其实您可以参考Stata手册上的例子与解说！

Stata12手册里的[MV] Multivariates Statistics的factor-factor analysis的例子一与例子二
296页里用了Tarlov et al. (1989)的研究【即Example1】，您可以看到他们也遇到与您一样的状况！

进一步的在Example2的开头【第一段297页下方】就指出那样的不合理情况！
The cumulative proportions of the eigenvalues exceeded 1.0 in our factor analysis because of the
negative eigenvalues. By default, the proportion and cumulative proportion columns are computed
using the sum of all eigenvalues as the divisor. The altdivisor option allows you to display the
proportions and cumulative proportions by using the trace of the correlation matrix as the divisor.
This option is allowed at estimation time or when replaying results. We demonstrate by replaying the
results with this option.

参考参考吧！ 但如果要更直观的解释，就期待高手们的补充吧！

补充一下，我以上用的的stata默认的pf方法。
如果用pcf，则不会出现这个问题。

       pf specifies that the principal-factor method be used to analyze the correlation
            matrix.  The factor loadings, sometimes called the factor patterns, are computed
            using the squared multiple correlations as estimates of the communality.  pf is
            the default.

        pcf specifies that the principal-component factor method be used to analyze the
            correlation matrix.  The communalities are assumed to be 1.
    pf, pcf, ipf, and ml indicate the type of estimation to be performed.  The default is
        pf.

能否给点更直观的解释？多谢！

您好，我碰到跟您一样的问题，请问您的问题现在解决了吗，能否指点一下我？谢谢了！

你做之前指标预处理了嘛？负指标转换成为正的