Aims: Multi-group analysis can be known as modeling the moderator variable since the strength of this method to moderates the influences of exogenous on endogenous variable. Basically, researchers interest to employ such method to extend their study to be more intense and practical. Sampling: This paper work used stratified sampling which is one of the probability sampling. Thus, the parametric method can be applied as set of statistical assumption. Methodology: Thus, multi-group analysis has become convenient to be practice in second generation modeling namely Structural Equation Modeling (SEM). Nevertheless, the limitation of Covariance Based Structural Equation Modeling (CB-SEM) causes the difficulties of researchers to further their studies. Hence, Partial Least Square Structural Equation Modeling (PLS-SEM) introduced to satisfy the necessity of researchers. Truthfully, multi-group analysis is not implement Method Article

This research develops techniques which are helpful in forecasting univariate time series data.

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) was used. The questionnaire were distributed by using two stage stratified cluster sampling technique to 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, a best fit model will be obtained for a better accuracy and precision estimation in further analysis.

This research develops techniques which are helpful in forecasting birth rate of male and female newborn in Malaysia. The techniques used in this study are Continuous Exponential, Discrete Logistics and Continuous Logistics Growth models. For the purpose of this study, secondary data of Total Birth Rate in Malaysia obtained from National Population and Family Development Board (NPFDB) Malaysia covering the period 1995 up to 2009 was used. From the result, it was found that Continuous Logistics model is the best model to forecast the birth rate of newborn in Malaysia since it has the lowest SSE values which are 598.462 for male and 392.8738 for female.