{FAC='savfile'|'dataset'} {FAC='savfile'|'dataset'} {FAC=* } {FAC=* } {FSC='savfile'|'dataset'} {FSC=* } [/METHOD = {CORRELATION**}] {COVARIANCE } [/SELECT=varname(value)] [/ANALYSIS=varlist...] [/PRINT=[DEFAULT**] [INITIAL**] [EXTRACTION**] [ROTATION**] [UNIVARIATE]...
这是对变量的因子分析，你可参见任何一本SPSS教程多元统计部分。
Field, A. (2005). Factor analysis using SPSS. Retrieved March, 17, 2009.Field, A.P. (2005), "Factor analysis using SPSS", available at: www.statisticshell.com/docs/factor.pdf (accessed 2 February 2013).Field, A. (2005) Factor Analysis Using SPSS. Available from: http://www....
Using these every time is good data analysis practice. SPSS doesn’t limit variable names to 8 characters like it used to, but you still can’t use spaces, and it will make coding easier if you keep the variable names short. learn more SPSS GLM: Choosing Fixed Factors and Covariates ...
FACTOR performs factor analysis based either on correlations or covariances and using one of the seven extraction methods. FACTOR also accepts matrix input in the form of correlation matrices, covariance matrices, or factor-loading matrices and can write the matrix materials to a matrix data file....
Finally, we'd create subscale scores in our data by computing means over these variables and perhaps proceed with a regression analysis. Excluding Items from Factor Analysis Most textbooks propose that you now exclude items with cross-loadings from the analysis. For our analysis, SPSS shows ...
《问卷统计分析实务:SPSS操作与应用》, 吴明隆著, 重庆大学出版社 《潜变量建模与Mplus应用·基础篇》, 王孟成著, 重庆大学出版社 因素分析简介 1. 含义 因素分析(Factor Analysis)是一种将描述某一事物的多个可观测的变量(即观测变量)缩减成描述该事物的少数几个不可观测的变量(即潜变量,又称潜在因素)的统计技...
Learn about factor analysis - a simple way to condense the data in many variables into a just a few variables.
Use the data SPSS 11.5 factor analysis 翻译结果5复制译文编辑译文朗读译文返回顶部 Carries on the factor analysis with SPSS11.5 to the data 相关内容 a我为当地的大学生,我们有责任为祖国的发展做出贡献。 I for the local university student, we have the responsibility to make the contribution for the...
在SPSS中，通过“分析”->“降维”->“因子分析”步骤，选择变量并进行主轴因子法分析，再通过旋转优化因素结构。Mplus则需要编写特定的语句，并关注模型拟合、旋转后因子负荷等信息。KMO值和Bartlett球形检验的显著性可以确认数据适合进行EFA。通过碎石图，研究者可以确定共同因素的数量。最终，理解并解释...