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When the population standard deviation is unknown and the sample size is large, the sample standard deviation s is commonly used as a point estimate of σ. However, it can sometimes under or overestimate the population standard deviation. To overcome this drawback, confidence intervals are determined to estimate population parameters and eliminate any calculation bias accurately. However, this only applies to random samples from normally distributed populations. Knowing the sample mean and...
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Lexical Decision Task for Studying Written Word Recognition in Adults with and without Dementia or Mild Cognitive Impairment
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Estimating latent reader-performance variability using the Obuchowski-Rockette method.

Stephen L Hillis1, Badera Al Mohammad2, Patrick C Brennan2

  • 1Departments of Radiology and Biostatistics, University of Iowa, Iowa City, IA, USA.

Proceedings of Spie--The International Society for Optical Engineering
|May 12, 2020
PubMed
Summary
This summary is machine-generated.

The Obuchowski-Rockette (OR) method accurately estimates latent reader performance variability in diagnostic studies, unlike traditional methods that overestimate differences due to measurement error. This improves understanding of true radiologist abilities.

Keywords:
AUCObuchowski-RocketteVariabilitydiagnostic radiologyreader performance

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Area of Science:

  • Medical Imaging Analysis
  • Radiology Research
  • Statistical Modeling in Medicine

Background:

  • Traditional methods for assessing reader performance variability in diagnostic studies, such as estimating the area under the ROC curve (AUC), often include measurement error.
  • This measurement error leads to overestimation of latent reader variability and results that are dependent on case sample size.

Purpose of the Study:

  • To introduce and illustrate the Obuchowski-Rockette (OR) method for estimating the variability of latent reader-performance outcomes in multi-reader diagnostic studies.
  • To demonstrate how the OR method overcomes the limitations of conventional approaches by accounting for measurement error.

Main Methods:

  • The Obuchowski-Rockette (OR) method was applied to analyze multi-reader diagnostic study data.
  • Latent reader performance outcomes, specifically the area under the ROC curve (AUC), were estimated.
  • A dataset of 29 radiologists reading 60 chest computed tomography (CT) scans was used for illustration.

Main Results:

  • The OR method estimated the middle 95% range for latent AUC values to be 0.07.
  • In contrast, the conventional method estimated the 95% range for observed AUCs to be 0.18.
  • This highlights that conventional methods significantly overstate the variability in true reader abilities.

Conclusions:

  • The Obuchowski-Rockette (OR) method provides a more accurate estimation of latent reader variability by excluding measurement error.
  • Accurate estimation of reader performance variability is crucial for reliable interpretation of diagnostic study results.
  • The findings underscore the importance of employing advanced statistical methods to avoid overstating differences in radiologist performance.