A Comparison Between Ordinary Least Square (OLS) And Structural Equation Modeling (SEM) Methods In Estimating The Influencial Factors Of 8th Grades Student’s Mathematics Achievement In Malaysia
نویسندگان
چکیده
This research demonstrates the application of Structural Equation Modeling (SEM) method in order to obtain the best fit model for a more efficient and accurate inter-relationship among variables findings and interpretation. For the purpose of this study, secondary data of Trends in International Mathematics and Science Study (TIMSS) had been used. The data were distributed by using two stage stratified cluster sampling technique and involving 5733 eighth grades students in Malaysia. A Confirmatory Factor Analysis (CFA), Discriminant Validity and Path Analysis had been conducted to obtain the best fit model of SEM. At the end of the study, the best fit model was then compared to the Ordinary Least Square (OLS) model method. From the Chi-Square value, it is found that the model of SEM method is much better compared to OLS model method based on its fitness and accuracy. KeywordsMathematics Achievement, Mediation, Ordinary Least Square, Structural Equation Modeling, TIMSS —————————— ——————————
منابع مشابه
Comparison of the Performance of Geographically Weighted Regression and Ordinary Least Squares for modeling of Sea surface temperature in Oman Sea
In Marine discussions, the study of sea surface temperature (SST) and study of its spatial relationships with other ocean parameters are of particular importance, in such a way that the accurate recognition of the SST relationships with other parameters allows the study of many ocean and atmospheric processes. Therefore, in this study, spatial relations modeling of SST with Surface Wind Speed (...
متن کاملLanguage Proficiency and Identity: Developing a Structural Equation Modeling (SEM) of Identity for Iranian EFL Learners
This study was an endeavor to develop a model of identity among Iranian EFL learners. To achieve this end, a multiphase design was implemented. Initially, it attempted to investigate different factors of identity to propose and validate a model. Thus, 120 EFL learners studying in different English language institutes in Iran were randomly selected, and 36 learners were interviewed about their v...
متن کاملStructural equation modeling for decomposing rank-dependent indicators of socioeconomic inequality of health: an empirical study
We present a flexible structural equation modeling (SEM) framework for the regression-based decomposition of rank-dependent indicators of socioeconomic inequality of health and compare it with simple ordinary least squares (OLS) regression. The SEM framework forms the basis for a proper use of the most prominent one- and two-dimensional decompositions and provides an argument for using the biva...
متن کاملEmbedding Irt in Structural Equation Models: a Comparison with Regression Based on Irt Scores
This paper reviews the problems associated with using IRT-based latent variable scores for analytical modeling, discusses the connection between IRT and SEM-based latent regression modelling for discrete data, and compares regression parameter estimates obtained using predicted IRT scores and standardized Number-Right scores in OLS regression with regression estimates obtained using the combine...
متن کاملA Critique of Partial Least Squares, and a Preliminary Assessement of an Alternative Estimation Method
Partial least squares (PLS) is sometimes used as an alternative to covariance-based structural equation modeling (SEM). This paper briefly reviews currently available SEM techniques, and provides a critique of the perceived advantages of PLS over covariance-based SEM as commonly cited by PLS users. Specific attention is drawn to the primary disadvantage of PLS, namely the lack of consistency of...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2013