A feasible method for standard errors of estimate in maximum likelihood factor analysis
A feasible method for standard errors of estimate in maximum likelihood factor analysis
复制标题
最大似然因子分析中估计标准误差的一种可行方法
DOI：
10.1007/bf02294078
复制
发表时间：
1980
期刊：
影响因子：
3
通讯作者：
D. B. Clarkson
中科院分区：
文献类型：
--
作者：
R. Jennrich;D. B. Clarkson
A jackknife-like procedure is developed for producing standard errors of estimate in maximum likelihood factor analysis. Unlike earlier methods based on information theory, the procedure developed is computationally feasible on larger problems. Unlike earlier methods based on the jackknife, the present procedure is not plagued by the factor alignment problem, the Heywood case problem, or the necessity to jackknife by groups. Standard errors may be produced for rotated and unrotated loading estimates using either orthogonal or oblique rotation as well as for estimates of unique factor variances and common factor correlations. The total cost for larger problems is a small multiple of the square of the number of variables times the number of observations used in the analysis. Examples are given to demonstrate the feasibility of the method.
