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      Measuring early childhood development in multiple contexts: the internal factor structure and reliability of the early Human Capability Index in seven low and middle income countries

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          Abstract

          Background

          The fourth year of the Sustainable Development Agenda era calls for countries to continue to invest not only in interventions and policies that will promote global equity and sustainability, but also in the monitoring systems required to track progress against these targets. A more pragmatic solution to measuring children’s early development in low and middle income countries in particular, is required. This study explores the psychometric properties of the early Human Capability Index (eHCI), a population measure of holistic development for children aged 3–5 years, designed with the vision of being flexible and feasible for use in low resource and capacity settings.

          Methods

          Utilizing data from seven low and middle income countries: Brazil ( n = 1810), China ( n = 11,421), Kiribati ( n = 8339), Lao People’s Democratic Republic ( n = 7493), Samoa ( n = 12,191), Tonga ( n = 6214), and Tuvalu ( n = 549), analyses explored the internal factor structure and reliability of scores produced by the tool within each country.

          Results

          Confirmatory factor analyses and internal consistency coefficients demonstrated that after local adaptation, translation, and different implementation methods across countries, the eHCI maintained the same factor structure of nine theoretically-based developmental domains: Physical Health, Verbal Communication, Cultural Knowledge, Social and Emotional Skills, Perseverance, Approaches to Learning, Numeracy, Reading, and Writing.

          Conclusions

          Findings support the aims of the eHCI in being adaptable and applicable for use within a range of low and middle income countries to facilitate measurement and monitoring of children’s early development, as is required for the tracking of progress towards the Sustainable Development Agenda.

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          Most cited references12

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          Estimating ordinal reliability for Likert-type and ordinal item response data: A conceptual, empirical, and practical guide

          This paper provides a conceptual, empirical, and practical guide for estimating ordinal reliability coefficients for ordinal item response data (also referred to as Likert, Likert-type, ordered categorical, or rating scale item responses). Conventionally, reliability coefficients, such as Cronbach’s alpha, are calculated using a Pearson correlation matrix. Ordinal reliability coefficients, such as ordinal alpha, use the polychoric correlation matrix (Zumbo, Gadermann, & Zeisser, 2007). This paper presents (i) the theoretical-psychometric rationale for using an ordinal version of coefficient alpha for ordinal data; (ii) a summary of findings from a simulation study indicating that ordinal alpha more accurately estimates reliability than Cronbach's alpha when data come from items with few response options and/or show skewness; (iii) an empirical example from real data; and (iv) the procedure for calculating polychoric correlation matrices and ordinal alpha in the freely available software program R. We use ordinal alpha as a case study, but also provide the syntax for alternative reliability coefficients (such as beta or omega). Accessed 35,197 times on https://pareonline.net from January 17, 2012 to December 31, 2019. For downloads from January 1, 2020 forward, please click on the PlumX Metrics link to the right.
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            Response Styles in Cross-national Survey Research: A 26-country Study

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                Author and article information

                Contributors
                alanna.sincovich@adelaide.edu.au
                tess.gregory@adelaide.edu.au
                crstn.zan@gmail.com
                ddsantos@fearp.usp.br
                john.lynch@adelaide.edu.au
                sally.brinkman@adelaide.edu.au
                Journal
                BMC Pediatr
                BMC Pediatr
                BMC Pediatrics
                BioMed Central (London )
                1471-2431
                3 December 2019
                3 December 2019
                2019
                : 19
                : 471
                Affiliations
                [1 ]ISNI 0000 0004 1936 7304, GRID grid.1010.0, School of Public Health, , University of Adelaide, ; Level 9, Adelaide Health and Medical Science Building, 57 North Terrace, Adelaide, South Australia 5005 Australia
                [2 ]Telethon Kids Institute, University of Western Australia, Level 15, 31 Flinders St, Adelaide, South Australia 5000 Australia
                [3 ]ISNI 0000 0001 2200 7498, GRID grid.8532.c, Department of Developmental Psychology and Personality, , Universidad Federal do Rio Grande do Sul, ; Av. Paulo Gama, 110, Bairro Farroupilha, Porto Alegre, Rio Grande do Sul 90040-060 Brazil
                [4 ]ISNI 0000 0004 1937 0722, GRID grid.11899.38, Department of Economy, , University of São Paulo, ; Av. Prof. Luciano Gualberto, 908, Butantã, São Paulo, 05508-010 Brazil
                [5 ]ISNI 0000 0004 1936 7603, GRID grid.5337.2, Population Health Sciences, Bristol Medical School, , University of Bristol, ; First Floor, 5 Tyndall Avenue, Bristol, BS8 1UD UK
                Article
                1852
                10.1186/s12887-019-1852-5
                6889461
                31795973
                e531fbe9-a4a7-4937-abaa-80e6706d6d04
                © The Author(s). 2019

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 30 September 2019
                : 22 November 2019
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Pediatrics
                child development,early human capability index,low and middle income countries,program evaluation,population monitoring

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