Japanese Journal of Biometrics
Online ISSN : 2185-6494
Print ISSN : 0918-4430
ISSN-L : 0918-4430
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Volume 31, Issue 1
Displaying 1-3 of 3 articles from this issue
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Original Article
  • Power Calculation for Likelihood Ratio Tests in the Nested Case-control Designs with a Randomly Sampled Control Per Case
    Shizue Izumi, Yoshinori Fujii
    2010 Volume 31 Issue 1 Pages 1-11
    Published: July 31, 2010
    Released on J-STAGE: December 14, 2010
    DOIhttps://doi.org/10.5691/jjb.31.1
    JOURNAL FREE ACCESS
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    This paper presents an asymptotic method of power calculations for likelihood ratio tests in the nested case-control designs with a randomly sampled control per case. It is an extension of the approach described in Self et al. (1992) for proportional hazards models. Our approach here focuses on a simple scenario with 1 : 1 case-control ratio, simple random sampling design, and two independent dichotomous covariates with no interaction effects. The approximation of the noncentrality of the noncentral chi-square distribution for the likelihood ratio statistic is provided. Simulation studies are conducted to examine the accuracy for several parameter values and data configurations. Overall the results suggest that estimates of power using our proposed method are consistent with those of actual power from Monte Carlo simulation. Therefore, the proposed approach can be practically useful in assessing the statistical power for the simple nested case-control design.
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Preliminary Report
  • Optimality of Gene Ranking Based on Univariate P-values for Detecting Differentially Expressed Genes
    Hisashi Noma, Shigeyuki Matsui
    2010 Volume 31 Issue 1 Pages 13-21
    Published: July 31, 2010
    Released on J-STAGE: December 14, 2010
    DOIhttps://doi.org/10.5691/jjb.31.13
    JOURNAL FREE ACCESS
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    Ranking significant genes based on the P-value in multiple testing is a simple and common practice in microarray data analysis, and its theoretical optimality is of particular interest. McLachlan et al. (Bioinformatics 2006; 22: 1608-1615) presented a method for calculating the local FDR under normal mixture models and provided a theoretical optimality of the local FDR as a ranking statistic. In this article, we show that the optimal gene ranking based on the local FDR calculated by the McLachlan et al.'s method perfectly accords with that based on P-value under certain conditions. We argue that these conditions are generally satisfied for significant genes with small P-values. We demonstrate it using several real examples.
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Review
  • Statistical Criteria for Surrogate Endpoint and Applications: A Review
    Shiro Tanaka, Koji Oba, Kenichi Yoshimura, Satoshi Teramukai
    2010 Volume 31 Issue 1 Pages 23-48
    Published: July 31, 2010
    Released on J-STAGE: December 14, 2010
    DOIhttps://doi.org/10.5691/jjb.31.23
    JOURNAL FREE ACCESS
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    Surrogate endpoints, which represent a compromise in the conflict between measurability and clinical relevance of endpoints, have considerable advantage in rapid drug approvals compared to true endpoints in confirmatory clinical trials dealing with life-threatening diseases, such as cancer or AIDS. However, past experiences have shown the risk of relying too heavily on surrogate endpoints. In this paper, we review statistical criteria for evaluating surrogate endpoints and the past examples properly evaluated the surrogacy, taking into consideration relevant clinical and statistical issues.
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