Computing measures of simplicity of fit for loadings in factor-analytically derived scales

Computing measures of simplicity of fit for loadings in factor-analytically derived scales
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DOI:
10.3758/bf03195531
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发表时间:
2003-11-01
期刊:
BEHAVIOR RESEARCH METHODS INSTRUMENTS & COMPUTERS
影响因子:
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通讯作者:
Fleming, JS
Fleming, JS
中科院分区:
其他
文献类型:
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作者:
Fleming, JS

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当使用因素分析来开发测量量表时,寻求一个非常简单的结构。SIMLOAD程序计算加载矩阵的行和列的阶乘简单性的度量(通常是因子模式)以及一些总体度量。其中包括Kaiser(1974)的变量(行)的阶乘简单性指数、作者的因子(列)的尺度拟合指数、Bentler(1977)的无标度矩阵测度和超平面计数。建议常规使用这些措施的多因素规模的发展。这些措施也可能是有用的,在更一般的因素的应用程序和验证性以及探索性分析。SIMLOAD还计算因子尺度相关性、尺度alpha系数(包括移除项时的alpha)和排序载荷以便于解释。
A very simple structure is sought when factor analysis is used to develop measurement scales. The SIMLOAD program computes measures of factorial simplicity for rows and columns of loading matrices (usually the factor pattern) as well as some overall measures. These include Kaiser's (1974) index of factorial simplicity for variables (rows), the author's scale fit index for factors (columns), Bentler's (1977) scale-free matrix measure, and hyperplane counts. Routine use of these measures is recommended for multifactor scale development. The measures may also be useful in more general factor applications and in confirmatory as well as exploratory analyses. SIMLOAD also computes factor scale intercorrelations, scale alpha coefficients (including alpha when an item is removed), and sorted loadings for ease of interpretation.