Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions. Johansson, F. D arXiv preprint arXiv:1811.05975, 2018.
Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions [link]Paper  abstract   bibtex   
We study heterogeneity in the effect of a mindset intervention on student-level performance through an observational dataset from the National Study of Learning Mindsets (NSLM). Our analysis uses machine learning (ML) to address the following associated problems: assessing treatment group overlap and covariate balance, imputing conditional average treatment effects, and interpreting imputed effects. By comparing several different model families we illustrate the flexibility of both off-the-shelf and purpose-built estimators. We find that the mindset intervention has a positive average effect of 0.26, 95%-CI [0.22, 0.30], and that heterogeneity in the range of [0.1, 0.4] is moderated by school-level achievement level, poverty concentration, urbanicity, and student prior expectations.
@article{johansson2018machine,
  title={Machine Learning Analysis of Heterogeneity in the Effect of Student Mindset Interventions},
  author={Johansson, Fredrik D},
  journal={arXiv preprint arXiv:1811.05975},
  year={2018},
  archivePrefix = "arXiv",
   eprint = {1811.05975},
 primaryClass = "stat.ML",
  url_Paper = {https://arxiv.org/pdf/1811.05975},
  abstract = {We study heterogeneity in the effect of a mindset intervention on student-level performance through an observational dataset from the National Study of Learning Mindsets (NSLM). Our analysis uses machine learning (ML) to address the following associated problems: assessing treatment group overlap and covariate balance, imputing conditional average treatment effects, and interpreting imputed effects. By comparing several different model families we illustrate the flexibility of both off-the-shelf and purpose-built estimators. We find that the mindset intervention has a positive average effect of 0.26, 95\%-CI [0.22, 0.30], and that heterogeneity in the range of [0.1, 0.4] is moderated by school-level achievement level, poverty concentration, urbanicity, and student prior expectations.}
}

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