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Does measurement invariance hold for the official Mexican multidimensional poverty measure? A state-level analysis 2012

Overview of attention for article published in Quality & Quantity, March 2016
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Title
Does measurement invariance hold for the official Mexican multidimensional poverty measure? A state-level analysis 2012
Published in
Quality & Quantity, March 2016
DOI 10.1007/s11135-016-0327-0
Pubmed ID
Authors

Hector Ernesto Najera

Abstract

One of the main goals in poverty measurement is making comparisons of prevalence and severity across geographical units. This is attained by merely disaggregating the index in question. The underlying assumption is that comparisons across units are tenable, inasmuch as the same indicators are utilised for constructing the index. Nonetheless, in practice, this assumption is very rarely tested. From the statistical perspective, measurement invariance (MI) must hold for comparisons to be valid, and violations thereof indicate that a given poverty index measures different things across different countries, states, counties, etc. Consequently, differentials in severity and prevalence cannot be attributed exclusively to the underlying construct (i.e. poverty) but to factors not considered in the measure. This article tests whether MI holds for two indexes: the Mexican official multidimensional measure (MPM) and an adjusted multidimensional measure (MPM-A) that uses less severe thresholds. The analysis is conducted using a novel method called the 'alignment method'. It uses these two measures and the method as an illustration of why it is vital to introduce MI tests into poverty measurement. The results suggest that partial strong MI holds for the official measure and MI is violated when the thresholds are adjusted. Partial strong MI guarantees making valid comparisons across the 32 states. Should the official measure requires to be updated with other thresholds, it would be necessary to adjust the threshold or drop the indicator for water deprivation.

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The data shown below were collected from the profiles of 3 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 26%
Student > Ph. D. Student 5 22%
Student > Doctoral Student 3 13%
Student > Bachelor 2 9%
Unspecified 2 9%
Other 2 9%
Unknown 3 13%
Readers by discipline Count As %
Economics, Econometrics and Finance 6 26%
Psychology 3 13%
Social Sciences 3 13%
Engineering 2 9%
Unspecified 2 9%
Other 4 17%
Unknown 3 13%
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 16 May 2017.
All research outputs
#14,345,967
of 22,971,207 outputs
Outputs from Quality & Quantity
#332
of 610 outputs
Outputs of similar age
#173,913
of 327,224 outputs
Outputs of similar age from Quality & Quantity
#3
of 7 outputs
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So far Altmetric has tracked 610 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 42nd percentile – i.e., 42% of its peers scored the same or lower than it.
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