• D-score Chapter I
  • Preface
  • 1 Introduction
    • 1.1 First 1000 days
    • 1.2 Relevance of child development
    • 1.3 Stunting as proxy for child development
    • 1.4 Measuring neurocognitive development
    • 1.5 Why this chapter?
    • 1.6 Intended audience
  • 2 Short history
    • 2.1 What is child development?
    • 2.2 Theories of child development
      • 2.2.1 Continuous or discontinuous?
      • 2.2.2 One course or multiple parallel tracks?
      • 2.2.3 Nature or nurture?
    • 2.3 Example of motor development
      • 2.3.1 Shirley’s motor data
      • 2.3.2 Individual trajectories of motor development
    • 2.4 Typical questions asked in child development
  • 3 Quantifying child development
    • 3.1 Age-based measurement of development
      • 3.1.1 Motivation for age-based measurement
      • 3.1.2 Age equivalent and developmental age
      • 3.1.3 Limitations of age-based measurement
    • 3.2 Probability-based measurement
      • 3.2.1 Example of probability-based measurement
      • 3.2.2 Limitations of probability-based measurement
    • 3.3 Score-based measurement of development
      • 3.3.1 Motivation for score-based measurement
      • 3.3.2 Example of score-based measurement
      • 3.3.3 Limitations of score-based measurement
    • 3.4 Unit-based measurement of development
      • 3.4.1 Motivation for unit-based measurement
      • 3.4.2 Example of unit-based measurement
      • 3.4.3 Limitations of unit-based measurement
    • 3.5 A unified framework
    • 3.6 Why unit-based measurement
  • 4 The D-score
    • 4.1 The Dutch Development Instrument (DDI)
      • 4.1.1 Setting
      • 4.1.2 Description of SMOCC study
      • 4.1.3 Codebook of DDI 0-30 months
    • 4.2 Probability of passing a milestone given age
    • 4.3 Probability of passing a milestone given D-score
    • 4.4 Relation between age and the D-score
    • 4.5 Measurement model for the D-score
      • 4.5.1 What are measurement models?
      • 4.5.2 Adapt the model? Or adapt the data?
    • 4.6 Item response functions
      • 4.6.1 Logistic model
      • 4.6.2 Types of item response functions
      • 4.6.3 Person response functions
    • 4.7 Engelhard criteria for invariant measurement
    • 4.8 Why take the Rasch model?
  • 5 Computation
    • 5.1 Identify nature of the problem
    • 5.2 Item parameter estimation
      • 5.2.1 Pairwise estimation of item difficulties
      • 5.2.2 Anchoring
    • 5.3 Estimation of the D-score
      • 5.3.1 Role of the starting prior
      • 5.3.2 Starting prior: Numerical example
      • 5.3.3 EAP algorithm
      • 5.3.4 EAP algorithm: Numerical example
      • 5.3.5 Technical observations on D-score estimation
    • 5.4 Age-conditional references
      • 5.4.1 Motivation
      • 5.4.2 Estimation of the reference distribution
      • 5.4.3 Conversion of \(D\) to DAZ, and vice versa
  • 6 Evaluation
    • 6.1 Item fit
      • 6.1.1 Well-fitting item response curves
      • 6.1.2 Item response curves showing severe underfit
      • 6.1.3 Item response curves showing overfit
      • 6.1.4 Item infit and outfit
      • 6.1.5 Infit and outfit in the DDI
    • 6.2 Person fit
      • 6.2.1 Person infit and outfit
      • 6.2.2 Person infit and outfit in the DDI
    • 6.3 Differential item functioning (DIF)
      • 6.3.1 Relevance of DIF for cross-cultural equivalence
      • 6.3.2 How to detect DIF?
      • 6.3.3 Examples of DIF
    • 6.4 Item information
      • 6.4.1 Item information at a given ability
      • 6.4.2 Item information at a given age
    • 6.5 Reliability
  • 7 Validity
    • 7.1 Internal validity
      • 7.1.1 Content validity
      • 7.1.2 Construct validity
    • 7.2 External validity
      • 7.2.1 Discriminatory validity
      • 7.2.2 Convergent and divergent validity
      • 7.2.3 Predictive validity
  • 8 Precision
    • 8.1 SMOCC design: Standard and additional milestones
    • 8.2 D-score from short tests
      • 8.2.1 Milestone sets
      • 8.2.2 Milestone sets at month 2
      • 8.2.3 Milestone sets at month 3
      • 8.2.4 Floor and ceiling effects
    • 8.3 Impact of short tests on predicting IQ
      • 8.3.1 Measurement and prediction
      • 8.3.2 UKKI
      • 8.3.3 Exploratory analysis
  • 9 Three studies
    • 9.1 SMOCC study
    • 9.2 POPS study
      • 9.2.1 POPS design
      • 9.2.2 Age-adjustment
      • 9.2.3 Effect of age-adjustment on the D-score
      • 9.2.4 Effect of no age adjustment (\(f = 0.00\)) on the DAZ
      • 9.2.5 Effect of full age adjustment (\(f = 1.00\)) on the DAZ
      • 9.2.6 Partial age adjustment
      • 9.2.7 Conclusions
    • 9.3 TOGO study
      • 9.3.1 Togo Kpalimé study, design
      • 9.3.2 D-score labelled by neurological problem
      • 9.3.3 D-score labelled by Apgar score
      • 9.3.4 D-score labelled by severe underweight
      • 9.3.5 D-score labelled by severe stunting
      • 9.3.6 Gross motor development
      • 9.3.7 Fine motor development
      • 9.3.8 Communication and language
    • 9.4 Conclusions
  • 10 Next steps
    • 10.1 Usefulness of D-score for monitoring child health
    • 10.2 D-chart, a growth chart for child development
    • 10.3 Opportunities for early intervention
    • 10.4 D-score for international settings
    • 10.5 D-score from existing instruments
    • 10.6 Creating new instruments for D-score
  • Appendices
  • A - Notation
  • B - Project information
    • Data availability
    • Grant information
    • Competing interests
  • C - Technical information
  • References

Child Development with the D-score

Child Development with the D-score

Turning Milestones into Measurement

Authors: Stef van Buuren & Iris Eekhout