数据收集
数据科学
鉴定(生物学)
度量(数据仓库)
计算机科学
光学(聚焦)
选择(遗传算法)
心理学
数据挖掘
统计
人工智能
植物
物理
数学
光学
生物
标识
DOI:10.1191/0269215504cr183ed
摘要
The terms 'measurement' and 'assessment' are often used interchangeably, especially when referring to the tools used to collect information. This leads to unclear thinking, and often to poor selection of a 'measure' or 'assessment'. This editorial suggests that we should distinguish between the identification of the data needed for some purpose, the methods used to collect data, and the use made of (interpretation of) the data collected. This would focus more attention on the three most important questions to consider when collecting data, whether in day-to-day clinical practice or in research: Why should the data be collected? How should the data be collected? and How should the results be interpreted?
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