Student Sorting and Bias in Value-Added Estimation: Selection on Observables and Unobservables

By Jesse M. Rothstein. Education Finance and Policy, 2009

403 citations recorded by the source corpus.

Subfields: Education, Information Systems and Management

View Paper: https://www.semanticscholar.org/paper/76895cd5ce0c629d06d957e9f818fa457515e2ed

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Citations in the corpus

The Legal Consequences of Mandating High Stakes Decisions Based on Low Quality Information: Teacher Evaluation in the Race-to-the-Top Era (2013, positive): “" (p. 8) Numerous authors have conducted analyses revealing the problems of omitted variables bias and the non-random sorting of students across classrooms (Ballou, Mokher, & Cavaluzzo, 2012, Briggs & Domingue, 2011; Rothstein, 2009, 2010, 2011).”
Assessing Rothstein's critique of teacher value‐added models (2012, methodology): “The top panel is taken directly from Table 5 in Rothstein (2010). The bottom panel is results produced by the author.”
Examining Teacher Effectiveness Using Classroom Observation Scores (2015, background): “Keywords: education policy, teacher effectiveness, teacher evaluation, Framework for Teaching (FFT) Examining Teacher Effectiveness Using Classroom Observation Scores to teachers (Rothstein, 2009).”
Connections Between Teachers’ Knowledge of Students, Instruction, and Achievement Outcomes (2018, methodology): “We argue that using this heavily controlled model helps address the observational nature of our analyses (see, for example, Rothstein, 2009).”
Teacher quality policy when supply matters (2012, background): “In Staiger and Rockoff’s (2010) simulation of teacher tenure policies, for example, the district can draw without limit from the current applicant pool to replace poor performers who are fired, without raising salaries.”
Classroom Composition and Measured Teacher Performance (2016, background): “…randomly assigned to classes of students.1 In principle, the random assignment of teachers to classes disrupts the assortative matching process that can confound measures of teacher effectiveness (Clotfelter et al., 2006; Garrett & Steinberg, 2015; Rothstein, 2009, 2010; Whitehurst et al., 2014).”
Teacher Quality in Educational Production. Tracking, Decay, and Student Achievement. NBER Working Paper No. 14442. (2008, positive): “30 While several 30 Although a full discussion is beyond the scope of this paper, assumptions about " decay " are closely related to issues of test scaling and content coverage (Rothstein, 2008; Ballou, 2008; Martineau, 2006).”
Where Should Student Teachers Learn to Teach? (2012, background): “Among them, researchers have expressed concern over year-to-year variation in scores (McCaffrey, Sass, Lockwood, & Mihaly, 2009) and bias due to nonrandom assignment of students to teachers (Rothstein, 2009).”
What's in a teacher test? Assessing the relationship between teacher licensure test scores and student STEM achievement and course-taking (2016, positive): “As discussed in Section 4 c, we also perform several robustness hecks of the achievement results designed to investigate whether he estimates described above may be biased by the non-random ssignment of students to teachers ( Rothstein, 2009, 2010 ).”
How Teacher Evaluation Methods Matter for Accountability (2014, background): “Second, some early work in value-added included the student fixed effects shown in Equation 1, but more recently there has been concern about the level of measurement error and potential biases in this model (Kane & Staiger, 2008; Rothstein, 2009).”