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Role of survey response rates on valid inference: an application to HIV prevalence estimates

Overview of attention for article published in Emerging Themes in Epidemiology, March 2018
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  • Above-average Attention Score compared to outputs of the same age (57th percentile)

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4 tweeters

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Title
Role of survey response rates on valid inference: an application to HIV prevalence estimates
Published in
Emerging Themes in Epidemiology, March 2018
DOI 10.1186/s12982-018-0074-x
Pubmed ID
Authors

Miguel Marino, Marcello Pagano

Abstract

Nationally-representative surveys suggest that females have a higher prevalence of HIV than males in most African countries. Unfortunately, these results are made on the basis of surveys with non-ignorable missing data. This study evaluates the impact that differential survey nonresponse rates between males and females can have on the point estimate of the HIV prevalence ratio of these two classifiers. We study 29 Demographic and Health Surveys (DHS) from 2001 to 2010. Instead of employing often used multiple imputation models with a Missing at Random assumption that may not hold in this setting, we assess the effect of ignoring the information contained in the missing HIV information for males and females through three proposed statistical measures. These measures can be used in settings where the interest is comparing the prevalence of a disease between two groups. The proposed measures do not utilize parametric models and can be implemented by researchers of any level. They are: (1) an upper bound on the potential bias of the usual practise of using reported HIV prevalence estimates that ignore subjects who have missing HIV outcomes. (2) Plausible range intervals to account for nonresponses, without any additional parametric modeling assumptions. (3) Prevalence ratio inflation factors to correct the point estimate of the HIV prevalence ratio, if estimates of nonresponders' HIV prevalences were known. In 86% of countries, males have higher upper bounds of HIV prevalence than females, this is consonant with males possibly having higher infection rates than females. Additionally, 74% of surveys have a plausible range that crosses 1.0, suggesting a plausible equivalence between male and female HIV prevalences. It is quite reasonable to conclude that there is so much DHS nonresponse in evaluating the HIV status question, that existing data is plausibly generated by the situation where the virus is equally distributed between the sexes.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 20%
Student > Master 3 20%
Student > Ph. D. Student 3 20%
Student > Bachelor 2 13%
Professor 1 7%
Other 0 0%
Unknown 3 20%
Readers by discipline Count As %
Medicine and Dentistry 3 20%
Social Sciences 2 13%
Mathematics 2 13%
Nursing and Health Professions 1 7%
Computer Science 1 7%
Other 3 20%
Unknown 3 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 03 April 2018.
All research outputs
#6,616,999
of 12,749,777 outputs
Outputs from Emerging Themes in Epidemiology
#61
of 103 outputs
Outputs of similar age
#112,473
of 271,908 outputs
Outputs of similar age from Emerging Themes in Epidemiology
#1
of 1 outputs
Altmetric has tracked 12,749,777 research outputs across all sources so far. This one is in the 47th percentile – i.e., 47% of other outputs scored the same or lower than it.
So far Altmetric has tracked 103 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.7. This one is in the 38th percentile – i.e., 38% 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 271,908 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 57% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them