The problem of inference from curves based on group data.

By Estes Wk. 1956

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Citations in the corpus

How algorithmic popularity bias hinders or promotes quality (2017, background): “ how people click search engine results [10] and scroll through social media feeds [26]. This model could accurately capture aggregate behavior even if individuals followed dierent selection schemes [8]. Alternatively, with probability 1 , an item is drawn with probability proportional to its qualit”
Dynamic Development of Action and Thought (2007, background): “Often the deviations are ignored, as researchers mistakenly use methods that sum across individuals, activities, and contexts and treat true variations in level as errors of measurement (Estes, 1956; Fischer, Knight, & Van Parys, 1993; Skinner, 1938; van Geert & van Dijk, 2002).”
Response Errors Explain the Failure of Independent-Channels Models of Perception of Temporal Order (2012, background): “05) but also because analyzing data aggregated across observers poses serious problems (Estes, 1956; Estes and Maddox, 2005).”
The power law repealed: The case for an exponential law of practice (2000, background): “the same form as the individual curves comprising the average (e.g., Estes, 1956; Kling, 1971;”
Methodological and empirical developments for the Ratcliff diffusion model of response times and accuracy (2009, result): “In contrast to the field of psychometrics, where individual differences are the main topic of investigation, the field of experimental psychology has traditionally ignored individual differences, pretending instead that each new participant is a replicate of the previous one (Batchelder, 2007 ) As ”