Statistical Estimation of Healthy Life Expectancy - Research Paper Example

Model selection was performed using the software Statistical Package for the Social Sciences (SPSS) Version 11.01. Values for Mallows' Cp were computed manually based on values derived from the computerized models. Scatter plot of the models are, however, performed in Microsoft Excel (2003) for more presentable rendition. To facilitate estimation of the most significant predictors of healthy life expectancy (HALE), one-variable linear regression was performed on each of the 22 predictor variables.

To assist in the refinement of the first multi-variable model, a scatter plot of p vs. Mallows' Cp is shown in Figure 1. It may be gleaned from the scatter plot in Figure 1 that four predictor variables X2, X9, X20, and X22 are outliers, while the rest of the other predictor variables were concentrated in the area on the plot encircled in red. The predictors were divided into three blocks: (1) block 1 variables consist of those assumed from the results of the one-variable regression models which can most significantly predict HALE; (2) block 2 variables were those assumed to be moderate predictors of HALE; and (3) block 3 variables were those assumed to be least significant predictors of HALE.

Criteria used in grouping the results of. Model selection was performed using the software Statistical Package for the Social Sciences (SPSS) Version 11.01. Values for Mallows' Cp were computed manually based on values derived from the computerized models. Scatter plot of the models are, however, performed in Microsoft Excel (2003) for more presentable rendition.Preliminary Analysis To facilitate estimation of the most significant predictors of healthy life expectancy (HALE), one-variable linear regression was performed on each of the 22 predictor variables.

To assist in the refinement of the first multi-variable model, a scatter plot of p vs. Mallows' Cp is shown in Figure 1.Figure 1. Scatter plot of p vs Mallows' CpIt may be gleaned from the scatter plot in Figure 1 that four predictor variables X2, X9, X20, and X22 are outliers, while the rest of the other predictor variables were concentrated in the area on the plot encircled in red. Modeling and Analysis The predictors were divided into three blocks: (1) block 1 variables consist of those assumed from the results of the one-variable regression models which can most significantly predict HALE; (2) block 2 variables were those assumed to be moderate predictors of HALE; and (3) block 3 variables were those assumed to be least significant predictors of HALE.

Criteria used in grouping the results of the one-variable regression models were: (1) computed values of Mallows' Cp which most closely approached the value of p; (2) coefficient of determination (R2), delimited to those capable of predicting the variance in HALE by at least 50% (R = > 0.500); (3) highly correlated, based on the Pearson correlation coefficient (0.70 < r < 1.00); and (4) values of the sum of squares of the residuals are to be less