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In regression analysis, partial leverage (PL) is a measure of the contribution of the individual independent variables to the total leverage of each observation. That is, if h i is the i th element of the diagonal of the hat matrix, PL is a measure of how h i changes as a variable is added to the regression model.
Partial leverage (PL) is a measure of the contribution of the individual independent variables to the total leverage of each observation. That is, PL is a measure of how h i i {\displaystyle h_{ii}} changes as a variable is added to the regression model.
Partial regression plots are most commonly used to identify data points with high leverage and influential data points that might not have high leverage. Partial residual plots are most commonly used to identify the nature of the relationship between Y and X i (given the effect of the other independent variables in the model).
In applied statistics, a partial residual plot is a graphical technique that attempts to show the relationship between a given independent variable and the response variable given that other independent variables are also in the model.
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Thus, for low leverage points, DFFITS is expected to be small, whereas as the leverage goes to 1 the distribution of the DFFITS value widens infinitely. For a perfectly balanced experimental design (such as a factorial design or balanced partial factorial design), the leverage for each point is p/n, the number of parameters divided by the ...