multi-level omics data integration has brought new statistical challenges. One important biological objective of such integrative analysis is to cluster patients in order to identify clinically relevant disease subtypes, which will form basis for tailored treatment and personalized medicine. Several methods have been proposed in the literature for this purpose, including the popular iCluster method used in many cancer applications. When clustering high-dimensional omics data, effective feature selection is critical for better clustering accuracy and biological interpretation. It is also common that a portion of “scattered samples” has patterns distinct from all major clusters and should not be assigned into any cluster as they may represent a rare disease subcategory or be in transition between disease subtypes. In this paper, we firstly propose to improve feature selection of the iCluster factor model by an overlapping sparse group lasso penalty on the omics features using prior knowledge of inter-omics regulatory flows. We then perform regularization over samples to allow clustering with scattered samples and generate tight clusters. The proposed group structured tight iCluster method will be evaluated by two real breast cancer examples and simulations to demonstrate its improved clustering accuracy, biological interpretation, and ability to generate coherent tight clusters.
      PubDate: 2016-08-22
      DOI: 10.1093/biostatistics/kxw039
  • Nonparametric overdose control with late-onset toxicity in phase I
           clinical trials
    • Authors: Lin R; Yin G.
      First page: 180
      Abstract: Under the framework of Bayesian model selection, we propose a nonparametric overdose control (NOC) design for dose finding in phase I clinical trials. Each dose assignment is guided via a feasibility bound, which thereby can control the number of patients allocated to excessively toxic dose levels. Several aspects of the NOC design are explored, including the coherence property in dose assignment, calibration of design parameters, and selection of the maximum tolerated dose (MTD). We further propose a fractional NOC (fNOC) design in conjunction with a so-called fractional imputation approach, to account for late-onset toxicity outcomes. Extensive simulation studies have been conducted to show that both the NOC and fNOC designs have robust and satisfactory finite-sample performance compared with the existing dose-finding designs. The proposed methods also possess several desirable properties: treating patients more safely and also neutralizing the aggressive escalation to overly toxic doses when the toxicity outcomes are late-onset. The fNOC design is exemplified with a real cancer phase I trial.
      PubDate: 2016-08-22
      DOI: 10.1093/biostatistics/kxw038
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