Statistical Estimation of Healthy Life Expectancy Research Paper

Statistical Estimation of Healthy Life Expectancy - explore Paper ExampleModel selection was performed using the softw ar Statistical Package for the Social Sciences (SPSS) discrepancy 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 than than presentable rendition.To facilitate estimation of the most significant predictors of healthy life forethought (HALE), one-variable linear regress was performed on each of the 22 predictor variables. To assist in the refinement of the offset multi-variable model, a sprinkling plot of p vs. Mallows Cp is shown in dactyl 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 encircle in red.The predictors were divided into three blocks (1) block 1 variables incorporate of those delusive from the results of the one-variable reverse models which can most significantly predict HALE (2) block 2 variables were those assumed to be reduce predictors of HALE and (3) block 3 variables were those assumed to be least significant predictors of HALE.Criteria utilise in separate the results of... Model selection was performed using the software Statistical Package for the Social Sciences (SPSS) indication 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 AnalysisTo 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.Fig ure 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 segmentation in HALE by at least 50% (R = 0.500) (3) highly correlated, based on the Pearson correlation coeffic ient (0.70 r 1.00) and (4) values of the sum of squares of the residuals are to be less