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      Longitudinal child data: What can be gained by linking administrative data and cohort data?

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          Abstract

          Introduction

          Linked administrative data sets are an emerging tool for studying the health and well-being of the population. Previous papers have described methods for linking Canadian data, although few have specifically focused on children, nor have they described linkage between tax outcomes and a cohort of children who are particularly at risk for poor financial outcomes.

          Objective and methods

          This paper describes a probabilistic linkage performed by Statistics Canada linking the Montreal Longitudinal Experimental Study (MLES) and the Quebec Longitudinal Study of Kindergarten Children (QLSKC) survey cohorts and administrative tax data from 1992 through 2012.

          Results

          The number of valid cases in the original cohort file with valid tax records was approximately 84%. Rates of false positives, false negatives, sensitivity, and specificity of the linkage were all acceptable. Using the linked file, the relationship of childhood behavioural indicators and adult income can be investigated in future studies.

          Conclusions

          Innovative methods for creating longitudinal datasets on children will assist in examining long-term outcomes associated with early childhood risk and protective factors as well as an evidence base for interventions that promote child well-being and positive outcomes.

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          Most cited references18

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          Income Inequality, Equality of Opportunity, and Intergenerational Mobility

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            A Theory for Record Linkage

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              Kindergarten Disruptive Behaviors, Protective Factors, and Educational Achievement by Early Adulthood.

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                Author and article information

                Journal
                Int J Popul Data Sci
                Int J Popul Data Sci
                IJPDS
                International Journal of Population Data Science
                Swansea University
                2399-4908
                14 November 2018
                2018
                : 3
                : 1
                : 451
                Affiliations
                [1 ] Statistics Canada 150 Tunney's Pasture Driveway Ottawa, Ontario K1A 0T6
                [2 ] CEPREMAP 48 boulevard Jourdan 75014 Paris FRANCE
                [3 ] Sciences Po, 27, rue Saint Guillaume - 75337 Paris
                [4 ] Groupe de recherche sur l'inadaptation psychosociale chez l'enfant (GRIP) Axe sur les maladies du cerveau Université de Montréal 3050 boul. Édouard-Montpetit, local B-234 Montréal, QC H3T 1J7
                Author notes
                [*] [* ] Corresponding author: L Findlay. leanne.findlay@ 123456canada.ca

                Statement on conflicts of interest: The Authors declare they have no conflicts of interest.

                Article
                3:0:21 S2399490818004512
                10.23889/ijpds.v3i1.451
                7299460
                aedf376b-3c0b-4c64-90cd-3fd9b3d1a794

                This work is licensed under a Creative Commons Attribution 4.0 International License.

                History
                Categories
                Population Data Science

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