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Publisher: Oxford University Press   (Total: 397 journals)

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Showing 1 - 200 of 397 Journals sorted alphabetically
ACS Symposium Series     Full-text available via subscription   (SJR: 0.189, CiteScore: 0)
Acta Biochimica et Biophysica Sinica     Hybrid Journal   (Followers: 5, SJR: 0.79, CiteScore: 2)
Adaptation     Hybrid Journal   (Followers: 9, SJR: 0.143, CiteScore: 0)
Advances in Nutrition     Hybrid Journal   (Followers: 53, SJR: 2.196, CiteScore: 5)
Aesthetic Surgery J.     Hybrid Journal   (Followers: 6, SJR: 1.434, CiteScore: 1)
African Affairs     Hybrid Journal   (Followers: 66, SJR: 1.869, CiteScore: 2)
Age and Ageing     Hybrid Journal   (Followers: 91, SJR: 1.989, CiteScore: 4)
Alcohol and Alcoholism     Hybrid Journal   (Followers: 19, SJR: 1.376, CiteScore: 3)
American Entomologist     Full-text available via subscription   (Followers: 8)
American Historical Review     Hybrid Journal   (Followers: 161, SJR: 0.467, CiteScore: 1)
American J. of Agricultural Economics     Hybrid Journal   (Followers: 45, SJR: 2.113, CiteScore: 3)
American J. of Clinical Nutrition     Hybrid Journal   (Followers: 168, SJR: 3.438, CiteScore: 6)
American J. of Epidemiology     Hybrid Journal   (Followers: 190, SJR: 2.713, CiteScore: 3)
American J. of Hypertension     Hybrid Journal   (Followers: 25, SJR: 1.322, CiteScore: 3)
American J. of Jurisprudence     Hybrid Journal   (Followers: 19, SJR: 0.281, CiteScore: 1)
American J. of Legal History     Full-text available via subscription   (Followers: 8, SJR: 0.116, CiteScore: 0)
American Law and Economics Review     Hybrid Journal   (Followers: 27, SJR: 1.053, CiteScore: 1)
American Literary History     Hybrid Journal   (Followers: 16, SJR: 0.391, CiteScore: 0)
Analysis     Hybrid Journal   (Followers: 22, SJR: 1.038, CiteScore: 1)
Animal Frontiers     Hybrid Journal   (Followers: 1)
Annals of Behavioral Medicine     Hybrid Journal   (Followers: 16, SJR: 1.423, CiteScore: 3)
Annals of Botany     Hybrid Journal   (Followers: 37, SJR: 1.721, CiteScore: 4)
Annals of Oncology     Hybrid Journal   (Followers: 56, SJR: 5.599, CiteScore: 9)
Annals of the Entomological Society of America     Full-text available via subscription   (Followers: 10, SJR: 0.722, CiteScore: 1)
Annals of Work Exposures and Health     Hybrid Journal   (Followers: 34, SJR: 0.728, CiteScore: 2)
Antibody Therapeutics     Open Access  
AoB Plants     Open Access   (Followers: 4, SJR: 1.28, CiteScore: 3)
Applied Economic Perspectives and Policy     Hybrid Journal   (Followers: 18, SJR: 0.858, CiteScore: 2)
Applied Linguistics     Hybrid Journal   (Followers: 58, SJR: 2.987, CiteScore: 3)
Applied Mathematics Research eXpress     Hybrid Journal   (Followers: 1, SJR: 1.241, CiteScore: 1)
Arbitration Intl.     Full-text available via subscription   (Followers: 20)
Arbitration Law Reports and Review     Hybrid Journal   (Followers: 14)
Archives of Clinical Neuropsychology     Hybrid Journal   (Followers: 30, SJR: 0.731, CiteScore: 2)
Aristotelian Society Supplementary Volume     Hybrid Journal   (Followers: 3)
Arthropod Management Tests     Hybrid Journal   (Followers: 2)
Astronomy & Geophysics     Hybrid Journal   (Followers: 44, SJR: 0.146, CiteScore: 0)
Behavioral Ecology     Hybrid Journal   (Followers: 52, SJR: 1.871, CiteScore: 3)
Bioinformatics     Hybrid Journal   (Followers: 327, SJR: 6.14, CiteScore: 8)
Biology Methods and Protocols     Hybrid Journal  
Biology of Reproduction     Full-text available via subscription   (Followers: 9, SJR: 1.446, CiteScore: 3)
Biometrika     Hybrid Journal   (Followers: 20, SJR: 3.485, CiteScore: 2)
BioScience     Hybrid Journal   (Followers: 29, SJR: 2.754, CiteScore: 4)
Bioscience Horizons : The National Undergraduate Research J.     Open Access   (Followers: 1, SJR: 0.146, CiteScore: 0)
Biostatistics     Hybrid Journal   (Followers: 17, SJR: 1.553, CiteScore: 2)
BJA : British J. of Anaesthesia     Hybrid Journal   (Followers: 179, SJR: 2.115, CiteScore: 3)
BJA Education     Hybrid Journal   (Followers: 65)
Brain     Hybrid Journal   (Followers: 68, SJR: 5.858, CiteScore: 7)
Briefings in Bioinformatics     Hybrid Journal   (Followers: 51, SJR: 2.505, CiteScore: 5)
Briefings in Functional Genomics     Hybrid Journal   (Followers: 3, SJR: 2.15, CiteScore: 3)
British J. for the Philosophy of Science     Hybrid Journal   (Followers: 36, SJR: 2.161, CiteScore: 2)
British J. of Aesthetics     Hybrid Journal   (Followers: 25, SJR: 0.508, CiteScore: 1)
British J. of Criminology     Hybrid Journal   (Followers: 600, SJR: 1.828, CiteScore: 3)
British J. of Social Work     Hybrid Journal   (Followers: 85, SJR: 1.019, CiteScore: 2)
British Medical Bulletin     Hybrid Journal   (Followers: 6, SJR: 1.355, CiteScore: 3)
British Yearbook of Intl. Law     Hybrid Journal   (Followers: 33)
Bulletin of the London Mathematical Society     Hybrid Journal   (Followers: 4, SJR: 1.376, CiteScore: 1)
Cambridge J. of Economics     Hybrid Journal   (Followers: 65, SJR: 0.764, CiteScore: 2)
Cambridge J. of Regions, Economy and Society     Hybrid Journal   (Followers: 11, SJR: 2.438, CiteScore: 4)
Cambridge Quarterly     Hybrid Journal   (Followers: 10, SJR: 0.104, CiteScore: 0)
Capital Markets Law J.     Hybrid Journal   (Followers: 2, SJR: 0.222, CiteScore: 0)
Carcinogenesis     Hybrid Journal   (Followers: 2, SJR: 2.135, CiteScore: 5)
Cardiovascular Research     Hybrid Journal   (Followers: 14, SJR: 3.002, CiteScore: 5)
Cerebral Cortex     Hybrid Journal   (Followers: 46, SJR: 3.892, CiteScore: 6)
CESifo Economic Studies     Hybrid Journal   (Followers: 18, SJR: 0.483, CiteScore: 1)
Chemical Senses     Hybrid Journal   (Followers: 1, SJR: 1.42, CiteScore: 3)
Children and Schools     Hybrid Journal   (Followers: 6, SJR: 0.246, CiteScore: 0)
Chinese J. of Comparative Law     Hybrid Journal   (Followers: 5, SJR: 0.412, CiteScore: 0)
Chinese J. of Intl. Law     Hybrid Journal   (Followers: 22, SJR: 0.329, CiteScore: 0)
Chinese J. of Intl. Politics     Hybrid Journal   (Followers: 10, SJR: 1.392, CiteScore: 2)
Christian Bioethics: Non-Ecumenical Studies in Medical Morality     Hybrid Journal   (Followers: 10, SJR: 0.183, CiteScore: 0)
Classical Receptions J.     Hybrid Journal   (Followers: 27, SJR: 0.123, CiteScore: 0)
Clean Energy     Open Access   (Followers: 1)
Clinical Infectious Diseases     Hybrid Journal   (Followers: 70, SJR: 5.051, CiteScore: 5)
Communication Theory     Hybrid Journal   (Followers: 24, SJR: 2.424, CiteScore: 3)
Communication, Culture & Critique     Hybrid Journal   (Followers: 27, SJR: 0.222, CiteScore: 1)
Community Development J.     Hybrid Journal   (Followers: 27, SJR: 0.268, CiteScore: 1)
Computer J.     Hybrid Journal   (Followers: 9, SJR: 0.319, CiteScore: 1)
Conservation Physiology     Open Access   (Followers: 3, SJR: 1.818, CiteScore: 3)
Contemporary Women's Writing     Hybrid Journal   (Followers: 9, SJR: 0.121, CiteScore: 0)
Contributions to Political Economy     Hybrid Journal   (Followers: 5, SJR: 0.906, CiteScore: 1)
Critical Values     Full-text available via subscription  
Current Developments in Nutrition     Open Access   (Followers: 2)
Current Legal Problems     Hybrid Journal   (Followers: 29)
Current Zoology     Full-text available via subscription   (Followers: 3, SJR: 1.164, CiteScore: 2)
Database : The J. of Biological Databases and Curation     Open Access   (Followers: 8, SJR: 1.791, CiteScore: 3)
Digital Scholarship in the Humanities     Hybrid Journal   (Followers: 14, SJR: 0.259, CiteScore: 1)
Diplomatic History     Hybrid Journal   (Followers: 20, SJR: 0.45, CiteScore: 1)
DNA Research     Open Access   (Followers: 5, SJR: 2.866, CiteScore: 6)
Dynamics and Statistics of the Climate System     Open Access   (Followers: 4)
Early Music     Hybrid Journal   (Followers: 16, SJR: 0.139, CiteScore: 0)
Economic Policy     Hybrid Journal   (Followers: 42, SJR: 3.584, CiteScore: 3)
ELT J.     Hybrid Journal   (Followers: 24, SJR: 0.942, CiteScore: 1)
English Historical Review     Hybrid Journal   (Followers: 54, SJR: 0.612, CiteScore: 1)
English: J. of the English Association     Hybrid Journal   (Followers: 15, SJR: 0.1, CiteScore: 0)
Environmental Entomology     Full-text available via subscription   (Followers: 11, SJR: 0.818, CiteScore: 2)
Environmental Epigenetics     Open Access   (Followers: 3)
Environmental History     Hybrid Journal   (Followers: 27, SJR: 0.408, CiteScore: 1)
EP-Europace     Hybrid Journal   (Followers: 3, SJR: 2.748, CiteScore: 4)
Epidemiologic Reviews     Hybrid Journal   (Followers: 9, SJR: 4.505, CiteScore: 8)
ESHRE Monographs     Hybrid Journal  
Essays in Criticism     Hybrid Journal   (Followers: 19, SJR: 0.113, CiteScore: 0)
European Heart J.     Hybrid Journal   (Followers: 63, SJR: 9.315, CiteScore: 9)
European Heart J. - Cardiovascular Imaging     Hybrid Journal   (Followers: 9, SJR: 3.625, CiteScore: 3)
European Heart J. - Cardiovascular Pharmacotherapy     Full-text available via subscription   (Followers: 2)
European Heart J. - Quality of Care and Clinical Outcomes     Hybrid Journal  
European Heart J. : Case Reports     Open Access  
European Heart J. Supplements     Hybrid Journal   (Followers: 8, SJR: 0.223, CiteScore: 0)
European J. of Cardio-Thoracic Surgery     Hybrid Journal   (Followers: 9, SJR: 1.681, CiteScore: 2)
European J. of Intl. Law     Hybrid Journal   (Followers: 195, SJR: 0.694, CiteScore: 1)
European J. of Orthodontics     Hybrid Journal   (Followers: 4, SJR: 1.279, CiteScore: 2)
European J. of Public Health     Hybrid Journal   (Followers: 20, SJR: 1.36, CiteScore: 2)
European Review of Agricultural Economics     Hybrid Journal   (Followers: 10, SJR: 1.172, CiteScore: 2)
European Review of Economic History     Hybrid Journal   (Followers: 30, SJR: 0.702, CiteScore: 1)
European Sociological Review     Hybrid Journal   (Followers: 42, SJR: 2.728, CiteScore: 3)
Evolution, Medicine, and Public Health     Open Access   (Followers: 12)
Family Practice     Hybrid Journal   (Followers: 16, SJR: 1.018, CiteScore: 2)
Fems Microbiology Ecology     Hybrid Journal   (Followers: 15, SJR: 1.492, CiteScore: 4)
Fems Microbiology Letters     Hybrid Journal   (Followers: 28, SJR: 0.79, CiteScore: 2)
Fems Microbiology Reviews     Hybrid Journal   (Followers: 32, SJR: 7.063, CiteScore: 13)
Fems Yeast Research     Hybrid Journal   (Followers: 13, SJR: 1.308, CiteScore: 3)
Food Quality and Safety     Open Access   (Followers: 1)
Foreign Policy Analysis     Hybrid Journal   (Followers: 25, SJR: 1.425, CiteScore: 1)
Forest Science     Hybrid Journal   (Followers: 7, SJR: 0.89, CiteScore: 2)
Forestry: An Intl. J. of Forest Research     Hybrid Journal   (Followers: 16, SJR: 1.133, CiteScore: 3)
Forum for Modern Language Studies     Hybrid Journal   (Followers: 6, SJR: 0.104, CiteScore: 0)
French History     Hybrid Journal   (Followers: 33, SJR: 0.118, CiteScore: 0)
French Studies     Hybrid Journal   (Followers: 21, SJR: 0.148, CiteScore: 0)
French Studies Bulletin     Hybrid Journal   (Followers: 10, SJR: 0.152, CiteScore: 0)
Gastroenterology Report     Open Access   (Followers: 2)
Genome Biology and Evolution     Open Access   (Followers: 14, SJR: 2.578, CiteScore: 4)
Geophysical J. Intl.     Hybrid Journal   (Followers: 36, SJR: 1.506, CiteScore: 3)
German History     Hybrid Journal   (Followers: 23, SJR: 0.161, CiteScore: 0)
GigaScience     Open Access   (Followers: 5, SJR: 5.022, CiteScore: 7)
Global Summitry     Hybrid Journal   (Followers: 1)
Glycobiology     Hybrid Journal   (Followers: 13, SJR: 1.493, CiteScore: 3)
Health and Social Work     Hybrid Journal   (Followers: 57, SJR: 0.388, CiteScore: 1)
Health Education Research     Hybrid Journal   (Followers: 16, SJR: 0.854, CiteScore: 2)
Health Policy and Planning     Hybrid Journal   (Followers: 24, SJR: 1.512, CiteScore: 2)
Health Promotion Intl.     Hybrid Journal   (Followers: 22, SJR: 0.812, CiteScore: 2)
History Workshop J.     Hybrid Journal   (Followers: 31, SJR: 1.278, CiteScore: 1)
Holocaust and Genocide Studies     Hybrid Journal   (Followers: 28, SJR: 0.105, CiteScore: 0)
Human Communication Research     Hybrid Journal   (Followers: 15, SJR: 2.146, CiteScore: 3)
Human Molecular Genetics     Hybrid Journal   (Followers: 9, SJR: 3.555, CiteScore: 5)
Human Reproduction     Hybrid Journal   (Followers: 72, SJR: 2.643, CiteScore: 5)
Human Reproduction Open     Open Access   (Followers: 1)
Human Reproduction Update     Hybrid Journal   (Followers: 20, SJR: 5.317, CiteScore: 10)
Human Rights Law Review     Hybrid Journal   (Followers: 62, SJR: 0.756, CiteScore: 1)
ICES J. of Marine Science: J. du Conseil     Hybrid Journal   (Followers: 56, SJR: 1.591, CiteScore: 3)
ICSID Review : Foreign Investment Law J.     Hybrid Journal   (Followers: 10)
ILAR J.     Hybrid Journal   (Followers: 2, SJR: 1.732, CiteScore: 4)
IMA J. of Applied Mathematics     Hybrid Journal   (SJR: 0.679, CiteScore: 1)
IMA J. of Management Mathematics     Hybrid Journal   (SJR: 0.538, CiteScore: 1)
IMA J. of Mathematical Control and Information     Hybrid Journal   (Followers: 2, SJR: 0.496, CiteScore: 1)
IMA J. of Numerical Analysis - advance access     Hybrid Journal   (SJR: 1.987, CiteScore: 2)
Industrial and Corporate Change     Hybrid Journal   (Followers: 10, SJR: 1.792, CiteScore: 2)
Industrial Law J.     Hybrid Journal   (Followers: 39, SJR: 0.249, CiteScore: 1)
Inflammatory Bowel Diseases     Hybrid Journal   (Followers: 48, SJR: 2.511, CiteScore: 4)
Information and Inference     Free  
Integrative and Comparative Biology     Hybrid Journal   (Followers: 8, SJR: 1.319, CiteScore: 2)
Interacting with Computers     Hybrid Journal   (Followers: 11, SJR: 0.292, CiteScore: 1)
Interactive CardioVascular and Thoracic Surgery     Hybrid Journal   (Followers: 7, SJR: 0.762, CiteScore: 1)
Intl. Affairs     Hybrid Journal   (Followers: 65, SJR: 1.505, CiteScore: 3)
Intl. Data Privacy Law     Hybrid Journal   (Followers: 25)
Intl. Health     Hybrid Journal   (Followers: 6, SJR: 0.851, CiteScore: 2)
Intl. Immunology     Hybrid Journal   (Followers: 3, SJR: 2.167, CiteScore: 4)
Intl. J. for Quality in Health Care     Hybrid Journal   (Followers: 36, SJR: 1.348, CiteScore: 2)
Intl. J. of Constitutional Law     Hybrid Journal   (Followers: 64, SJR: 0.601, CiteScore: 1)
Intl. J. of Epidemiology     Hybrid Journal   (Followers: 240, SJR: 3.969, CiteScore: 5)
Intl. J. of Law and Information Technology     Hybrid Journal   (Followers: 5, SJR: 0.202, CiteScore: 1)
Intl. J. of Law, Policy and the Family     Hybrid Journal   (Followers: 28, SJR: 0.223, CiteScore: 1)
Intl. J. of Lexicography     Hybrid Journal   (Followers: 10, SJR: 0.285, CiteScore: 1)
Intl. J. of Low-Carbon Technologies     Open Access   (Followers: 1, SJR: 0.403, CiteScore: 1)
Intl. J. of Neuropsychopharmacology     Open Access   (Followers: 3, SJR: 1.808, CiteScore: 4)
Intl. J. of Public Opinion Research     Hybrid Journal   (Followers: 11, SJR: 1.545, CiteScore: 1)
Intl. J. of Refugee Law     Hybrid Journal   (Followers: 38, SJR: 0.389, CiteScore: 1)
Intl. J. of Transitional Justice     Hybrid Journal   (Followers: 11, SJR: 0.724, CiteScore: 2)
Intl. Mathematics Research Notices     Hybrid Journal   (Followers: 1, SJR: 2.168, CiteScore: 1)
Intl. Political Sociology     Hybrid Journal   (Followers: 40, SJR: 1.465, CiteScore: 3)
Intl. Relations of the Asia-Pacific     Hybrid Journal   (Followers: 23, SJR: 0.401, CiteScore: 1)
Intl. Studies Perspectives     Hybrid Journal   (Followers: 9, SJR: 0.983, CiteScore: 1)
Intl. Studies Quarterly     Hybrid Journal   (Followers: 48, SJR: 2.581, CiteScore: 2)
Intl. Studies Review     Hybrid Journal   (Followers: 25, SJR: 1.201, CiteScore: 1)
ISLE: Interdisciplinary Studies in Literature and Environment     Hybrid Journal   (Followers: 2, SJR: 0.15, CiteScore: 0)
ITNOW     Hybrid Journal   (Followers: 1, SJR: 0.103, CiteScore: 0)
J. of African Economies     Hybrid Journal   (Followers: 16, SJR: 0.533, CiteScore: 1)
J. of American History     Hybrid Journal   (Followers: 46, SJR: 0.297, CiteScore: 1)
J. of Analytical Toxicology     Hybrid Journal   (Followers: 14, SJR: 1.065, CiteScore: 2)
J. of Antimicrobial Chemotherapy     Hybrid Journal   (Followers: 15, SJR: 2.419, CiteScore: 4)
J. of Antitrust Enforcement     Hybrid Journal   (Followers: 1)
J. of Applied Poultry Research     Hybrid Journal   (Followers: 5, SJR: 0.585, CiteScore: 1)
J. of Biochemistry     Hybrid Journal   (Followers: 40, SJR: 1.226, CiteScore: 2)
J. of Burn Care & Research     Hybrid Journal   (Followers: 10, SJR: 0.768, CiteScore: 2)
J. of Chromatographic Science     Hybrid Journal   (Followers: 18, SJR: 0.36, CiteScore: 1)
J. of Church and State     Hybrid Journal   (Followers: 12, SJR: 0.139, CiteScore: 0)
J. of Communication     Hybrid Journal   (Followers: 55, SJR: 4.411, CiteScore: 5)
J. of Competition Law and Economics     Hybrid Journal   (Followers: 37, SJR: 0.33, CiteScore: 0)
J. of Complex Networks     Hybrid Journal   (Followers: 2, SJR: 1.05, CiteScore: 4)
J. of Computer-Mediated Communication     Open Access   (Followers: 29, SJR: 2.961, CiteScore: 6)
J. of Conflict and Security Law     Hybrid Journal   (Followers: 13, SJR: 0.402, CiteScore: 0)
J. of Consumer Research     Full-text available via subscription   (Followers: 47, SJR: 5.856, CiteScore: 5)

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Journal Cover
Biostatistics
Journal Prestige (SJR): 1.553
Citation Impact (citeScore): 2
Number of Followers: 17  
 
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1465-4644 - ISSN (Online) 1468-4357
Published by Oxford University Press Homepage  [397 journals]
  • Monte Carlo local likelihood approximation
    • Authors: Jeon M; Kaufman C, Rabe-Hesketh S.
      Pages: 164 - 179
      Abstract: SummaryWe propose the Monte Carlo local likelihood (MCLL) method for approximating maximum likelihood estimation (MLE). MCLL initially treats model parameters as random variables, sampling them from the posterior distribution as in a Bayesian model. The likelihood function is then approximated up to a constant by fitting a density to the posterior samples and dividing the approximate posterior density by the prior. In the MCLL algorithm, the posterior density is estimated using local likelihood density estimation, in which the log-density is locally approximated by a polynomial function. We also develop a new method that allows users to efficiently compute standard errors and the Bayes factor. Two empirical and three simulation studies are provided to demonstrate the performance of the MCLL method.
      PubDate: Thu, 04 Jan 2018 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx070
      Issue No: Vol. 20, No. 1 (2018)
       
  • Biostatistics Reviewer List 2018
    • Pages: 180 - 181
      Abstract: Albers, David
      PubDate: Mon, 17 Dec 2018 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxy077
      Issue No: Vol. 20, No. 1 (2018)
       
  • Using ecological propensity score to adjust for missing confounders in
           small area studies
    • Authors: Wang Y; Pirani M, Hansell A, et al.
      Pages: 1 - 16
      Abstract: SummarySmall area ecological studies are commonly used in epidemiology to assess the impact of area level risk factors on health outcomes when data are only available in an aggregated form. However, the resulting estimates are often biased due to unmeasured confounders, which typically are not available from the standard administrative registries used for these studies. Extra information on confounders can be provided through external data sets such as surveys or cohorts, where the data are available at the individual level rather than at the area level; however, such data typically lack the geographical coverage of administrative registries. We develop a framework of analysis which combines ecological and individual level data from different sources to provide an adjusted estimate of area level risk factors which is less biased. Our method (i) summarizes all available individual level confounders into an area level scalar variable, which we call ecological propensity score (EPS), (ii) implements a hierarchical structured approach to impute the values of EPS whenever they are missing, and (iii) includes the estimated and imputed EPS into the ecological regression linking the risk factors to the health outcome. Through a simulation study, we show that integrating individual level data into small area analyses via EPS is a promising method to reduce the bias intrinsic in ecological studies due to unmeasured confounders; we also apply the method to a real case study to evaluate the effect of air pollution on coronary heart disease hospital admissions in Greater London.
      PubDate: Thu, 09 Nov 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx058
      Issue No: Vol. 20, No. 1 (2017)
       
  • Dose-finding designs for cumulative toxicities using multiple constraints
    • Authors: Lee S; Ursino M, Cheung Y, et al.
      Pages: 17 - 29
      Abstract: This article addresses the concern regarding late-onset dose-limiting toxicities (DLT), moderate toxicities below the threshold of a DLT and cumulative toxicities that may lead to a DLT, which are mostly disregarded or handled in an ad hoc manner when determining the maximum tolerated dose (MTD) in dose-finding cancer clinical trials. An extension of the Time-to-Event Continual Reassessment Method (TITE-CRM) which allows for the specification of toxicity constraints on both DLT and moderate toxicities, and can account for partial information is proposed. The method is illustrated in the context of an Erlotinib dose-finding trial with low DLT rates, but a significant number of moderate toxicities leading to treatment discontinuation in later cycles. Based on simulations, our method performs well at selecting the dose level that satisfies both the DLT and moderate-toxicity constraints. Moreover, it has similar probability of correct selection compared to the TITE-CRM when the true MTD based on DLT only and the true MTD based on grade 2 or higher toxicities alone coincide, but reduces the probability of recommending a dose above the MTD.
      PubDate: Mon, 13 Nov 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx059
      Issue No: Vol. 20, No. 1 (2017)
       
  • Estimating autoantibody signatures to detect autoimmune disease patient
           subsets
    • Authors: Wu Z; Casciola-Rosen L, Shah A, et al.
      Pages: 30 - 47
      Abstract: Autoimmune diseases are characterized by highly specific immune responses against molecules in self-tissues. Different autoimmune diseases are characterized by distinct immune responses, making autoantibodies useful for diagnosis and prediction. In many diseases, the targets of autoantibodies are incompletely defined. Although the technologies for autoantibody discovery have advanced dramatically over the past decade, each of these techniques generates hundreds of possibilities, which are onerous and expensive to validate. We set out to establish a method to greatly simplify autoantibody discovery, using a pre-filtering step to define subgroups with similar specificities based on migration of radiolabeled, immunoprecipitated proteins on sodium dodecyl sulfate (SDS) gels and autoradiography [Gel Electrophoresis and band detection on Autoradiograms (GEA)]. Human recognition of patterns is not optimal when the patterns are complex or scattered across many samples. Multiple sources of errors—including irrelevant intensity differences and warping of gels—have challenged automation of pattern discovery from autoradiograms.In this article, we address these limitations using a Bayesian hierarchical model with shrinkage priors for pattern alignment and spatial dewarping. The Bayesian model combines information from multiple gel sets and corrects spatial warping for coherent estimation of autoantibody signatures defined by presence or absence of a grid of landmark proteins. We show the pre-processing creates more clearly separated clusters and improves the accuracy of autoantibody subset detection via hierarchical clustering. Finally, we demonstrate the utility of the proposed methods with GEA data from scleroderma patients.
      PubDate: Mon, 13 Nov 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx061
      Issue No: Vol. 20, No. 1 (2017)
       
  • Z-scores-based methods and their application to biological monitoring: an
           example in professional soccer players
    • Authors: Saulière G; Dedecker J, Marquet L, et al.
      Pages: 48 - 64
      Abstract: SummaryThe clinical and biological follow-up of individuals, such as the biological passport for athletes, is typically based on the individual and longitudinal monitoring of hematological or urine markers. These follow-ups aim to identify abnormal behavior by comparing the individual’s biological samples to an established baseline. These comparisons may be done via different ways, but each of them requires an appropriate extra population to compute the significance levels, which is a non-trivial issue. Moreover, it is not necessarily relevant to compare the measures of a biomarker of a professional athlete to that of a reference population (even restricted to other athletes), and a reasonable alternative is to detect the abnormal values by considering only the other measurements of the same athlete. Here we propose a simple adaptive statistic based on maxima of Z-scores that does not rely on the use of an extra population. We show that, in the Gaussian framework, it is a practical and relevant method for detecting abnormal values in a series of observations from the same individual. The distribution of this statistic does not depend on the individual parameters under the null hypothesis, and its quantiles can be computed using Monte Carlo simulations. The proposed method is tested on the 3-year follow-up of ferritin, serum iron, erythrocytes, hemoglobin, and hematocrit markers in 2577 elite male soccer players. For instance, if we consider the abnormal values for the hematocrit at a 5% level, we found that 5.57% of the selected cohort had at least one abnormal value (which is not significantly different from the expected false-discovery rate). The approach is a starting point for more elaborate models that would produce a refined individual baseline. The method can be extended to the Gaussian linear model, in order to include additional variables such as the age or exposure to altitude. The method could also be applied to other domains, such as the clinical patient follow-up in monitoring abnormal values of biological markers.
      PubDate: Wed, 15 Nov 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx044
      Issue No: Vol. 20, No. 1 (2017)
       
  • Instrumental variables estimation under a structural Cox model
    • Authors: Martinussen T; Nørbo Sørensen D, Vansteelandt S.
      Pages: 65 - 79
      Abstract: SummaryInstrumental variable (IV) analysis is an increasingly popular tool for inferring the effect of an exposure on an outcome, as witnessed by the growing number of IV applications in epidemiology, for instance. The majority of IV analyses of time-to-event endpoints are, however, dominated by heuristic approaches. More rigorous proposals have either sidestepped the Cox model, or considered it within a restrictive context with dichotomous exposure and instrument, amongst other limitations. The aim of this article is to reconsider IV estimation under a structural Cox model, allowing for arbitrary exposure and instruments. We propose a novel class of estimators and derive their asymptotic properties. The methodology is illustrated using two real data applications, and using simulated data.
      PubDate: Mon, 20 Nov 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx057
      Issue No: Vol. 20, No. 1 (2017)
       
  • Adjusting for bias introduced by instrumental variable estimation in the
           Cox proportional hazards model
    • Authors: Martínez-Camblor P; Mackenzie T, Staiger D, et al.
      Pages: 80 - 96
      Abstract: SummaryInstrumental variable (IV) methods are widely used for estimating average treatment effects in the presence of unmeasured confounders. However, the capability of existing IV procedures, and most notably the two-stage residual inclusion (2SRI) algorithm recommended for use in non-linear contexts, to account for unmeasured confounders in the Cox proportional hazard model is unclear. We show that instrumenting an endogenous treatment induces an unmeasured covariate, referred to as an individual frailty in survival analysis parlance, which if not accounted for leads to bias. We propose a new procedure that augments 2SRI with an individual frailty and prove that it is consistent under certain conditions. The finite sample-size behavior is studied across a broad set of conditions via Monte Carlo simulations. Finally, the proposed methodology is used to estimate the average effect of carotid endarterectomy versus carotid stenting on the mortality of patients suffering from carotid artery disease. Results suggest that the 2SRI-frailty estimator generally reduces the bias of both point and interval estimators compared to traditional 2SRI.
      PubDate: Sat, 16 Dec 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx062
      Issue No: Vol. 20, No. 1 (2017)
       
  • Fixed choice design and augmented fixed choice design for network data
           with missing observations
    • Authors: Ott M; Harrison M, Gile K, et al.
      Pages: 97 - 110
      Abstract: SummaryThe statistical analysis of social networks is increasingly used to understand social processes and patterns. The association between social relationships and individual behaviors is of particular interest to sociologists, psychologists, and public health researchers. Several recent network studies make use of the fixed choice design (FCD), which induces missing edges in the network data. Because of the complex dependence structure inherent in networks, missing data can pose very difficult problems for valid statistical inference. In this article, we introduce novel methods for accounting for the FCD censoring and introduce a new survey design, which we call the augmented fixed choice design (AFCD). The AFCD adds considerable information to analyses without unduly burdening the survey respondent, resulting in improvements over the FCD, and other existing estimators. We demonstrate this new method through simulation studies and an analysis of alcohol use in a network of undergraduate students living in a residence hall.
      PubDate: Sat, 16 Dec 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx066
      Issue No: Vol. 20, No. 1 (2017)
       
  • Multivariate generalized linear model for genetic pleiotropy
    • Authors: Schaid D; Tong X, Batzler A, et al.
      Pages: 111 - 128
      Abstract: SummaryWhen a single gene influences more than one trait, known as pleiotropy, it is important to detect pleiotropy to improve the biological understanding of a gene. This can lead to improved screening, diagnosis, and treatment of diseases. Yet, most current multivariate methods to evaluate pleiotropy test the null hypothesis that none of the traits are associated with a variant; departures from the null could be driven by just one associated trait. A formal test of pleiotropy should assume a null hypothesis that one or fewer traits are associated with a genetic variant. We recently developed statistical methods to analyze pleiotropy for quantitative traits having a multivariate normal distribution. We now extend this approach to traits that can be modeled by generalized linear models, such as analysis of binary, ordinal, or quantitative traits, or a mixture of these types of traits. Based on methods from estimating equations, we developed a new test for pleiotropy. We then extended the testing framework to a sequential approach to test the null hypothesis that $k+1$ traits are associated, given that the null of $k$ associated traits was rejected. This provides a testing framework to determine the number of traits associated with a genetic variant, as well as which traits, while accounting for correlations among the traits. By simulations, we illustrate the Type-I error rate and power of our new methods, describe how they are influenced by sample size, the number of traits, and the trait correlations, and apply the new methods to a genome-wide association study of multivariate traits measuring symptoms of major depression. Our new approach provides a quantitative assessment of pleiotropy, enhancing current analytic practice.
      PubDate: Sat, 16 Dec 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx067
      Issue No: Vol. 20, No. 1 (2017)
       
  • Time-varying proportional odds model for mega-analysis of clustered event
           times
    • Authors: Garcia T; Marder K, Wang Y.
      Pages: 129 - 146
      Abstract: SummaryMega-analysis, or the meta-analysis of individual data, enables pooling and comparing multiple studies to enhance estimation and power. A challenge in mega-analysis is estimating the distribution for clustered, potentially censored event times where the dependency structure can introduce bias if ignored. We propose a new proportional odds model with unknown, time-varying coefficients, and random effects. The model directly captures event dependencies, handles censoring using pseudo-values, and permits a simple estimation by transforming the model into an easily estimable additive logistic mixed effect model. Our method consistently estimates the distribution for clustered event times even under covariate-dependent censoring. Applied to three observational studies of Huntington’s disease, our method provides, for the first time in the literature, evidence of similar conclusions about motor and cognitive impairments in all studies despite different recruitment criteria.
      PubDate: Fri, 22 Dec 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx065
      Issue No: Vol. 20, No. 1 (2017)
       
  • It’s all about balance: propensity score matching in the context of
           complex survey data
    • Authors: Lenis D; Nguyen T, Dong N, et al.
      Pages: 147 - 163
      Abstract: SummaryMany research studies aim to draw causal inferences using data from large, nationally representative survey samples, and many of these studies use propensity score matching to make those causal inferences as rigorous as possible given the non-experimental nature of the data. However, very few applied studies are careful about incorporating the survey design with the propensity score analysis, which may mean that the results do not generate population inferences. This may be because few methodological studies examine how to best combine these methods. Furthermore, even fewer of them investigate different non-response mechanisms. This study examines methods for handling survey weights in propensity score matching analyses of survey data under different non-response mechanisms. Our main conclusions are: (i) whether the survey weights are incorporated in the estimation of the propensity score does not impact estimation of the population treatment effect, as long as good population treated-comparison balance is achieved on confounders, (ii) survey weights must be used in the outcome analysis, and (iii) the transferring of survey weights (i.e., assigning the weights of the treated units to the comparison units matched to them) can be beneficial under certain non-response mechanisms.
      PubDate: Wed, 27 Dec 2017 00:00:00 GMT
      DOI: 10.1093/biostatistics/kxx063
      Issue No: Vol. 20, No. 1 (2017)
       
 
 
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