{smcl} {* 21nov2009}{...} {cmd:help sortl} {hline} {title:Title} {hi:sortl -} sort rotated loadings (pattern matrix) or rotated components created by {manhelp rotate MV} {title:Syntax} {cmd:sortl} {title:Description} {pstd} To make an interpretation of a factor solution easier, {cmd:-sortl-} sorts the rotated loadings (pattern matrix) or rotated components stored by {manhelp rotate MV} into the matrix {hi:e(r_L)}. It also sorts the matrix {hi:e(Psi)} of the unique or unexplained variances created by {manhelp factor MV} or by {manhelp pca MV} into the same order. {pstd} {cmd:-sortl-} displays the sorted loadings or components and the unique or unexplained variances of the variables in the Stata Results window, stores the sorted loadings or components into the matrix {hi:e(r_Ls)}, and stores the sorted unique or unexplained variances into the matrix {hi:e(Psis)}. {title:Example} {com}. webuse bg2 {txt}(Physician-cost data) {com}. factor bg*, factors(2) {txt}(obs=568) Factor analysis/correlation{col 52}Number of obs = {res} 568 {col 5}{txt}Method: principal factors{col 52}Retained factors = {res} 2 {col 5}{txt}Rotation: (unrotated){col 52}Number of params = {res} 11 {txt}{col 5}{hline 13}{c TT}{hline 60} {col 5} Factor {c |} {ralign 12:Eigenvalue} Difference Proportion Cumulative {col 5}{hline 13}{c +}{hline 60} {col 5}{ralign 11:Factor1} {c |}{res} 0.85389 0.31282 1.0310 1.0310 {txt}{col 5}{ralign 11:Factor2} {c |}{res} 0.54107 0.51786 0.6533 1.6844 {txt}{col 5}{ralign 11:Factor3} {c |}{res} 0.02321 0.17288 0.0280 1.7124 {txt}{col 5}{ralign 11:Factor4} {c |}{res} -0.14967 0.03951 -0.1807 1.5317 {txt}{col 5}{ralign 11:Factor5} {c |}{res} -0.18918 0.06197 -0.2284 1.3033 {txt}{col 5}{ralign 11:Factor6} {c |}{res} -0.25115 . -0.3033 1.0000 {txt}{col 5}{hline 13}{c BT}{hline 60} {col 5}LR test: independent vs. saturated: chi2({res}15{txt}) ={res} 269.07{txt} Prob>chi2 ={res} 0.0000 {txt}Factor loadings (pattern matrix) and unique variances {space 4}{hline 13}{c TT}{hline 10}{hline 10}{c TT}{hline 14} {space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1} {space 4}{hline 13}{c +}{hline 10}{hline 10}{c +}{hline 14} {space 4}{space 0}{ralign 12:bg2cost1}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.2470}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.3670}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.8043}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost2}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.3374}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.3321}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.7759}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost3}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.3764}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.3756}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.7173}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost4}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.3221}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.1942}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.8586}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost5}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.4550}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.2479}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.7315}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost6}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.4760}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.2364}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.7176}}}{space 1} {space 4}{hline 13}{c BT}{hline 10}{hline 10}{c BT}{hline 14} {com}. rotate, oblique promax {txt}Factor analysis/correlation{col 52}Number of obs = {res} 568 {col 5}{txt}Method: principal factors{col 52}Retained factors = {res} 2 {col 5}{txt}Rotation: oblique promax (Kaiser off){col 52}Number of params = {res} 11 {txt}{col 5}{hline 13}{c TT}{hline 60} {col 5} Factor {c |} Variance Proportion Rotated factors are correlated {col 5}{hline 13}{c +}{hline 60} {col 5}{ralign 11:Factor1} {c |}{res} 0.75531 0.9120 {txt}{col 5}{ralign 11:Factor2} {c |}{res} 0.69865 0.8436 {txt}{col 5}{hline 13}{c BT}{hline 60} {col 5}LR test: independent vs. saturated: chi2({res}15{txt}) ={res} 269.07{txt} Prob>chi2 ={res} 0.0000 {txt}Rotated factor loadings (pattern matrix) and unique variances {space 4}{hline 13}{c TT}{hline 10}{hline 10}{c TT}{hline 14} {space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{c |}{space 1}{ralign 12:Uniqueness}{space 1} {space 4}{hline 13}{c +}{hline 10}{hline 10}{c +}{hline 14} {space 4}{space 0}{ralign 12:bg2cost1}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.4428}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.1682}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.8043}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost2}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0020}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.4730}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.7759}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost3}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.0014}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.5320}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.7173}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost4}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0907}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.3480}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.8586}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost5}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.5059}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0513}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.7315}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost6}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.5126}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0729}}}{space 1}{c |}{space 1}{center 12:{res:{sf: 0.7176}}}{space 1} {space 4}{hline 13}{c BT}{hline 10}{hline 10}{c BT}{hline 14} Factor rotation matrix {space 4}{hline 13}{c TT}{hline 9}{hline 9} {space 4}{space 0}{ralign 12:}{space 1}{c |}{space 1}{ralign 7:Factor1}{space 1}{space 1}{ralign 7:Factor2}{space 1} {space 4}{hline 13}{c +}{hline 9}{hline 9} {space 4}{space 0}{ralign 12:Factor1}{space 1}{c |}{space 1}{ralign 7:{res:{sf: 0.8276}}}{space 1}{space 1}{ralign 7:{res:{sf:-0.7098}}}{space 1} {space 4}{space 0}{ralign 12:Factor2}{space 1}{c |}{space 1}{ralign 7:{res:{sf: 0.5614}}}{space 1}{space 1}{ralign 7:{res:{sf: 0.7045}}}{space 1} {space 4}{hline 13}{c BT}{hline 9}{hline 9} {com}. sortl {res} {txt}{p 0 0 2}Rotated factor loadings (pattern matrix) and unique variances sorted{p_end} {space 4}{hline 13}{c TT}{hline 10}{hline 10}{c TT}{hline 13} {space 4}{space 0}{ralign 12:Variable}{space 1}{c |}{space 1}{ralign 8:Factor1}{space 1}{space 1}{ralign 8:Factor2}{space 1}{c |}{space 1}{ralign 11:Uniqueness}{space 1} {space 4}{hline 13}{c +}{hline 10}{hline 10}{c +}{hline 13} {space 4}{space 0}{ralign 12:bg2cost6}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.5126}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0729}}}{space 1}{c |}{space 1}{ralign 11:{res:{sf: 0.7176}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost5}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.5059}}}{space 1}{space 1}{ralign 8:{res:{sf: -0.0513}}}{space 1}{c |}{space 1}{ralign 11:{res:{sf: 0.7315}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost1}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.4428}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.1682}}}{space 1}{c |}{space 1}{ralign 11:{res:{sf: 0.8043}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost3}{space 1}{c |}{space 1}{ralign 8:{res:{sf: 0.0014}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.5320}}}{space 1}{c |}{space 1}{ralign 11:{res:{sf: 0.7173}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost2}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0020}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.4730}}}{space 1}{c |}{space 1}{ralign 11:{res:{sf: 0.7759}}}{space 1} {space 4}{space 0}{ralign 12:bg2cost4}{space 1}{c |}{space 1}{ralign 8:{res:{sf: -0.0907}}}{space 1}{space 1}{ralign 8:{res:{sf: 0.3480}}}{space 1}{c |}{space 1}{ralign 11:{res:{sf: 0.8586}}}{space 1} {space 4}{hline 13}{c BT}{hline 10}{hline 10}{c BT}{hline 13} {title:Author} Dirk Enzmann http://www2.jura.uni-hamburg.de/instkrim/kriminologie/Mitarbeiter/Enzmann/Enzmann.html dirk.enzmann@uni-hamburg.de