气候变化领域集成服务门户

The utility and credibility of environmental assessments depend on the use of unbiased data. However, it is increasingly clear that, despite peer review, much of the scientific literature is biased. Sources of bias include publication practices, research design and implementation, funding influences, investigator expectations, statistical methods, confounding, suppression, and fraud. Assessors can take precautions against biased data by performing their own reviews of the sources of data, checking for retractions and corrections, requiring full disclosure of methods, acquiring original data and reanalyzing it, avoiding secondary sources, avoiding unreplicated studies or studies that are not concordant with related studies, and checking for funding or investigator biases. Journals, government agencies, and other institutions can take many more types of actions to reduce bias in scientific data. Some of these are already being implemented but others will require a greater willingness to enforce scientific ethical standards.