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Attrition Bias in Panel Data: A Sheep in Wolf's Clothing? A Case Study Based on the Mabel Survey

Overview of attention for article published in Health economics (Online), May 2015
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Title
Attrition Bias in Panel Data: A Sheep in Wolf's Clothing? A Case Study Based on the Mabel Survey
Published in
Health economics (Online), May 2015
DOI 10.1002/hec.3206
Pubmed ID
Authors

Terence C Cheng, Pravin K Trivedi

Abstract

This paper investigates the nature and consequences of sample attrition in a unique longitudinal survey of medical doctors. We describe the patterns of non-response and examine if attrition affects the econometric analysis of medical labour market outcomes using the estimation of physician earnings equations as a case study. We compare the econometric gestimates obtained from a number of different modelling strategies, which are as follows: balanced versus unbalanced samples; an attrition model for panel data based on the classic sample selection model; and a recently developed copula-based selection model. Descriptive evidence shows that doctors who work longer hours, have lower years of experience, are overseas trained and have changed their work location are more likely to drop out. Our analysis suggests that the impact of attrition on inference about the earnings of general practitioners is small. For specialists, there appears to be some evidence for an economically significant bias. Finally, we discuss how the top-up samples in the Medicine in Australia: Balancing Employment and Life survey can be used to address the problem of panel attrition. Copyright © 2015 John Wiley & Sons, Ltd.

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The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 25%
Student > Master 11 21%
Researcher 10 19%
Student > Bachelor 3 6%
Student > Postgraduate 2 4%
Other 2 4%
Unknown 12 23%
Readers by discipline Count As %
Economics, Econometrics and Finance 17 32%
Social Sciences 9 17%
Medicine and Dentistry 5 9%
Agricultural and Biological Sciences 2 4%
Psychology 2 4%
Other 4 8%
Unknown 14 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 May 2015.
All research outputs
#16,072,027
of 25,411,814 outputs
Outputs from Health economics (Online)
#2,149
of 2,667 outputs
Outputs of similar age
#148,725
of 279,518 outputs
Outputs of similar age from Health economics (Online)
#33
of 38 outputs
Altmetric has tracked 25,411,814 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,667 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.5. This one is in the 16th percentile – i.e., 16% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 279,518 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.