浙江省传染病网报数据分析和利用调查

目的：了解浙江省基层CDC对传染病网络直报数据分析和利用的现状．为制订网报数据分析方案，建立有效利用直报数据的机制提供依据。方法：采用自填式问卷调查全省基层CDC中传染病网络直报工作相关人员．资料录入Epidata数据库．运用SPSS软件进行统计分析。结果：网报主要用于查看疫情，对数据的利用进行疫情预警监测的较少（27．48％），96．04％的人员使用Excel对直报数据进行整理和分析，其次为EpiData（47．79％），而SAS、Stata等软件的使用率较低。软件使用熟练程度最高的是Excel（54．37％），其他软件使用熟练程度均较差。影响数据分析利用的主要原因是学历和统计软件的掌握。结论：目前浙江省基层CDC直报工作相关人员对直报数据的分析和利用程度较低，数据的统计技能不高．急需加强网络直报人员的培训。     

基于物联网的血液净化中心信息系统设计

目的：结合血透中心在日常管理和运行过程中存在的问题和需求，设计一套血液透析中心信息化解决方案。方法：根据血透中心的业务流程，利用物联网思维，设计一套血液透析中心信息化解决方案，系统流程包括患者刷卡签到、体重采集、血压采集、患者日常排班、医嘱下达、透析评估及不良事件警示；以及医嘱管理、通路管理、科室管理、库存管理、费用管理、设备管理、实现掌上电脑手持终端和各项指标统计。结合临床业务流程完成全过程信息化管理。结果：通过物联网手段实现血透设备硬件对接，集中高效管理并与院内医院信息系统、实验室信息管理系统等软件对接，实现数据上报功能。结论：该项系统能提高医务人员工作效率，规范业务流程、降低医疗风险、减少工作强度，降低血透中心运营成本，积累患者检查数据便于后期拓展分析，并有效地实现了科室的动态管理。     

空气污染人群健康影响监测信息系统在线统计分析功能的设计与实现

目的实现空气污染人群健康影响监测信息系统的在线统计分析功能,实时获取数据分析信息。方法采用描述性统计方法并结合后续时间序列分析、多元回归分析,利用SQL语言和可视化工具,基于数据库软件在监测系统中实现在线统计分析。结果在线生成空气污染暴露和人群健康数据的基础统计表和汇总统计表;在线生成数据趋势图并通过连接数据库进行交互;在线生成可直接导入R语言、SAS或SPSS软件进行分析的对接表。结论空气污染人群健康影响监测信息系统可实现在线统计分析功能,为使用者提供实时的数据分析结果。     

当代名中医痢疾医案43则中药配伍及方证规律的数据挖掘分析

目的探讨当代名中医治疗痢疾的中药配伍及方证规律。方法收集43篇医案,采用关联规则与频数分析方法进行统计,数据分析在SPSS Clementine统计软件上进行。结果四诊信息与中药、病因与中药、证候与中药之间有对应规律,根据关联规则挖掘提出的基本方与中医证治痢疾理论切合。结论采取关联规则与频数分析方法能较好地挖掘名老中医关于痢疾的中药配伍及方证规律的经验。     

当代名中医痢疾医案43则中药配伍及方证规律的数据挖掘分析

目的探讨当代名中医治疗痢疾的中药配伍及方证规律。方法收集43篇医案,采用关联规则与频数分析方法进行统计,数据分析在SPSS Clementine统计软件上进行．结果四诊信息与中药、病因与中药、证候与中药之间有对应规律,根据关联规则挖掘提出的基本方与中医证治痢疾理论切合。结论采取关联规则与频数分析方法能较好地挖掘名老中医关于痢疾的中药配伍及方证规律的经验。     

不同行业人群健康知识知晓与行为调查

目的：评价分析不同行业人群的卫生行为形成率和健康知识知晓率，探求开展行业健康教育的工作方法和措施。方法：调查人员到机关、卫生单位、食品行业单位进行随机抽样，自行设计问卷调查。结果：卫生行为的形成和健康知识的知晓表现为卫生组强于机关组，机关组强于食品行业组，经卫生学统计处理存在差异无统计学意义。结论：有针对性和目的性地抓好不同行业人群的健康教育，实现全社会人人健康的目标。     

基于R软件的多组独立样本秩和检验的多重比较

目的基于R软件实现Kruskal-Wallis秩和检验的多重比较。方法本文结合实例数据,采用pgirmess软件统计包的kruskalmc函数,实现多组秩和检验的两两比较方法。结果 R软件的kruskalmc函数可显示基于默认检验水准α=0.05,完全随机化设计多个样本比较的秩和检验的两两比较结果。结论通过R软件实现多组秩和检验的多重比较分析是一种简便可行的方法。     

关于统计软件数据分析模块功能设计探讨

随着计算机技术的发展，医院统计室工作模式发生了革命性变化，由过去手工统计方式转变为现在使用计算机软件统计方式，医院统计软件的使用，大大提高了统计工作效率，方便了对统计数据的分析与调用。但由于医院性质、医院级别不同等原因，全国目前有多个版本的统计软件在使用，这些软件都能完成医院常用统计工作，产生需要的统计报表与统计指标．但在对统计数据、指标常规分析上存在不小的差异。笔者结合多年医院统计软件开发经验，提出了医院统计软件数据分析模块应具备的功能。     

组内相关系数及其软件实现

目的 介绍可靠性评价指标组内相关系数及其统计软件实现.方法 结合实例阐明各种不同类型组内相关系数的意义、计算和SAS、SPSS软件实现.结果 选择恰当的ICC取决于以下三个方面,选择的模型是one-waymodel或two-way model:采用single measure或average measure:选择absolute agreement或consistency.结论 研究者应根据资料类型和分析目的选择恰当的组内相关系数,SAS和SPSS可提供计算结果.     

结合分析方法及其在SAS中的统计实现

目的阐述结合分析方法的基本原理及探讨如何在统计软件SAS中完成该统计分析。方法通过案例说明结合分析在SAS8．2中的统计实现及在应用中应注意的问题。结果在SAS中，可以通过编程和图形用户界面两种途径实现结合分析的统计。结论结合分析是一种定量地测量消费者选择偏好的研究方法，与传统的直接询问式分析方法相比有其独特的优势，并可在SAS中实现统计。     

Les enquêtes cas–cohorte

In this paper, we present the main tools for conception, implementation and analysis of case–cohort surveys. In particular, we describe the classical weighted estimators, the weighted approach recently suggested by Breslow et al. and the multiple imputation approach, an alternative to weighted analysis of case–cohort data. Variance estimators are also described. We show how to obtain the subcohort size. Finally, we mention the functions and procedures available in R, SAS and Stata software and we illustrate their implementation using simulated subcohorts from the PRIME cohort.     

Potential for bias in case-crossover studies with shared exposures analyzed using SAS

The case-crossover method is an efficient study design for evaluating associations between transient exposures and the onset of acute events. In one common implementation of this design, odds ratios are estimated using conditional logistic or stratified Cox proportional hazards models, with data stratified on each individual event. In environmental epidemiology, where aggregate time-series data are often used, combining strata with identical exposure histories may be computationally convenient. However, when the SAS software package (SAS Institute Inc., Cary, North Carolina) is used for analysis, users can obtain biased results if care is not taken to properly account for multiple cases observed at the same time. The authors show that fitting a stratified Cox model with the "Breslow" option for handling tied failure times (i.e., ties = Breslow) provides unbiased health-effects estimates in case-crossover studies with shared exposures. The authors' simulations showed that using conditional logistic regression-or equivalently a stratified Cox model with the "ties = discrete" option-in this setting leads to health-effect estimates which can be biased away from the null hypothesis of no association by 22%-39%, even for small simulated relative risks. All methods tested by the authors yielded unbiased results under a simulated scenario with a relative risk of 1.0. This potential bias does not arise in R (R Foundation for Statistical Computing, Vienna, Austria) or Stata (Stata Corporation, College Station, Texas).     

Analysis of 2 x 2 tables of frequencies: matching test to experimental design

BACKGROUND: Biomedical investigators often use unsuitable statistical techniques for analysing the 2 x 2 tables that result from their experimental observations. This is because they are confused by the conflicting, and sometimes inaccurate, advice they receive from statistical texts or statistical consultants. METHODS: These consist of a review of published work, and the use of five different statistical procedures to analyse a 2 x 2 table, executed by StatXact 8.0, Testimate 6.0, Stata 10.0, SAS 9.1 and SPSS 16.0. Discussion and Conclusions It is essential to classify a 2 x 2 table before embarking on its analysis. A useful classification is into (i) Independence trials (doubly conditioned). These almost never occur in biomedical research because they involve predetermining the column and row totals in a 2 x 2 table. The Fisher exact test is the best method for analysing these trials. (ii) Comparative trials (singly conditioned). These correspond to the usual experimental design in biomedical work, in which a sample of convenience is randomized into two treatment groups, so that the group (column) totals are fixed in advance. The proper tests of significance are exact tests on the odds ratio, on the ratio of proportions (relative risk and risk ratio) or on the difference between proportions. (iii) Double dichotomy trials (unconditional). In these, a genuine random sample is taken from a defined population. Thus, neither column nor row totals are fixed in advance. The only practicable test is Pearson's chi(2)-test. In analysing any of the above trials, exact tests are to be much preferred to asymptotic (approximate) tests. The different commercial software packages use different algorithms for exact tests, and can give different outcomes in terms of P-values and confidence intervals. The most useful are StatXact and Testimate.     

城乡社区慢性病患者的消费及服务需求调查

目的调查了解城乡慢性病患者的医疗消费能力以及在"4P"医学模式上对社区卫生服务的服务需求,提出加大医疗投入及加强医患沟通等建议。方法以封闭式调查问卷以及面对面访谈的形式进行调查;回收问卷后,对问卷进行描述,SPSS17.0统计学软件统计、分析并处理。结果城乡慢性病患者的社区卫生服务消费能力不足,社区卫生服务不能从服务质量、心理服务等方面满足城乡慢性病患者的看病需求。结论加大力度解决患者看病问题和从"4P"医学模式上更好地为广大慢性病患者服务。     

配对四格表资料χ2检验在 SPSS 和 SAS 软件中的实现

目的：通过实例来介绍配对四格表资料的卡方检验在SPSS和SAS统计分析软件中如何操作,输出结果的区别及正确的解读,为临床及相关科研人员提供可以借鉴的方法。方法使用SPSS和SAS统计软件,对配对四格表资料的卡方检验进行操作和分析。结果本文以两种方法诊断肺癌的检测结果为例题,根据基本公式算得统计量χ2＝4．92,P＜0．05,得出两种诊断方法的诊断结果存在差异。在SPSS软件的分析结果中只有P值,SAS软件的分析结果可以给出统计量和P的确切值,但统计量χ2＝6．23,与基本公式计算的结果不同,经过自编程序运行后,我们得到了与基本公式相同的结果。结论 SPSS和SAS统计软件是医学统计学数据分析的常用教学软件,本文通过实例详解,得出在结果的输出方面两种软件有很大区别,但这并不影响我们得出相同的统计结论。 SPSS软件操作简便,SAS软件编程比较麻烦,以及SAS软件在处理此类资料上存在默认不校正的问题,因此,在实际应用中,我们可以根据情况自行选择。     

More powerful procedures for multiple significance testing

The problem of multiple comparisons is discussed in the context of medical research. The need for more powerful procedures than classical multiple comparison procedures is indicated. To this end some new, general and simple procedures are discussed and demonstrated by two examples from the medical literature: the neuropsychologic effects of unidentified childhood exposure to lead, and the sleep patterns of sober chronic alcoholics.     

A longitudinal model for magnetic resonance imaging lesion count data in multiple sclerosis patients

Magnetic resonance imaging (MRI) data are routinely collected at multiple time points during phase 2 clinical trials in multiple sclerosis. However, these data are typically summarized into a single response for each patient before analysis. Models based on these summary statistics do not allow the exploration of the trade-off between numbers of patients and numbers of scans per patient or the development of optimal schedules for MRI scanning. To address these limitations, in this paper, we develop a longitudinal model to describe one MRI outcome: the number of lesions observed on an individual MRI scan. We motivate our choice of a mixed hidden Markov model based both on novel graphical diagnostic methods applied to five real data sets and on conceptual considerations. Using this model, we compare the performance of a number of different tests of treatment effect. These include standard parametric and nonparametric tests, as well as tests based on the new model. We conduct an extensive simulation study using data generated from the longitudinal model to investigate the parameters that affect test performance and to assess size and power. We determine that the parameters of the hidden Markov chain do not substantially affect the performance of the tests. Furthermore, we describe conditions under which likelihood ratio tests based on the longitudinal model appreciably outperform the standard tests based on summary statistics. These results establish that the new model is a valuable practical tool for designing and analyzing multiple sclerosis clinical trials.     

Block design allowed for control of the Hawthorne effect in a randomized controlled trial of test ordering

BACKGROUND AND OBJECTIVE: To evaluate the value of balanced incomplete block designs in quality improvement research, and their capacity to control for the Hawthorne effect. METHODS: General practitioners teams were randomized into three arms and received an intervention on test ordering, relating to tests for two groups of clinical problems (A tests and B tests). In the two trials within the block design, we tried to control for the Hawthorne effect by comparing the complete intervention in both arms on either the A (arm I) or B tests (arm II); the arms acted as blind controls for each other. In the classical trial, the complete intervention on B tests (arm II) was compared with a control arm without any intervention on B tests (arm III). RESULTS: The trials with the block design yielded statistically significant changes in the numbers of A tests ordered (P=.013), but not in the numbers of B tests ordered (P=.29). In the classical design, the complete intervention reached a marginally significant change in the B tests (P=.068). The Hawthorne effect was the same for both arms of the block design. In the classical design, the effect could to some extent be attributed to the Hawthorne effect. CONCLUSION: Our block design allowed us to control for the Hawthorne effect. Suitable use of block designs may further our knowledge of nonspecific effects in quality improvement research.     

Statistics in medical journals: some recent trends

I review some areas of medical statistics that have gained prominence over the last 5-10 years: meta-analysis, evidence-based medicine, and cluster randomized trials. I then consider several issues relating to data analysis and interpretation, many relating to the use and misuse of hypothesis testing, drawing on recent reviews of the use of statistics in medical journals. I also consider developments in the reporting of research in medical journals.