کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
11016183 | 1778131 | 2019 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Structural equation modeling of multiple-indicator multimethod-multioccasion data: A primer
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
علوم اعصاب رفتاری
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چکیده انگلیسی
We provide a tutorial on how to analyze multiple-indicator multi-method (MM) longitudinal (multi-occasion, MO) data. Multiple-indicator MM-MO data presents specific challenges due to (1) different types of method effects, (2) longitudinal and cross-method measurement equivalence (ME) testing, (3) the question as to which process characterizes the longitudinal course of the construct under study, and (4) the issue of convergent validity versus method-specificity of different methods such as multiple informants. We present different models for multiple-indicator MM-MO data and discuss a modeling strategy that begins with basic single-method longitudinal confirmatory factor models and ends with more sophisticated MM-MO models. Our proposed strategy allows researchers to identify a well-fitting and possibly parsimonious model through a series of model comparisons. We illustrate our proposed MM-MO modeling strategy based on mother and father reports of inattention in a sample of NÂ =Â 805 Spanish children.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Personality and Individual Differences - Volume 136, 1 January 2019, Pages 79-89
Journal: Personality and Individual Differences - Volume 136, 1 January 2019, Pages 79-89
نویسندگان
Christian Geiser, Fred A. Hintz, G. Leonard Burns, Mateu Servera,