Matti Langel and Yves Tillé (University of Neuchâtel, Switzerland) published in Journal of the Royal Statistical Society: Series A (Statistics in Society) Volume 176 Issue 2 (February 2013)
Summary
Since Corrado Gini suggested the index that bears his name as a way of measuring inequality, the computation of variance of the Gini index has been subject to numerous publications.
We survey a large part of the literature related to the topic and show that the same results, as well as the same errors, have been republished several times, often with a clear lack of reference to previous work.
Whereas existing literature on the subject is very fragmented, we regroup references from various fields and attempt to bring a wider view of the problem. Moreover, we try to explain how this situation occurred and the main issues that are involved when trying to perform inference on the Gini index, especially under complex sampling designs.
The interest of several linearization methods is discussed and the contribution of recent references is evaluated. Also, a general result to linearize a quadratic form is given, allowing the approximation of variance to be computed in only a few lines of calculation.
Finally, the relevance of the regression-based approach is evaluated and an empirical comparison is proposed.
Showing posts with label sampling. Show all posts
Showing posts with label sampling. Show all posts
Thursday, 14 February 2013
Monday, 19 December 2011
Adaptive browsing: Sensitivity to time pressure and task difficulty
an article by Susan C. Wilkinson (University of Wales Institute Cardiff) Will Reader (Sheffield Hallam University) and Stephen J. Payne (University of Bath) published in International Journal of Human-Computer Studies Volume 70 Issue 1 (January 2012)
Abstract
Two experiments explored how learners allocate limited time across a set of relevant on-line texts, in order to determine the extent to which time allocation is sensitive to local task demands. The first experiment supported the idea that learners will spend more of their time reading easier texts when reading time is more limited; the second experiment showed that readers shift preference towards harder texts when their learning goals are more demanding.
These phenomena evince an impressive capability of readers. Further, the experiments reveal that the most common method of time allocation is a version of satisficing (Reader and Payne, 2007) in which preference for texts emerges without any explicit comparison of the texts (the longest time spent reading each text is on the first time that text is encountered). These experiments therefore offer further empirical confirmation for a method of time allocation that relies on monitoring on-line texts as they are read, and which is sensitive to learning goals, available time and text difficulty.
Abstract
Two experiments explored how learners allocate limited time across a set of relevant on-line texts, in order to determine the extent to which time allocation is sensitive to local task demands. The first experiment supported the idea that learners will spend more of their time reading easier texts when reading time is more limited; the second experiment showed that readers shift preference towards harder texts when their learning goals are more demanding.
These phenomena evince an impressive capability of readers. Further, the experiments reveal that the most common method of time allocation is a version of satisficing (Reader and Payne, 2007) in which preference for texts emerges without any explicit comparison of the texts (the longest time spent reading each text is on the first time that text is encountered). These experiments therefore offer further empirical confirmation for a method of time allocation that relies on monitoring on-line texts as they are read, and which is sensitive to learning goals, available time and text difficulty.
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