# 选择4个因子,不旋转,最大似然法 fa.res <- fa(df.use, nfactors = 4, rotate = "none", fm="ml") fa.res ## Factor Analysis using method = ml ## Call: fa(r = df.use, nfactors = 4, rotate = "none", fm = "ml") ## Standardized loadings (pattern matrix) based upon correlation matrix ## ML3 ML1 ML2 ML4 h2 u2 com ## 门诊人次 0.61 0.78 0.11 -0.01 1.00 0.005 1.9 ## 出院人数 -0.40 0.31 0.34 -0.59 0.72 0.276 3.1 ## 病床利用率 -0.30 0.56 0.25 0.49 0.71 0.289 2.9 ## 病床周转次数 -0.55 0.75 0.35 0.01 1.00 0.005 2.3 ## 平均住院天数 0.67 -0.13 0.16 0.26 0.57 0.435 1.5 ## 治愈好转率 0.15 -0.39 0.91 0.00 1.00 0.005 1.4 ## 病死率 0.14 -0.07 -0.47 0.10 0.26 0.743 1.3 ## 诊断符合率 0.45 0.11 -0.10 0.36 0.36 0.642 2.2 ## 抢救成功率 -0.56 -0.12 0.05 -0.46 0.55 0.455 2.1 ## ## ML3 ML1 ML2 ML4 ## SS loadings 1.94 1.79 1.40 1.02 ## Proportion Var 0.22 0.20 0.16 0.11 ## Cumulative Var 0.22 0.41 0.57 0.68 ## Proportion Explained 0.32 0.29 0.23 0.17 ## Cumulative Proportion 0.32 0.61 0.83 1.00 ## ## Mean item complexity = 2.1 ## Test of the hypothesis that 4 factors are sufficient. ## ## The degrees of freedom for the null model are 36 and the objective function was 3.82 with Chi Square of 119.03 ## The degrees of freedom for the model are 6 and the objective function was 0.24 ## ## The root mean square of the residuals (RMSR) is 0.04 ## The df corrected root mean square of the residuals is 0.09 ## ## The harmonic number of observations is 36 with the empirical chi square 3.43 with prob < 0.75 ## The total number of observations was 36 with Likelihood Chi Square = 6.84 with prob < 0.34 ## ## Tucker Lewis Index of factoring reliability = 0.931 ## RMSEA index = 0.055 and the 90 % confidence intervals are 0 0.235 ## BIC = -14.67 ## Fit based upon off diagonal values = 0.99 ## Measures of factor score adequacy ## ML3 ML1 ML2 ML4 ## Correlation of (regression) scores with factors 1.00 1.00 1.00 0.87 ## Multiple R square of scores with factors 0.99 1.00 0.99 0.75 ## Minimum correlation of possible factor scores 0.99 0.99 0.99 0.50
# 选择4个因子,最大方差旋转,最大似然法 fa.res <- fa(df.use, nfactors = 4, rotate = "varimax", fm="ml") fa.res ## Factor Analysis using method = ml ## Call: fa(r = df.use, nfactors = 4, rotate = "varimax", fm = "ml") ## Standardized loadings (pattern matrix) based upon correlation matrix ## ML3 ML1 ML2 ML4 h2 u2 com ## 门诊人次 -0.31 0.23 -0.03 0.92 1.00 0.005 1.4 ## 出院人数 0.75 0.16 0.24 0.27 0.72 0.276 1.6 ## 病床利用率 -0.10 0.83 0.03 0.07 0.71 0.289 1.0 ## 病床周转次数 0.46 0.84 0.09 0.26 1.00 0.005 1.8 ## 平均住院天数 -0.64 -0.23 0.24 0.21 0.57 0.435 1.8 ## 治愈好转率 -0.09 -0.09 0.98 -0.10 1.00 0.005 1.1 ## 病死率 -0.20 -0.18 -0.42 -0.06 0.26 0.743 1.9 ## 诊断符合率 -0.56 0.02 -0.10 0.18 0.36 0.642 1.3 ## 抢救成功率 0.70 -0.04 0.04 -0.21 0.55 0.455 1.2 ## ## ML3 ML1 ML2 ML4 ## SS loadings 2.15 1.58 1.29 1.12 ## Proportion Var 0.24 0.18 0.14 0.12 ## Cumulative Var 0.24 0.41 0.56 0.68 ## Proportion Explained 0.35 0.26 0.21 0.18 ## Cumulative Proportion 0.35 0.61 0.82 1.00 ## ## Mean item complexity = 1.4 ## Test of the hypothesis that 4 factors are sufficient. ## ## The degrees of freedom for the null model are 36 and the objective function was 3.82 with Chi Square of 119.03 ## The degrees of freedom for the model are 6 and the objective function was 0.24 ## ## The root mean square of the residuals (RMSR) is 0.04 ## The df corrected root mean square of the residuals is 0.09 ## ## The harmonic number of observations is 36 with the empirical chi square 3.43 with prob < 0.75 ## The total number of observations was 36 with Likelihood Chi Square = 6.84 with prob < 0.34 ## ## Tucker Lewis Index of factoring reliability = 0.931 ## RMSEA index = 0.055 and the 90 % confidence intervals are 0 0.235 ## BIC = -14.67 ## Fit based upon off diagonal values = 0.99 ## Measures of factor score adequacy ## ML3 ML1 ML2 ML4 ## Correlation of (regression) scores with factors 0.93 0.96 1.00 0.98 ## Multiple R square of scores with factors 0.86 0.92 0.99 0.96 ## Minimum correlation of possible factor scores 0.72 0.85 0.99 0.91