著者

柳川 堯

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.38, no.2, pp.153-161, 2018-03-01 (Released:2018-05-18)

参考文献数

5

---

Many clinical studies are conducted in Japan with sample sizes that are not deter-mined statistically. Application of Neyman-Pearson type statistical tests to data from such studies is not justifiable and should be stopped. Also 5% significance level that is commonly employed in a clinical study without taking into account disease, drug and other factors is not justifiable. Alternatively, the use of p-value is recommended in this paper as a measure of showing the magnitude of difference of two treatments; it is the role of principal investigator to summarize the study results by considering disease, drug and other factors, sample sizes and p-value.

著者

三中 信宏

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.38, no.2, pp.117-125, 2018-03-01 (Released:2018-05-18)

参考文献数

21

---

The recent controversy over the use and abuse of p-values in statistical data analysis sheds a light on the epistemological diversity of scientific researches and the nature of science. Since the nineteenth century theoretical statisticians including Karl Pearson, Ronald A. Fisher, Jerzy Neyman, and Egon S.Pearson constructed the mathematical basis of modern statistics, for example, experimental design, sampling distributions, or hypothesis testing, etc. However, statistical reasoning as empirical inference is not necessarily limited to the Neyman-Pearson’s decision-making paradigm. Any kind of non-deductive inference—for example, abduction—also uses statistics as an exploratory tool for relative ranking among alternative hypotheses and models. We must understand not only the proper use of statistical methods and procedures but also the nature of each science to which statistics is applied.

著者

篠崎 智大 横田 勲 大庭 幸治 上妻 佳代子 坂巻 顕太郎

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.41, no.1, pp.1-35, 2020 (Released:2020-12-04)

参考文献数

65

---

Prediction models are usually developed through model-construction and validation. Especially for binary or time-to-event outcomes, the risk prediction models should be evaluated through several aspects of the accuracy of prediction. With unified algebraic notation, we present such evaluation measures for model validation from five statistical viewpoints that are frequently reported in medical literature: 1) Brier score for prediction error; 2) sensitivity, specificity, and C-index for discrimination; 3) calibration-in-the-large, calibration slope, and Hosmer-Lemeshow statistic for calibration; 4) net reclassification and integrated discrimination improvement indexes for reclassification; and 5) net benefit for clinical usefulness. Graphical representation such as a receiver operating characteristic curve, a calibration plot, or a decision curve helps researchers interpret these evaluation measures. The interrelationship between them is discussed, and their definitions and estimators are extended to time-to-event data suffering from outcome-censoring. We illustrate their calculation through example datasets with the SAS codes provided in the web appendix.

著者

岩崎 学 吉田 清隆

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.26, no.2, pp.53-63, 2005-12-31 (Released:2011-09-30)

参考文献数

16

被引用文献数

5

---

For the occurrence of a rare event A such as a severe adverse drug reaction, there exists the “Rule of Three” to remind practitioners that “absence of evidence is not evidence of absence.” The Rule of Three actually says that even if the event A was not observed among n patients it would be quite possible to observe three events among other n patients. The present paper examines this useful rule in detail and also extends it to a testing problem for occurrence probability of A.First, the Rule of Three is extended to the case that the number of the event observed among the first n patients is more than zero. We give rules that when k (> 0) events were observed among n patients, nk events would be possibly observed among other n patients. Next, a testing procedure is introduced to examine whether the occurrence probabilities of A for two populations are the same under the condition that k events were observed among n patients for one population. It will be shown that the relevant probability distribution is a negative binomial, and then critical regions for small k's are given. For a possible application of the procedure, we mention the signal detection for spontaneous reporting system of adverse drug reaction.

著者

寒水 孝司 杉本 知之 濱崎 俊光

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.34, no.1, pp.35-52, 2013-08-31 (Released:2013-09-20)

参考文献数

61

被引用文献数

1

---

Clinical trials often employ two or more primary endpoints because a single endpoint may not provide a comprehensive picture of the intervention’s effects. In such clinical trials, a decision is generally made as to whether it is desirable to evaluate the joint effects on all endpoints (i.e., co.primary endpoints) or at least one of the endpoints. This decision defines the alternative hypothesis to be tested and provides a framework for approaching trial design. In this article, we discuss recent statistical issues in clinical trials with multiple primary endpoints. Especially, we introduce the methods for power and sample size determinations in clinical trials with co-primary endpoints, considering the correlations among the endpoints into the calculations. We also discuss the methods to alleviate conservativeness of testing co-primary endpoints.

著者

手良向 聡

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.41, no.1, pp.37-54, 2020 (Released:2020-12-04)

参考文献数

43

被引用文献数

1 1

---

Fisher’s randomization rule has been widely viewed as a revolutionary invention in experimental design. The three rationales of randomization in clinical trials are (i) randomization ensures that known and unknown confounders are asymptotically controlled, (ii) the use of randomization itself provides the basis of statistical inference, supposing patients in a clinical trial are a non-random sample of a population, and (iii) the act of randomization mitigates selection bias by providing unpredictability in treatment allocation. Randomized controlled trials have been the gold standard for more than five decades, while such trials may be costly, inconvenient and ethically challenging. Some Fisherian statisticians have emphasized the importance of design-based inference based on randomization test, however some statisticians does not agree with them. From the Bayesian point of view, the randomization sequence is ancillary for a parameter of interest, and randomization itself is not absolutely essential although it may sometimes be helpful. In this review, I provide an overview of the rationales of randomization and the related topics, and discuss the significance and limitations of randomization in clinical trials.

著者

田中 司朗

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.40, no.1, pp.35-62, 2019-08-01 (Released:2019-09-18)

参考文献数

37

被引用文献数

1

---

A central problem in medical research is how to make inferences about the causal effects of treatments or exposures. In this article, we review fundamental concepts for making such inferences in randomized clinical trials or observational studies. The statistical framework consists of potential outcomes, an assignment mechanism, and probability distributions. Randomization-based and model-based methods of statistical inference are illustrated with a series of extracorporeal membrane oxygenation (ECMO) clinical trials, which are thought-provoking in that each trial used different assignment mechanisms.

著者

矢田 真城 魚住 龍史 田栗 正隆

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.40, no.2, pp.81-116, 2020-06-01 (Released:2020-07-21)

参考文献数

63

---

When a causal effect between treatment and outcome variables is observed, effects on the outcome are of interest to investigate the mechanisms among the outcome and treatment. Indirect effect is defined as the causal effect of the treatment on the outcome via the mediator. Direct effect is defined as the causal effect of the treatment on the outcome that is not through the mediator. In this paper, we discuss the estimation of direct and indirect effects based on the framework of potential response models focusing on the 4-way decomposition. Direct and indirect effect estimations are illustrated with two examples where the outcome, mediator, covariate variables are continuous and categorical data. Moreover, we discuss the estimation of clausal effects and the effect decomposition in the settings that include confounder of mediator and outcome affected by treatment, multiple mediators, or time-varying treatment in the presence of time-dependent confounder.

著者

松山 裕

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.25, no.2, pp.89-116, 2004-12-31 (Released:2012-02-08)

参考文献数

55

被引用文献数

2 1

---

Missing data is a prevalent complication in the analysis of data from longitudinal studies, and remains an active area of research for biostatisticians and other quantitative methodologists. This paper reviews several statistical methods that are used to address outcome-related drop-out. We begin with a review of important concepts such as missing data patterns, missing data mechanisms, ignorability and likelihood-based inference, which were originally proposed by Rubin (1976, Biometrika 63, 581-592). Secondly, we review the simple analysis methods for handling drop-outs such as a complete-case analysis, an available data analysis and a last observation carried forward analysis, and their limitations are given. Thirdly, we review the more sophisticated approaches for handling drop-outs, which take account of the missing data mechanisms in the analysis. Inverse probability weighted methods and multiple imputation methods, which represent two distinct paradigms for handling missing data, are reviewed. The analysis methods for non-ignorable drop-outs are also reviewed. Three approaches, selection models, pattern mixture models and latent variable models are presented. We illustrate the analysis techniques using the longitudinal clinical trial of contracepting women reported by Machine et al (1988, Contraception 38, 165-179). We briefly review the analysis methods in the presence of missing covariates. Finally, we give some notice in the analysis of missing data.

著者

坂巻 顕太郎 兼清 道雄 大和田 章一 松浦 健太郎 柿爪 智行 高橋 文博 高沢 翔 萩原 駿祐 森田 智視

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.41, no.1, pp.55-91, 2020 (Released:2020-12-04)

参考文献数

44

---

It is common to use hypothesis testing to decide whether an investigational drug is ineffective and to determine sample size. However, it may not be good practice that only hypothesis testing is used for sample size determination, go/no-go decision making, and drug development decisions, especially in exploratory clinical trials. That is because important factors for decision making, such as treatment effects, drug development costs, and gains after launch, are not considered in hypothesis testing. The Bayesian decision theory is one of the approaches to consider such factors for decision making. The utility, which is defined by using important information such as cost, benefit, and disease severity, is used for decision making in the decision theory. In consideration of uncertainties of data and parameters, the expected value of the utility is used for decision making in the Bayesian decision theory. In this article, we explain basic concepts of the Bayesian decision theory, backward induction for calculation of expected value of utility in sequential decision-making, and introduce some approaches using the Bayesian decision theory in clinical trials. We summarize actions, utilities and sample size determination for applications of Bayesian decision theory in future clinical trials.

著者

佐藤 俊哉

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.38, no.2, pp.109-115, 2018-03-01 (Released:2018-05-18)

参考文献数

21

被引用文献数

1

---

On March 7th, 2016, the American Statistical Association released its “ASA Statement on Statistical Significance and P-values,” which provided 6 principles to improve the conduct or interpretation of quantitative research. Misunderstanding and misuse of statistical tests and P-values were discussed many times in the epidemiologic field. In this paper, I gave a summary of the ASA statement and its translation process into Japanese. Then, I discussed how to avoid misunderstanding or misuse of statistical tests or P-values in epidemiologic observational studies.

著者

浜田 知久馬 中西 豊支 松岡 伸篤

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.27, no.2, pp.139-157, 2006-12-01 (Released:2011-09-25)

参考文献数

50

被引用文献数

4 3

---

Meta-analysis is defined to be ‘the statistical analysis of a large collection of analysis results from individual studies for the purpose of integrating the findings'. Since the 1980s there has been an upsurge in the application of meta-analysis to medical research. The rapid increase in the number of meta-analysis being conducted during the last decade is mainly due to a greater emphasis on evidence based medicine and the need for reliable summaries of the vast and expanding volume of clinical studies. Over the same period there have been great developments and refinements of the associated methodology of meta-analysis. When judging the reliability of the results of a meta-analysis, attention should be focused on ‘publication bias’. Publication bias is the term for what occurs whenever the research that appears in the published literature is systematically unrepresentative of the population of completed studies. This bias can provide a flaw of the result of meta-analysis. In this article, the causes and origins of publication bias are reviewed, and then the history and some findings of publication bias in medical research are presented. Several statistical methods that have been developed to detect, quantify and assess the impact of publication bias in meta-analysis are demonstrated.

著者

黒木 学 小林 史明

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.32, no.2, pp.119-144, 2012-03-31 (Released:2012-06-08)

参考文献数

89

被引用文献数

2

---

This paper reviews basic ideas of Structural Causal Models (SCMs) proposed by Judea Pearl (1995, 2009a). SCMs are nonparametric structual equation models which express cause-effect relationship between variables, and justify matematical principles of both the potential outcome approach and the graphical model approach for statistical causal inference. In this paper, considering the difference/connection between SCMs and Rubin's Causal Models (RCMs) (Rubin, 1974, 1978, 2006), we state that (1) the expressive power of the potential outcome approach is higher than that of the graphical model approach, but (2) the graphical model approach. From these consderations, we conclude that we should discuss statistical causal inference based on both approaches.

著者

武田 健太朗 大庭 真梨 柿爪 智行 坂巻 顕太郎 田栗 正隆 森田 智視

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.36, no.1, pp.25-50, 2015-07-20 (Released:2015-09-08)

参考文献数

47

被引用文献数

6 6

---

It is expected to develop new drug more efficiently by incorporating historical data into the current study data. Borrowing historical data which is sufficiently similar to the current data allows increasing power and improving the accuracy of the estimated treatment effect. On the other hand, if the historical data is not similar to the current data, there is a potential for bias and inflated type I error rate. Power prior and hierarchical model are widely known as the Bayesian approaches with borrowing strength from historical information. They have the advantage of deciding the amount of historical information continuously depending on the similarity between historical data and current data. Our goal is to introduce power prior and hierarchical model while showing some examples, and provide a review of points to keep in mind when these approaches are used in the clinical trials.

著者

谷岡 健資 上阪 彩香 山下 陽司 大森 崇 寒水 孝司

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.35, no.2, pp.95-105, 2015-01-31 (Released:2015-03-23)

参考文献数

13

被引用文献数

1 1

---

Few studies have investigated the content of introductory statistics classes for medical school students in Japan. Yet, to assure the quality of university statistics courses and develop a standard curriculum for them, it is necessary to assess the current condition of statistics education.Therefore, we collected data on the type of course (i.e., course title and targeted year for the students), field of specialty of the lecturer, course contents, and which textbooks were pre-specified for the lecture by analyzing the syllabi of statistics courses published on university websites. Next, the result of the survey is summarized. Of the 80 universities surveyed, 45 universities provided the online sylabi for the introductory statistics course. We identified 26 different course titles for statistics classes. Thirty courses (73.3%) were intended for first-year students. Eightteen courses (54.5%) provided two credits. The most common field of specialty for statistics lecturers was mathematics (43.2%). Further, we found that the course contents included various subjects related to mathematics. A total of 35 textbooks were specified. Finally, the conclusion is that mathematical concepts seem to be taught more often than statistical practice in introductory statistics classes. Further, there were large variations in each item of analysis except the target year.

著者

佐藤 俊哉 松山 裕

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.32, no.Special_Issue, pp.S35-S49, 2011-05-31 (Released:2011-09-05)

参考文献数

11

被引用文献数

4 2

著者

久保田 康裕 楠本 聞太郎 塩野 貴之 五十里 翔吾 深谷 肇一 高科 直 吉川 友也 重藤 優太郎 新保 仁 竹内 彰一 三枝 祐輔 小森 理

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.43, no.2, pp.145-188, 2023 (Released:2023-06-28)

参考文献数

110

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Biodiversity big data plays an essential role in better understanding of biodiversity pattern in space and time and its underpinning macroecological mechanisms. Biodiversity as a concept is inductively quantified by the measurable multivariate data relative to taxonomic, functional and phylogenetic/genetic aspects. Therefore, conservation is also argued by using particular biodiversity metrics, context dependently, e.g., spatial conservation prioritization, design of protected areas network.Individual descriptive information accumulated in biogeography, ecology, physiology, molecular biology, taxonomy, and paleontology are aggregated through the spatial coordinates of biological distributions. Such biodiversity big data enables to visualize geography of 1) the richness of nature, 2) the value of nature, and 3) the uncertainty of nature, based on statistical models including maximum likelihood, machine learning, deep learning techniques. This special issue focuses on statistical and mathematical methods in terms of the quantitative visualization of biodiversity concepts. We hope that this special issue serves as an opportunity to involve researchers from different fields interested in biodiversity information and to develop into new research projects related to Nature Positive by 2030 that aims at halting and reversing the loss of biodiversity and ecosystem service.

著者

上村 鋼平

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.33, no.1, pp.77-99, 2012-08-31 (Released:2012-10-02)

参考文献数

74

---

Recently, it is becoming more challenging to cope with low success probabilities, much cost and severe competitions in a new drug development. An adaptive design is considered to be a promising tool for efficient development for its various types of adaptations and applications in multiple development stages. However, its flexibility does not necessarily make the development more efficient and it may always allow a risk of operational bias to use such a design. Thus, to consider the specific benefit and risk of each adaptive design using quantitative measures under a concrete setting, it is important to make intensive discussions and to share experiences between each side persons in charge. In this review, focusing on sample size re-estimation which is a relatively simple and basic adaptive design, I will give some outlines of methods and review statistical points to consider.

著者

山口 拓洋

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.26, no.2, pp.81-117, 2005-12-31 (Released:2011-09-30)

参考文献数

102

被引用文献数

3 3

---

Recurrent events data such as epileptic seizures and recurrence of superficial bladder cancer are frequently encountered in medical researches when individuals may experience multiple events of the same type. The analysis of recurrent events is complicated because related recurrent events within a subject are correlated and we need to take into account the dependence of responses from the same subject to draw valid statistical inferences. In principle, statistical strategies are classified into two approaches. The one is we focus on the number of events occurring within defined time intervals and compare / model the event rate (number of events per unit of time). The other is the recurrence times are viewed as multivariate failure times and survival analysis methods are applied. According to this perspective, we review several statistical methods to analyze recurrent events data and illustrate the techniques with real medical applications. We recommend that the choice of the endpoint (effect measure) and the corresponding statistical analysis method should be determined by the study purpose. Robust methods for the assumption of event occurring process should be used especially for analyzing confirmatory studies.

著者

三輪 哲久

出版者

日本計量生物学会

雑誌

計量生物学 (ISSN:09184430)

巻号頁・発行日

vol.38, no.2, pp.163-170, 2018-03-01 (Released:2018-05-18)

参考文献数

12

---

In 2016 the American Statistical Association published “ASA Statement on Statistical Significance and P-Values.” In this statement it seems that the use of statistical tests or p-values is discouraged because they are misused and misinterpreted. I doubt whether a statistical procedure such as test of significance should be rejected because it is misused and misinterpreted. I pose some questions about the ASA statement.