Jamali-Phiri, Monica, Kafumba, Juba, MacLachlan, Malcolm, Smith, Emma, Ebuenyi, Ikenna, Eide, Arne H. and Munthali, Alister (2020) Addressing data deficiencies in assistive technology by using statistical matching methodology: a case study from Malawi. Disability and Rehabilitation: Assistive Technology. ISSN 1748-3107
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Abstract
Purpose: To address the data gap on efforts to assess use of assistive technology among children with
disability in sub-Saharan Africa. Contribute towards efforts examining access to assistive technologies in
sub-Saharan Africa.
Materials and methods: The paper uses data from the 2017 survey on Living conditions among persons
with disabilities in Malawi and the 2015-16 Malawi Demographic and Health survey to address the objective
of the study. The two datasets were statistically matched through random hot deck technique, by
integrating the two datasets using randomly selected units from a subset of all available data donors.
Results: Results indicate that statistical matching technique produces a composite dataset with an uncertainty
value of 2.2%. An accuracy assessment test of the technique also indicates that the marginal distribution
of use of assistive technology in the composite dataset is similar to that of the donor dataset with
an Overlap index value of close to 1 (Overlap ¼ 0.997).
Conclusions: The statistical matching procedure does enable generation of good data in data constrained
contexts. In the current study, this approach enabled measurement of access to assistive products among
children with disabilities, in situations where the variables of interest have not been jointly observed.
Such a technique can be valuable in mining secondary data, the collection of which may have been
funded from different sources and for different purposes. This is of significance for the efficient use of
current and future data sets, allowing new questions to be asked and addressed by locally based
researchers in poor settings.
Item Type: | Article |
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Keywords: | Assistive technology; children with disabilities; statistical matching; sub- Saharan Africa; distinct data-sources; |
Academic Unit: | Assisting Living & Learning,ALL institute Faculty of Science and Engineering > Psychology |
Item ID: | 16369 |
Identification Number: | 10.1080/17483107.2020.1861118 |
Depositing User: | Malcolm MacLachlan |
Date Deposited: | 28 Jul 2022 09:02 |
Journal or Publication Title: | Disability and Rehabilitation: Assistive Technology |
Publisher: | Taylor & Francis |
Refereed: | Yes |
Related URLs: | |
URI: | https://mu.eprints-hosting.org/id/eprint/16369 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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