The Rothstein falsification test generates large and implausible future teacher effects even when students are randomly assigned to classrooms¶

Claim · All claims
Evidence · 1 study · theoretical r3 · q2
Currency · newest study 2015 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? The Rothstein falsification test yields large and implausible future teacher effects even under random assignment of students to classrooms, so such effects are not by themselves evidence of bias in value-added models. → Dan Goldhaber 2015

Evidence¶

Dan Goldhaber 2015¶

Dan Goldhaber, Duncan Dunbar Chaplin. (2015). Assessing the "Rothstein Falsification Test": Does It Really Show Teacher Value-Added Models Are Biased? Journal of Research on Educational Effectiveness, vol. 8, issue 1. https://www.mathematica.org/publications/assessingthe-rothstein-falsification-test-does-it-really-show-teacher-valueadded-models-are-biased doi:10.1080/19345747.2014.978059

q2 · i? · theoretical · r3

The authors' summary of their re-analysis of the Rothstein falsification test, reporting that the test "generates large and implausible future teacher effects even when students are randomly assigned to classrooms." No effect size or test statistic is printed on the page.

"We find that the “Rothstein falsification test” generates large and implausible future teacher effects even when students are randomly assigned to classrooms."

Discussion¶

Related Claims¶

• Theoretically and in simulations, the Rothstein test often falsifies unbiased VAMs and fails to falsify biased VAMs — a broader claim this one bears on
• Detecting that students are tracked to teachers does not necessarily imply bias in teacher effectiveness estimates — related
• Tracking based on lagged student achievement is usually accounted for in value-added models, which is why the falsification test can mislead — related
• Rothstein (2010) found that standard VAMs imply implausible future-teacher effects on past student achievement — related
• The Rothstein falsification test is not definitive in showing bias in VAM teacher effect estimates — a broader claim this one bears on
• The Rothstein test can reject VAMs even when students are randomly assigned conditional on the covariates in the model — related
• The Rothstein falsification test can reject value-added models even when estimated teacher effects are unbiased — a broader claim this one bears on