Addressing data deficiencies in assistive technology by using statistical matching methodology: a case study from Malawi

References

• Borg J, Lindström A, Larsson S. Assistive technology in developing countries: national and international responsibilities to implement the Convention on the Rights of Persons with Disabilities. Lancet. 2009;374:1863–1865.
   PubMed Web of Science ®Google Scholar
• World Health Organization. Assistive technology for children with disabilities: creating opportunities for education, inclusion and participation. A discussion paper. 2015.
   Google Scholar
• Donatiello G, et al. Statistical matching of income and consumption expenditures. Int J Econ Sci. 2014;3:50.
   Google Scholar
• Moriarity C, Scheuren F. Statistical matching: a paradigm for assessing the uncertainty in the procedure. J Off Stat. 2001;17:407.
   Google Scholar
• Khasnabis C, Mirza Z, MacLachlan M. Opening the GATE to inclusion for people with disabilities. Lancet. 2015;386:2229–2230.
   PubMed Web of Science ®Google Scholar
• Mji G, Edusei A. An introduction to a special issue on the role of assistive technology in social inclusion of persons with disabilities in Africa: Outcome of the fifth African Network for Evidence-to-Action in Disability conference. Afr J Disabil. 2019;8:681.
   PubMed Web of Science ®Google Scholar
• Osam JA, et al. The use of assistive technologies among children with disabilities: the perception of parents of children with disabilities in Ghana. Disabil Rehabil Assist Technol. 2019.
   PubMed Web of Science ®Google Scholar
• D'Orazio M, Zio MD, Scanu M. Statistical matching: theory and practice. Hoboken (NJ): John Wiley & Sons; 2006.
   Google Scholar
• D’Orazio M. Statistical matching and imputation of survey data with StatMatch. 2016.
   Google Scholar
• Rubin DB. Statistical matching using file concatenation with adjusted weights and multiple imputations. J Bus Econ Stat. 1986;4:87–94.
   Web of Science ®Google Scholar
• Simonson J, Gordo LR, Kelle N. Statistical matching of the German aging survey and the sample of active pension accounts as a source for analyzing life courses and old age incomes. Hist Soc Res. 2012;37:185–210.
   Web of Science ®Google Scholar
• Marcello D, Zio MD, Scanu M. Statistical matching for categorical data: displaying uncertainty and using logical constraints. J Off Stat. 2006;22:137.
   Google Scholar
• Zhang L-C. On proxy variables and categorical data fusion. J Off Stat. 2015;31:783–807.
   Web of Science ®Google Scholar
• Leulescu A, Agafitei M. Statistical matching: a model based approach for data integration. Eurostat-Methodologies and Working papers. 2013.
   Google Scholar
• D’Orazio M. Statistical matching and imputation of survey data with the Package StatMatch for the R Environment. R package vignette. 2011. http://www.cros-portal.eu/sites/default/files//Statistical_Matching_with_StatMatch.pdf
   Google Scholar
• Ebuenyi ID, Smith EM, Kafumba J, et al. Implementation of the Assistive Product List (APL) in Malawi through development of appropriate policy and systems: an action research protocol. BMJ Open. 2020;10:e040281
   PubMed Web of Science ®Google Scholar
• Eide AH, Munthali A. Living conditions among persons with disabilities in Malawi. A national, representative survey. 2017.
   Google Scholar
• WHO. Towards a common language for functioning, disability, and health: ICF. The international classification of functioning, disability and health, 2002.
   Google Scholar
• Nsonm I. Malawi demographic and health survey 2015–16. Zomba (Malawi): National Statistical Office; Rockville (MD): ICF; 2017.
   Google Scholar
• World Health Organization. World report on disability 2011. Geneva (Switzerland): World Health Organization; 2011.
   Google Scholar
• World Health Organization. Joint position paper on the provision of mobility devices in less-resourced settings: a step towards implementation of the Convention on the Rights of Persons with Disabilities (CRPD) related to personal mobility. Geneva (Switzerland): World Health Organization; 2011.
   Google Scholar
• Allen S, Resnik L, Roy J. Promoting independence for wheelchair users: the role of home accommodations. Gerontologist. 2006;46:115–123.
   PubMed Web of Science ®Google Scholar
• Weber R, Weber D. Statistical matching of EU-SILC and the Household Budget Survey to compare poverty estimates using income, expenditures and material deprivation. Eurostat Working Papers and Methodologies. 2013.
   Google Scholar
• Agresti A. An introduction to categorical data analysis. 3rd ed. New York (NY): Wiley; 2007.
   Google Scholar
• Field A. Discovering statistics using IBM SPSS statistics. London (UK): Sage; 2013.
   Google Scholar
• Reynolds HT. Analysis of nominal data. Vol. 7. 1984. Newburypark (CA): Sage.
   Google Scholar
• D’Orazio M, Zio MD, Scanu M. Old and new approaches in statistical matching when samples are drawn with complex survey designs. Proceedings of the 45th “Riunione Scientifica della Societa’Italiana di Statistica”; Padova, Italy. 2010. p. 16–18.
   Google Scholar
• D’Orazio M, M. Di Z, Scanu M. Statistical matching of data from complex sample surveys. Proceedings of the European Conference on Quality in Official Statistics-Q2012. 2012.
   Google Scholar
• DOrazio M. Statistical matching: metodological issues and practice with R-StatMtach. Proceedings of the EUSTAT 55th International Statistical Seminar; 2013 Nov 21–22; Vitoria-Gasteiz, Spain. 2013.
   Google Scholar
• Office NS. 2018. Malawi population and housing census. Preliminary report. 2018. Zomba (Malawi): National Statistical Office.
   Google Scholar
• Jylhä M. What is self-rated health and why does it predict mortality? Towards a unified conceptual model. Soc Sci Med. 2009;69:307–316.
   PubMed Web of Science ®Google Scholar
• Jylhä M, et al. Walking difficulty, walking speed, and age as predictors of self-rated health: the women’s health and aging study. J Gerontol A Biol Sci Med Sci. 2001;56:M609–M617.
   PubMed Web of Science ®Google Scholar
• Mwaijande VT. Access to education and assistive devices for children with physical disabilities in Tanzania. Oslo and Akershus University College; 2014.
   Google Scholar
• MacLachlan M, Banes D, Bell D, et al. Assistive technology policy: a position paper from the first global research, innovation, and education on assistive technology (GREAT) summit. Disabil Rehabil Assist Technol. 2018;13:454–466.
   PubMed Web of Science ®Google Scholar
• Tebbutt E, Brodmann R, Borg J, et al. Assistive products and the sustainable development goals (SDGs). Global Health. 2016;12:79.
   PubMed Web of Science ®Google Scholar
• Serrat O. Political economy analysis for development effectiveness. In: Serrat O, editor. Knowledge solutions. Singapore: Springer; 2017. p. 207–222.
   Google Scholar