定性资料统计分析错误辨析与释疑

通过揭示大量的生物医学科研中出现的定性资料统计分析方面的错误案例,说明重视识别定性资料列联表的类型、检查前提条件和考虑统计分析目的,对于合理选用定性资料统计分析方法是至关重要的。     

实验设计错误辨析与释疑

本文介绍了实验设计的核心内容,并针对人们在进行临床试验设计时,常违犯对照和均衡原则的事实,举出了很多常见的实例。通过对这些实例的辨析和释疑,有利于提高临床医生的实验设计质量。     

如何用SAS软件正确分析生物医学科研资料——Ⅰ．用SAS实现单组设计定量资料的统计分析

生物统计学是生物学领域科学研究和实际工作中必不可少的工具,在分子生物学迅速发展的今天,生物统计学更显示出了它的重要性。实验设计与数据统计分析是现代生物学的基石,是生物学研究者检验假说、寻找模式、建立生物学理论的有利工具,也是生物学研究者探索微观和宏观生物世界的必备基础知识。对于每天甚至是每时每刻涌现的大量的、以天文数字计量的分子遗传数据,必须借助统计学知识加以分析处理,才能从中获得有意义的信息。     

如何用SAS软件正确分析生物医学科研资料 X.用SAS软件实现嵌套设计和裂区设计定量资料的统计分析

生物统计学是生物学领域科学研究和实际工作中必不可少的工具,在分子生物学迅速发展的今天,生物统计学更显示出了它的重要性。实验设计与数据统计分析是现代生物学的基石,是生物学研究者检验假说、寻找模式、建立生物学理论的有利工具,也是生物学研究者探索微观和宏观生物世界的必备基础知识。对于每天甚至是每时每刻涌现的大量的、以天文数字计量的分子遗传数据,必须借助统计学知识加以分析处理,才能从中获得有意义的信息。"生物多样性数据分析"是开展生物多样性研究的一个重要方面,数据分析能力的高低极大地影响着我们对各种生态学现象认识的深度和广度。现在,电子计算机的普及使得生物统计分析过程大大简化,生物统计分析软件包的普及将生物统计学从统计学家的书本里解放了出来,简化了生物统计分析过程,使之成为生物学研究者的常用工具。本刊特邀军事医学科学院生物医学统计学咨询中心主任胡良平教授,以"如何用SAS软件正确分析生物医学科研资料"为题,撰写系列统计学讲座,希望该系列讲座能对生物医学科研工作者有所帮助。     

用SAS软件实现均匀设计定量资料的统计分析

生物统计学是生物学领域科学研究和实际工作中必不可少的工具,在分子生物学迅速发展的今天,生物统计学更显示出了它的重要性。实验设计与数据统计分析是现代生物学的基石,是生物学研究者检验假说、寻找模式、建立生物学理论的有利工具,也是生物学研究者探索微观和宏观生物世界的必备基础知识。     

如何用SAS软件正确分析生物医学科研资料 XV.用SAS软件实现具有一个重复测量的两因素和具有两个重复测量的两因素设计定量资料的统计分析

生物统计学是生物学领域科学研究和实际工作中必不可少的工具,在分子生物学迅速发展的今天,生物统计学更显示出了它的重要性。实验设计与数据统计分析是现代生物学的基石,是生物学研究者检验假说、寻找模式、建立生物学理论的有利工具,也是生物学研究者探索微观和宏观生物世界的必备基础知识。对于每天甚至是每时每刻涌现的大量的、以天文数字计量的分子遗传数据,必须借助统计学知识加以分析处理,才能从中获得有意义的信息。"生物多样性数据分析"是开展生物多样性研究的一个重要方面,数据分析能力的高低极大地影响着我们对各种生态学现象认识的深度和广度。现在,电子计算机的普及使得生物统计分析过程大大简化,生物统计分析软件包的普及将生物统计学从统计学家的书本里解放了出来,简化了生物统计分析过程,使之成为生物学研究者的常用工具。本刊特邀军事医学科学院生物医学统计学咨询中心主任胡良平教授,以"如何用SAS软件正确分析生物医学科研资料"为题,撰写系列统计学讲座,希望该系列讲座能对生物医学科研工作者有所帮助。     

如何用SAS软件正确分析生物医学科研资料 Ⅱ．用SAS软件实现配对设计定量资料的统计分析

生物统计学是生物学领域科学研究和实际工作中必不可少的工具,在分子生物学迅速发展的今天,生物统计学更显示出了它的重要性。实验设计与数据统计分析是现代生物学的基石,是生物学研究者检验假说,寻找模式、建立生物学理论的有利工具,也是生物学研究者探索微观和宏观生物世界的必备基础知识。对于每天甚至是每时每刻涌现的大量的、以天文数字计量的分子遗传数据,必须借助统计学知识加以分析处理,才能从中获得有意义的信息。“生物多样性数据分析”是开展生物多样性研究的一个重要方面,数据分析能力的高低极大地影响着我们对各种生态学现象认识的深度和广度。     

如何用SAS软件正确分析生物医学科研资料Ⅲ．用SAS软件实现成组设计定量资料的统计分析

生物统计学是生物学领域科学研究和实际工作中必不可少的工具,在分子生物学迅速发展的今天,生物统计学更显示出了它的重要性。实验设计与数据统计分析是现代生物学的基石,是生物学研究者检验假说、寻找模式、建立生物学理论的有利工具,也是生物学研究者探索微观和宏观生物世界的必备基础知识。对于每天甚至是每时每刻涌现的大量的、以天文教字计量的分子遗传数据,必须借助统计学知识加以分析处理,才能从中获得有意义的信息。“生物多样性数据分析”是开展生物多样性研究的一个重要方面,数据分析能力的高低极大地影响着我们对各种生态学现象认识的深度和广度。     

如何用SAS软件正确分析生物医学科研资料 IX. 用SAS软件实现交叉设计定量资料的统计分析

生物统计学是生物学领域科学研究和实际工作中必不可少的工具,在分子生物学迅速发展的今天,生物统计学更显示出了它的重要性。实验设计与数据统计分析是现代生物学的基石,是生物学研究者检验假说、寻找模式、建立生物学理论的有利工具,也是生物学研究者探索微观和宏观生物世界的必备基础知识。对于每天甚至是每时每刻涌现的大量的、以天文数字计量的分子遗传数据,必须借助统计学知识加以分析处理,才能从中获得有意义的信息。     

简单线性相关与回归分析错误辨析与释疑

通过揭示大量相关与回归分析方面的错误案例,说明重视基本概念和基本步骤,对于正确应用线性相关与回归分析方法是至关重要的。由于很多人极度贫乏有关的基本知识,现行的很多统计学教科书在这方面又十分薄弱,因此,广大实际工作者加强这方面知识的学习,是十分必要的。     

统计资料表达与描述方面错误辨析与释疑（讲座）

统计资料表达和描述的质量是反映学术论文质量高低的一个方面。作者通过阅读大量医学论文后发现,统计表、统计图、相对数、平均与变异指标的结合应用等方面出错的频率相当高。因此,该讲座通过展示人们在进行统计资料表达和描述时常犯的错误,指出正确的表达和描述方法,并进一步提醒科研人员统计资料表达和描述方面的错误不可小视,只要在思想上引起高度重视,这些错误是可以避免的。     

Common statistical errors in the design and analysis of subfertility trials

BACKGROUND: The quality of clinical trials has received increasing attention with the growth of evidence-based medicine and systematic reviews. We aimed to identify whether errors and omissions commonly encountered when undertaking Cochrane reviews in this field are still passing peer review. METHODS: We undertook a review of trials published in 2001 by two major journals. We selected from Medline only trials in which authors compared pregnancy rates under two interventions by allocating women to different groups. RESULTS: We identified 39 trials meeting our criteria. Six trials were fatally flawed by design, either by inappropriate use of a cross-over design or by systematic allocation described by the authors as 'random'. Only six reports claimed to apply the intention-to-treat principle, and the principle was misunderstood by four of these. Only five trials reported live birth rates sufficiently to allow valid meta-analysis. Most trials (82%) included at least one 'unit of analysis' error. CONCLUSIONS: We selected simple trials from respected journals, assuming that our sample would represent trials of highest methodological quality in the field. Nevertheless, the standards of design, analysis and reporting of many subfertility trials are not sufficient to allow reliable interpretation of results, or inclusion in meta-analyses.     

Discrimination of hyperplasia and carcinoma of the endometrium by quantitative microscopy–a feasibility study

Endometrial hyperplasias and carcinomas have been investigated by quantitative microscopical methods. The aim of this study was to develop an objective method of histopathological diagnosis because of the great subjective variability of these endometrial conditions. A total of 79 cases were studied. Only those were included, which, after re-examination of the material by different pathologists, were regarded as mild atypical hyperplasia (38 cases), marked atypical (adenomatous) hyperplasia (11 cases), well and moderately differentiated adenocarcinoma (19 and 11 cases, respectively). There are many significant differences between these four groups. Stereological features contained the most important information, whilst nuclear features were less successful discriminators. The volume percentage of the epithelium and of the glands and the inner surface density of the glands showed the most significant differences between adenomatous hyperplasia and well differentiated carcinoma. On the basis of these findings, a quantitative model is suggested which might give more insight into the development of these abnormalities, assuming a gradual transition from one to another. The great advantage of the quantitative analysis of data over subjective impressions, it that is is objective, and provides consistently reproducible results. The present results may be especially useful when histopathological diagnosis is in doubt. It is concluded that application of quantitative microscopy in the discrimination of endometrial hyperplasia and carcinoma in histopathology is feasible.     

A quantitative statistical analysis of the submentalis muscle EMG amplitude during sleep in normal controls and patients with REM sleep behavior disorder

The aim of this study was to evaluate quantitatively the amplitude of the submentalis muscle EMG activity during sleep in controls and in patients with idiopathic REM sleep behavior disorder (RBD) or with RBD and multiple system atrophy (MSA). We recruited 21 patients with idiopathic RBD, 10 with MSA, 10 age-matched and 24 young normal controls. The average amplitude of the rectified submentalis muscle EMG signal was used for the assessment of atonia and a Sleep Atonia Index was developed; moreover, also chin muscle activations were detected and their duration and interval analyzed. The Sleep Atonia Index was able to distinguish clearly REM from NREM sleep in normal controls with values very close to 1 in young normal subjects and only slightly (but significantly) lower in old controls. Idiopathic RBD patients showed a further significant decrease of this index; MSA patients showed the lowest values of REM Sleep Atonia Index, which were very well distinguishable from those of normal controls and of idiopathic RBD patients. The distribution of the duration of chin activations was monomodal in all groups, with idiopathic RBD patients showing the highest levels. This study is a really quantitative attempt to provide practical indices for the objective evaluation of EMG atonia during REM sleep and of EMG activations. Our proposed Sleep Atonia Index can have a practical application in the clinical evaluations of patients and represents an additional useful parameters to be used in conjunction with the other criteria for the diagnosis of this sleep motor disorder.     

Quantifying the pathology of neurodegenerative disorders: quantitative measurements,sampling strategies and data analysis

The use of quantitative methods has become increasingly important in the study of neurodegenerative disease. Disorders such as Alzheimer's disease (AD) are characterized by the formation of discrete, microscopic, pathological lesions which play an important role in pathological diagnosis. This article reviews the advantages and limitations of the different methods of quantifying the abundance of pathological lesions in histological sections, including estimates of density, frequency, coverage, and the use of semiquantitative scores. The major sampling methods by which these quantitative measures can be obtained from histological sections, including plot or quadrat sampling, transect sampling, and point-quarter sampling, are also described. In addition, the data analysis methods commonly used to analyse quantitative data in neuropathology, including analyses of variance (anova) and principal components analysis (PCA), are discussed. These methods are illustrated with reference to particular problems in the pathological diagnosis of AD and dementia with Lewy bodies (DLB).     

Model-Based Multifactor Dimensionality Reduction to detect epistasis for quantitative traits in the presence of error-free and noisy data

Detecting gene-gene interactions or epistasis in studies of human complex diseases is a big challenge in the area of epidemiology. To address this problem, several methods have been developed, mainly in the context of data dimensionality reduction. One of these methods, Model-Based Multifactor Dimensionality Reduction, has so far mainly been applied to case-control studies. In this study, we evaluate the power of Model-Based Multifactor Dimensionality Reduction for quantitative traits to detect gene-gene interactions (epistasis) in the presence of error-free and noisy data. Considered sources of error are genotyping errors, missing genotypes, phenotypic mixtures and genetic heterogeneity. Our simulation study encompasses a variety of settings with varying minor allele frequencies and genetic variance for different epistasis models. On each simulated data, we have performed Model-Based Multifactor Dimensionality Reduction in two ways: with and without adjustment for main effects of (known) functional SNPs. In line with binary trait counterparts, our simulations show that the power is lowest in the presence of phenotypic mixtures or genetic heterogeneity compared to scenarios with missing genotypes or genotyping errors. In addition, empirical power estimates reduce even further with main effects corrections, but at the same time, false-positive percentages are reduced as well. In conclusion, phenotypic mixtures and genetic heterogeneity remain challenging for epistasis detection, and careful thought must be given to the way important lower-order effects are accounted for in the analysis.     

Array-CGH and quantitative PCR genetic analysis in a case with bilateral hypoplasia of pulmonary arteries and lungs and simultaneous unilateral renal agenesis

We describe the clinical course and have characterised anatomically and genetically a unique case of a newborn with bilateral hypoplasia of pulmonary arteries, consecutive extremely hypoplastic lung tissue and associated unilateral renal agenesis. Intrauterine oxygenation by the placenta seemed to have allowed normotrophic body maturity but immediately after delivery, in the third trimester, progressive hypoxemia developed and the newborn succumbed to acute respiratory failure. Genetic analysis by array-based comparative genomic hybridisation and quantitative PCR revealed duplication of 1p21, which, however, might not be the disease causing aberration. This case might represent an extreme form of previously reported, rare cases with simultaneous dysorganogenesis of lungs and kidneys.