Callas P W, Pastides H, Hosmer D W
Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst 01003-0430.
Occup Environ Med. 1994 Oct;51(10):649-55. doi: 10.1136/oem.51.10.649.
This survey was conducted to determine the frequency with which different data analysis techniques are being used in occupational cohort studies. Of particular interest was the relative use of external and internal comparison groups, and the choice of multivariable model.
Occupational cohort studies published in 1990-91 were located with Medline and Index Medicus, and the contents of several relevant journals were systematically reviewed. Each study was categorised by the methods of external or internal comparisons performed.
Of 200 occupational cohort studies identified, 104 (52%) conducted only external comparisons, 46 (23%) conducted only internal, and 50 (25%) presented both. Of those that used an external referent population, about two thirds used a national standard. 40 of the studies that performed internal comparisons fitted multivariable models, with use divided about equally between proportional hazards regression, Poisson regression, and logistic regression.
The finding that logistic regression is used quite commonly, even though it does not directly model time dependent data of the type frequently encountered in occupational cohort studies, was suprising. The reasons why investigators choose from among the available statistical and modelling techniques are likely to include familiarity, ease of use, restrictions in study population characteristics, especially study size, and others. Authors should be encouraged to be more explicit about the statistical methods used in the analysis of occupational cohort studies, as well as whether important assumptions about their data have been evaluated.
开展此项调查以确定不同数据分析技术在职业队列研究中的使用频率。特别令人感兴趣的是外部和内部比较组的相对使用情况以及多变量模型的选择。
利用医学索引数据库（Medline）和医学索引（Index Medicus）查找1990 - 1991年发表的职业队列研究，并对几种相关期刊的内容进行系统综述。每项研究按所进行的外部或内部比较方法进行分类。
在确定的200项职业队列研究中，104项（52%）仅进行了外部比较，46项（23%）仅进行了内部比较，50项（25%）两者都有。在使用外部参照人群的研究中，约三分之二采用了国家标准。进行内部比较的40项研究拟合了多变量模型，比例风险回归、泊松回归和逻辑回归的使用大致相当。
逻辑回归虽不能直接对职业队列研究中经常遇到的那种时间依赖性数据进行建模，但却被相当普遍地使用，这一发现令人惊讶。研究人员从可用的统计和建模技术中进行选择的原因可能包括熟悉程度、易用性、研究人群特征的限制，尤其是研究规模等。应鼓励作者更明确地说明职业队列研究分析中所使用的统计方法，以及是否对其数据的重要假设进行了评估。
