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Maximum Likelihood Analysis for a Generalized Regession-Discontinuity Design

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  • Ronald A. Visser
  • Jan De Leeuw

Abstract

The regression-discontinuity design (RDD) offers the possibility of making inferences about causal effects from observations on selected groups. The quasi-experimental groups are formed by dividing the scores of a premeasurement in two halves. The treatment effect is inferred from the differences between the regression of a postmeasurement on the premeasurement for the two groups. We discuss a generalized form of this design: (a) Apart from parallel shift of the regression lines, differences in variance and covariance are considered; (b) pretest and posttest may be multivariate; and (c) more than two groups may be involved in the design. Data from such a design are considered to have a truncated bivariate distribution. For the RDD, maximum likelihood parameter estimation procedures and tests of hypotheses are presented.

Suggested Citation

  • Ronald A. Visser & Jan De Leeuw, 1984. "Maximum Likelihood Analysis for a Generalized Regession-Discontinuity Design," Journal of Educational and Behavioral Statistics, , vol. 9(1), pages 45-60, March.
    • Handle: RePEc:sae:jedbes:v:9:y:1984:i:1:p:45-60
    DOI: 10.3102/10769986009001045
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