"There can be personal bias in reading non-digital instruments or estimating certain quantities. This is referred to as the 'personal equation'. One example is a mercury thermometer. Mercury has a lower surface tension in contact with glass, than in contact with air, so a meniscus forms on top of the mercury column in a glass tube. This results in a subjective reading, notably in estimating values between the marks on the scale (1). Another example is the estimation of cloudiness. Apparently many people prefer reporting cloudiness as 1 or 3 or 7 oktas rather than other values (2). Sometimes a discontinuity in a time series of station temperature, cloudiness, or other meteorological variable can be attributed to a staff change. The personal equation is an important factor in other sciences such as anthropometry, demography, geography, and physics (1)."
E.T. Linacre [no relation to Editor of RMT]
(1) Cox, N.J. 1991. Human factors. Nature 353, 597.
(2) Linacre, E.T. 1992. Climate Data & Resources. Routledge.
Hard science sometimes somewhat soft, Linacre E.T. Rasch Measurement Transactions, 2004, 18:3 p. 994
|Rasch Measurement Transactions (free, online)||Rasch Measurement research papers (free, online)||Probabilistic Models for Some Intelligence and Attainment Tests, Georg Rasch||Applying the Rasch Model 3rd. Ed., Bond & Fox||Best Test Design, Wright & Stone|
|Rating Scale Analysis, Wright & Masters||Introduction to Rasch Measurement, E. Smith & R. Smith||Introduction to Many-Facet Rasch Measurement, Thomas Eckes||Invariant Measurement: Using Rasch Models in the Social, Behavioral, and Health Sciences, George Engelhard, Jr.||Statistical Analyses for Language Testers, Rita Green|
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