دانلود مقاله ISI انگلیسی شماره 10090
عنوان فارسی مقاله

مطالعه شبیه سازی با استفاده از برنامه های CFAو EFA مبتنی بر تاثیر داده های از دست رفته در ابعاد آزمون

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
10090 2012 6 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
A simulation study using EFA and CFA programs based the impact of missing data on test dimensionality
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Expert Systems with Applications, , Volume 39, Issue 4, March 2012, Pages 4026-4031

کلمات کلیدی
بستن اطلاعات -     ابعاد آزمون -     تحلیل عاملی تأییدی -     اکتشافی تحلیل عاملی -     بسته آمار برای علوم اجتماعی
پیش نمایش مقاله
پیش نمایش مقاله مطالعه شبیه سازی با استفاده از  برنامه های CFAو  EFA  مبتنی بر تاثیر داده های از دست رفته در ابعاد آزمون

چکیده انگلیسی

This study examines the impact of missing rates and data imputation methods on test dimensionality. We consider how missing rate levels (10%, 20%, 30%, and 50%) and the six missed data imputation methods (Listwise, Serial Mean, Linear Interpolation, Linear Trend, EM, and Regression) affect the structure of a test. A simulation study is conducted using the SPSS 15.0 EFA and CFA programs. The EFA results for the six methods are similar, and all results obtained two factors. The CFA results also fit the hypothesized two factor structure model for all six methods. However, we observed that the EM method fits the EFA results relatively well. When the percentage of missing data is less than 20%, the impact of the imputation methods on test dimensionality is not statistically significant. The Serial Mean and Linear Trend methods are suggested for use when the percentage of missing data is greater than 30%.

نتیجه گیری انگلیسی

The different missing imputation methods do not have a significant impact on the test dimensionality when the percentage of missingness is low. However, when the percentage of missingness is high (>30%), it is suggested that the Serial Mean and Trend missing imputation methods be used, because both methods offer a better model fit than the other methods. We also conclude that the missingness has relatively little impact on the validity based on the internal structure, unless the missingness is large. There are some limitations of this study. We assume that the missingness mechanism is MCAR, and include only continuously observed items in this study. We would like to further consider MAR or NMAR missingness mechanisms and dichotomous observed items to investigate the effect of missing imputation methods on the test structure.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.