作者: Jeffrey M. Girard , Jeffrey F. Cohn
关键词: Data mining 、 Psychology 、 Reliability (statistics) 、 Variety (cybernetics) 、 Data science 、 Observational methodology 、 Observational study 、 Interobserver reliability 、 Affective computing 、 Fully automated 、 Observer (quantum physics)
摘要: Observational measurement plays an integral role in a variety of scientific endeavors within biology, psychology, sociology, education, medicine, and marketing. The current article provides interdisciplinary primer on observational measurement; particular, it highlights recent advances methodology the challenges that accompany such growth. First, we detail various types instrument can be used to standardize measurements across observers. Second, argue for importance validity provide several approaches validation based contemporary theory. Third, outline currently faced by researchers pertaining drift, observer reactivity, reliability analysis, time/expense. Fourth, describe computer-assisted measurement, fully automated statistical data analysis. Finally, identify key directions future research explore.