In the above stated equation, the yi is the concluded value at the ith unit; b0 is the coefficient for the intercept where as B1 is the coefficient value for the pretest, B2 comprises of the difference between the mean for the treatment group, and Xi is the value of covariate, Zi involves the dummy variable with their treatment of 0 and 1 and e is the residual value or it might be the possibilities of error in the model. The main characteristic for the examination of the model is to know the approximate size of the vertical displacement of the values of the treatment group from the line of regression as taking in view all the units of the control group.
[large]The regression point displacement analysis is some how very beneficial in examination of the large consistent groups which may include the companies or any communities. But in such cases it I compulsory to have the important measures from the group that is comparable means that form the control group to have the better sought of comparison. The graphs are drawn to analyze the before and after effects because these measures shows a very helpful change in determining the every aspect of comparison. Other than this the general principle can also be used for the comparison that includes the comparing values against the critical masses. In the regression point displacement analysis, the single measure evaluations can express the large number of sample with all its importance. The point may be aroused that results obtained from the single person are not valid but unforeseen the results are considered to be more significant.
The actual purpose of the regression point displacement analysis is to compare the pre post concluded values for single or may be for multiple treatment groups in order to control the population size. This analysis provides an easy factor for the implementation of the community based results with comparatively very low costs.
References
• Linden, A. and Adams, J. “Evaluation and the health profession”. Evaluating Program Effectiveness Using the Regression Point Displacement Design.
• Hsiao, V. (1994), Use of the regression point displacement design to evaluate interventions made on the basis of small area analysis. Pp 338: Cornel University.