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Statistical Analysis of the Regression Point Displacement Design (RPD)

Learn about the Statistical Requirements for N(n=1) in the RPD, including the analysis of covariance model, pre-post analysis, and regression model details for treatment variables. Understand how to interpret results and coefficients in an RPD example.

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Statistical Analysis of the Regression Point Displacement Design (RPD)

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  1. Statistical Analysis of the Regression Point Displacement Design(RPD)

  2. 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

  3. RPD Example 0 . 0 7 0 1 0 . 0 6 Y 0 . 0 5 0 . 0 4 0 . 0 3 0 . 0 3 0 . 0 4 0 . 0 5 0 . 0 6 0 . 0 7 0 . 0 8 X

  4. Regression Model for Analysis of Covariance yi = 0 + 1Xi + 2Zi + ei 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 where:

  5. 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%

  6. RPD Example 0 . 0 7 0 1 0 . 0 6 Y 0 . 0 5 2=-.019936 0 . 0 4 0 . 0 3 0 . 0 3 0 . 0 4 0 . 0 5 0 . 0 6 0 . 0 7 0 . 0 8 X

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