A partir de los datos del primer ejemplo, se puede observar como la solución varia al utilizar el metodo del factor principal.

Extraction   1 for analysis   1, Principal Axis Factoring (PAF)
Initial Statistics:
Variable     Communality  *  Factor   Eigenvalue   Pct of Var   Cum Pct
X16               .51364  *     1       4.25313       70.9         70.9
X17               .69627  *     2        .49556        8.3         79.1
X18               .64848  *     3        .46084        7.7         86.8
X19               .78264  *     4        .42083        7.0         93.8
X20               .49440  *     5        .22175        3.7         97.5
X21               .69691  *     6        .14788        2.5        100.0
PAF   extracted   1 factors.    5 iterations required.
Factor Matrix:
              Factor  1
X16             .73464
X17             .82770
X18             .80748
X19             .90727
X20             .71440
X21             .84284
Final Statistics:
Variable     Communality  *  Factor   Eigenvalue   Pct of Var   Cum Pct
X16               .53970  *     1       3.92069       65.3         65.3
X17               .68509  *
X18               .65202  *
X19               .82314  *
X20               .51037  *
X21               .71037  *