Statistical Analysis of the Regression Point Displacement Design (RPD)

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Presentation transcript:

Statistical Analysis of the Regression Point Displacement Design (RPD)

Statistical Requirements N(n=1) O X O N O O Pre-post Two groups, but one group has n=1 Dummy-code treatment variable Analysis of Covariance model

RPD Example . 7 1 . 6 Y . 5 . 4 . 3 . 3 . 4 . 5 . 6 . 7 . 8 X

Regression Model for Analysis of Covariance yi = 0 + 1Xi + 2Zi + ei where: yi = outcome score for the ith unit 0 = coefficient for the intercept 1 = pretest coefficient 2 = mean difference for treatment Xi = covariate Zi = dummy variable for treatment (0 = control, 1= treatment[n=1]) ei = residual for the ith unit

RPD Example The regression equation is Y = 0.0120 + 0.784 X - 0.0199 Z Predictor Coef Stdev t-ratio p Constant 0.011956 0.004965 2.41 0.023 X 0.78365 0.09864 7.94 0.000 Z -0.019936 0.005800 -3.44 0.002 s = 0.005689 R-sq = 72.6% R-sq(adj) = 70.6%

RPD Example . 7 1 . 6 Y . 5 2=-.019936 . 4 . 3 . 3 . 4 . 5 . 6 . 7 . 8 X