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  • Search: isPartOf:"The International Journal of Biostatistics"
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EM algorithm 1 Genetics 1 HIV-1 1 Longitudinal Data Analysis and Time Series 1 haplotype block 1 linkage disequilibrium 1 quantitative trait loci 1 single nucleotide polymorphism 1
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Undetermined 266
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Article 266
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Undetermined 266
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van der Laan Mark J. 43 Moodie Erica E. M. 8 Susan, Gruber 7 C, Austin Peter 4 J, Carroll Raymond 4 L, Petersen Maya 4 Paul, Gustafson 4 Platt Robert W. 4 Torsten, Hothorn 4 Yangxin, Huang 4 A, Stephens David 3 Allan, Donner 3 B, Rubin Daniel 3 J, VanderWeele Tyler 3 Jianguo, Sun 3 Kaufman Jay S. 3 Liang, Li 3 Mario, Hasler 3 Robins James M. 3 Sherri, Rose 3 Victor, De Gruttola 3 W, Platt Robert 3 Yasutaka, Chiba 3 A, Hothorn Ludwig 2 Andrea, Rotnitzky 2 Antoine, Chambaz 2 Arvid, Sjolander 2 Ashkan, Ertefaie 2 B, Salter Amy 2 Chunning, Yan 2 Cécile, Proust-Lima 2 D, McNicholas Paul 2 Daniel, Commenges 2 Daniel, Rubin 2 Delaney Joseph A.C. 2 Donna, Spiegelman 2 Dylan, Small 2 Eric, Tchetgen Tchetgen 2 F, Desmond Anthony 2 Foulkes Andrea S. 2
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The International Journal of Biostatistics 266
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RePEc 266
Showing 41 - 50 of 266
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Sensitivity Analysis for Causal Inference under Unmeasured Confounding and Measurement Error Problems
Iván, Díaz; van der Laan Mark J. - In: The International Journal of Biostatistics 9 (2013) 2, pp. 149-160
In this article, we present a sensitivity analysis for drawing inferences about parameters that are not estimable from observed data without additional assumptions. We present the methodology using two different examples: a causal parameter that is not identifiable due to violations of the...
Persistent link: https://www.econbiz.de/10011019038
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Assessing Agreement of Repeated Binary Measurements with an Application to the CDC’s Anthrax Vaccine Clinical Trial
Yi, Pan; Rose Charles E.; Michael, Haber; Yan, Ma; … - In: The International Journal of Biostatistics 9 (2013) 1, pp. 14-14
Cohen’s kappa coefficient, which was introduced in 1960, serves as the most widely employed coefficient to assess inter-observer agreement for categorical outcomes. However, the original kappa can only be applied to cross-sectional binary measurements and, therefore, cannot be applied in the...
Persistent link: https://www.econbiz.de/10010685935
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Latent Conditional Individual-Level Models for Infectious Disease Modeling
Deeth Lorna E.; Rob, Deardon - In: The International Journal of Biostatistics 9 (2013) 1, pp. 19-19
Individual-level models (ILMs) have previously been used to model the spatiotemporal spread of infectious diseases. These models can incorporate individual-level covariate information, to account for population heterogeneity. However, incomplete or unreliable data are a common problem in...
Persistent link: https://www.econbiz.de/10010685936
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Multiple Contrasts for Repeated Measures
Mario, Hasler - In: The International Journal of Biostatistics 9 (2013) 1, pp. 13-13
This article addresses the problem of multiple contrast tests for repeated measures. Three procedures are described and compared by simulations concerning the familywise error type I. The procedure based on sandwich estimators seems to be most robust, except for all-pair comparisons.
Persistent link: https://www.econbiz.de/10010685937
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A New Species Abundance Distribution Model Based on Model Combination
Abbas, Golestani; Robin, Gras - In: The International Journal of Biostatistics 9 (2013) 1, pp. 16-16
Species abundance distribution (SAD) is one of the important measures of biodiversity and one of the most significant concepts in ecology communities. Using this concept, the biologists can infer a lot of information from their collected data. In this article, we proposed a new method for...
Persistent link: https://www.econbiz.de/10010685938
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Efficient Analysis of Q-Level Nested Hierarchical General Linear Models Given Ignorable Missing Data
Yongyun, Shin; Raudenbush Stephen W. - In: The International Journal of Biostatistics 9 (2013) 1, pp. 25-25
This article extends single-level missing data methods to efficient estimation of a Q-level nested hierarchical general linear model given ignorable missing data with a general missing pattern at any of the Q levels. The key idea is to reexpress a desired hierarchical model as the joint...
Persistent link: https://www.econbiz.de/10010696588
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Detecting Differential Gene Expression in Subgroups of a Disease Population
Emerson Sarah C.; Emerson Scott S. - In: The International Journal of Biostatistics 9 (2013) 1, pp. 14-14
In many disease settings, it is likely that only a subset of the disease population will exhibit certain genetic or phenotypic differences from the healthy population. Therefore, when seeking to identify genes or other explanatory factors that might be related to the disease state, we might...
Persistent link: https://www.econbiz.de/10010696589
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Testing the assumptions for the analysis of survival data arising from a prevalent cohort study with follow-up
Vittorio, Addona; Juli, Atherton; Wolfson David B. - In: The International Journal of Biostatistics 8 (2012) 1, pp. 1-21
In a prevalent cohort study with follow-up subjects identified as prevalent cases are followed until failure (defined suitably) or censoring. When the dates of the initiating events of these prevalent cases are ascertainable, each observed datum point consists of a backward recurrence time and a...
Persistent link: https://www.econbiz.de/10011019033
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Estimation of the Mean Frequency Function for Recurrent Events when Ascertainment of Events Is Delayed
Charles, Casper T.; Cook Thomas D. - In: The International Journal of Biostatistics 8 (2012) 1, pp. 1-20
In many large clinical trials there are delays between the time at which events occur and the time at which they are reported. Estimators of the mean frequency function for recurrent events that are currently used are inconsistent in these circumstances. We propose two new estimators to be used...
Persistent link: https://www.econbiz.de/10009493048
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Bias Analysis to Guide New Data Collection
Lash Timothy L.; Ahern Thomas P. - In: The International Journal of Biostatistics 8 (2012) 2, pp. 1-23
Bias analysis serves multiple objectives in epidemiologic data analysis. The objectives most often emphasized are quantification of uncertainty due to systematic errors and reduction in overconfidence by specifying hypotheses that compete with the causal hypothesis. A third objective is the...
Persistent link: https://www.econbiz.de/10009415480
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