Parenting and Child Development in Low- and Middle-Income Countries
Predictors of early childhood development: A machine learning approach
Publication
, Chapter
Bizzego, A; Gabrieli, G; Lim, M; Rothenberg, WA; Bornstein, MH; Esposito, G
September 9, 2022
Duke Scholars
DOI
ISBN
9780367491765
Publication Date
September 9, 2022
Start / End Page
210 / 239
Citation
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Bizzego, A., Gabrieli, G., Lim, M., Rothenberg, W. A., Bornstein, M. H., & Esposito, G. (2022). Predictors of early childhood development: A machine learning approach. In Parenting and Child Development in Low- and Middle-Income Countries (pp. 210–239). https://doi.org/10.4324/9781003044925-6
Bizzego, A., G. Gabrieli, M. Lim, W. A. Rothenberg, M. H. Bornstein, and G. Esposito. “Predictors of early childhood development: A machine learning approach.” In Parenting and Child Development in Low- and Middle-Income Countries, 210–39, 2022. https://doi.org/10.4324/9781003044925-6.
Bizzego A, Gabrieli G, Lim M, Rothenberg WA, Bornstein MH, Esposito G. Predictors of early childhood development: A machine learning approach. In: Parenting and Child Development in Low- and Middle-Income Countries. 2022. p. 210–39.
Bizzego, A., et al. “Predictors of early childhood development: A machine learning approach.” Parenting and Child Development in Low- and Middle-Income Countries, 2022, pp. 210–39. Scopus, doi:10.4324/9781003044925-6.
Bizzego A, Gabrieli G, Lim M, Rothenberg WA, Bornstein MH, Esposito G. Predictors of early childhood development: A machine learning approach. Parenting and Child Development in Low- and Middle-Income Countries. 2022. p. 210–239.
DOI
ISBN
9780367491765
Publication Date
September 9, 2022
Start / End Page
210 / 239