000			02870cam a2200337 a 4500
003			EG-GiCUC
005			20250223031824.0
008			171014s2017 ua f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.18.04.M.Sc.2017.No.E
100	0		_aNoha Gamil Mahmoud Abdelreheem
245	1	0	_aEstimation methods of structural equation models : _bA comparative study / _cNoha Gamil Mahmoud Abdelreheem ; Supervised Ahmed Amin Elsheikh , Mohamed Reda Abonazel
246	1	5	_aطرق تقدير نماذج المعادلات الهيكلية : _bدراسة مقارنة
260			_aCairo : _bNoha Gamil Mahmoud Abdelreheem , _c2017
300			_a117 Leaves ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Statistics and Econometrics
520			_aStructural equation modeling (SEM) is a widely used statistical method in most of social science fields. Similar to other statistical methods, the choice of the appropriate estimation methods affects the results of the analysis, thus we found it important to examine the performance of SEM estimation methods under the different situations a researcher might face in reality. Thereby, an investigation on the performance of SEM estimation methods was held through an application study as well as simulation study, we mainly divided the studies into two sections: One under complete data analysis and the second is under incomplete (missing) data analysis. In simulation studies different conditions were imposed with respect to sample sizes and factor loading values, as well as misspecification but only under complete data. Both studies were executed through the statistical software R. Finally, the performances of the estimation methods were compared in terms of RMSEA, SRMR, CFI, TLI, and convergence rate (especially with missing data). Under complete data it was found that maximum likelihood, robust maximum likelihood, and diagonally weighted least squares gave better fit to the model than the other two methods. Under misspecified model, it was found that ML method was the most sensitive method to misspecification, followed by WLS and GLS. It was also concluded that the effect of factor loading was negative on the fit indices, which might be used as an indicator for misspecification. DWLS was the least method that showed sensitivity to misspecification
530			_aIssued also as CD
653		4	_aGeneralized Least Squares
653		4	_aMaximum likelihood
653		4	_aStructural equation modeling
700	0		_aAhmed Amin Elsheikh , _eSupervisor
700	0		_aMohamed Reda Abonazel , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aSamia _eCataloger
942			_2ddc _cTH
999			_c62894 _d62894