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Reichardt, Charles; Gollob, Harry – New Directions for Program Evaluation, 1986
Causal models often omit variables that should be included, use variables that are measured fallibly, and ignore time lags. Such practices can lead to severely biased estimates of effects. The discussion explains these biases and shows how to take them into account. (Author)
Descriptors: Effect Size, Error of Measurement, High Schools, Mathematical Models