dscore

The D-score is a numerical score that measures generic development in children. You may use the D-score to analyze and predict development of children similar to measures like height and weight.

The dscore package contains tools to

• Map your item names to the GSED convention
• Calculate D-score from item level responses
• Transform the D-scores into DAZ, age-standardised Z-scores

The required input consists of item level responses on milestones from widely used instruments for measuring child development.

Installation

You can install the development version from GitHub with:

install.packages("remotes")
remotes::install_github("d-score/dscore")

Overview

You may estimate the D-score and the D-score age-adjusted Z-score (DAZ) from child data on developmental milestones. Four steps are needed:

1. Identify whether the dscore package covers your measurement instrument;
2. Map your variable names to the GSED 9-position schema;
3. Calculate D-score and DAZ;
4. Summarise your results.

The dscore package provides various function that support these steps. See Getting started for more details.

Resources

Books and reports

1. D-score: Turning milestones into measurement
2. Inventory of 147 instruments for measuring early child development: Fernald et al. (2017)

Keys

1. Project with dutch key, 0-2 years: van Buuren (2014)
2. Project with gcdg key: Weber et al. (2019)
3. Project with gsed key: GSED team (Maureen Black, Kieran Bromley, Vanessa Cavallera (lead author), Jorge Cuartas, Tarun Dua (corresponding author), Iris Eekhout, Günther Fink, Melissa Gladstone, Katelyn Hepworth, Magdalena Janus, Patricia Kariger, Gillian Lancaster, Dana McCoy, Gareth McCray, Abbie Raikes, Marta Rubio-Codina, Stef van Buuren, Marcus Waldman, Susan Walker and Ann Weber) (2019)

Methodology

1. Interval scale: Jacobusse, van Buuren, and Verkerk (2006)
2. Adaptive testing: Jacobusse and van Buuren (2007)

Shiny app

If you want to calculate the D-score on your own data, and you’re not an R user, you might wish to check out our interactive Shiny dcalculator app.

Acknowledgement

This study was supported by the Bill & Melinda Gates Foundation. The contents are the sole responsibility of the authors and may not necessarily represent the official views of the Bill & Melinda Gates Foundation or other agencies that may have supported the primary data studies used in the present study. The authors wish to recognize the principal investigators and their study team members for their generous contribution of the data that made this tool possible and the members of the Ki team who directly or indirectly contributed to the study: Amina Abubakar, Claudia R. Lindgren Alves, Orazio Attanasio, Maureen M. Black, Maria Caridad Araujo, Susan M. Chang-Lopez, Gary L. Darmstadt, Bernice M. Doove, Wafaie Fawzi, Lia C.H. Fernald, Günther Fink, Emanuela Galasso, Melissa Gladstone, Sally M. Grantham-McGregor, Cristina Gutierrez de Pineres, Pamela Jervis, Jena Derakhshani Hamadani, Charlotte Hanlon, Simone M. Karam, Gillian Lancaster, Betzy Lozoff, Gareth McCray, Jeffrey R Measelle, Girmay Medhin, Ana M. B. Menezes, Lauren Pisani, Helen Pitchik, Muneera Rasheed, Lisy Ratsifandrihamanana, Sarah Reynolds, Linda Richter, Marta Rubio-Codina, Norbert Schady, Limbika Sengani, Chris Sudfeld, Marcus Waldman, Susan P. Walker, Ann M. Weber and Aisha K. Yousafzai.

Literature