The purpose of this study was to examine the potential for using propensity score-based matching methods to estimate teacher contributions to student learning. Value-added models are increasingly used in teacher accountability systems in the United States in spite of ongoing qualms about the validity of teacher quality estimates resulting from those models. Using a large national dataset, teacher effects were estimated for 435 teachers using both value-added and propensity score-based approaches. The two approaches resulted in teacher effect estimates that were moderately correlated, with propensity score-based estimates more highly correlating with the value-added estimates as the matching ratio was increased. For many teachers' students, finding a set of matched control students was impossible unless the set of matching variables was reduced. Results suggest that many teachers have classroom compositions that are unusual, making evaluation of the teachers' impacts on student outcomes problematic. It was also found that, while value-added estimates were relatively insensitive to covariate inclusion choices or method of effect estimation, propensity score-based estimates were somewhat sensitive. Propensity score-based teacher effect estimates offer promise both for better accounting for classroom composition and student background variables and for indicating when a teacher's context is unique with respect to those variables, making the teacher's impact challenging to evaluate. [The dissertation citations contained here are published with the permission of ProQuest LLC. Further reproduction is prohibited without permission. Copies of dissertations may be obtained by Telephone (800) 1-800-521-0600. Web page: http://www.proquest.com/en-US/products/dissertations/individuals.shtml.]