The assessment of model fit is important in Structural Equation Modeling (SEM). Several goodness-of-fit (GoF) measures are affected by sample size and the number of parameters to be estimated. A large sample size is needed to test a complex model involving a large number of parameters to be estimated. One of the solutions to reduce the number of parameters to be estimated in a given model is by considering item parceling. The effects of item parceling on parameter estimates and GoF measures in a structural equation model was investigated via a simulation study. The simulation results indicate that the parameter estimates are closer to the true parameter values for the IL model whenever the distribution of data is normal but biased when the data is highly skewed. The parameter estimates for the IP model were found to be underestimated for both normal and non-normal data. The GoF measures were higher for the IP model. Additionally, the RMSEA was lower for the IP model when data were skewed. This shows that item parceling may improve GoF measures but the effect of exogenous on endogenous variable is underestimated. Application to a real data set confirmed the results of the simulation study.
This study highlights the advantage of functional data approach in assessing and comparing the PM10 pollutant behaviour as an alternative statistical approach during and between the two extreme haze years (1997 and 2005) that have been reported in Selangor, state of Malaysia. The aim of the study was to improvise the current conventional methods used in air quality assessment so that any unforeseen implicit information can be revealed and the previous research findings can be justified. An analysis based on the daily diurnal curves in place of discrete point values was performed. The
analysis results provided evidences of the influence of the change in the climate (due to the El-Nino event), the different levels of different emission sources and meteorological conditions on the severity of the PM10 problem. By means of the cummulative exceedence index and the functional depth method, most of the monitoring stations for the year 2005 experienced the worst day of critical exceedences on the 10th of August, while for the year 1997 it occurred between 13th and 26th September inclusively at different dates among the stations.
In most research including environmental research, missing recorded data often exists and has become a common problem for data quality. In this study, several imputation methods that have been designed based on the techniques for functional data analysis are introduced and the capability of the methods for estimating missing values is investigated. Single imputation methods and iterative imputation methods are conducted by means of curve estimation using regression and roughness penalty smoothing approaches. The performance of the methods is compared using a reference data set, the real PM10 data from an air quality monitoring station namely the Petaling Jaya station located at the western part of Peninsular Malaysia. A hundred of the missing data sets that have been generated from a reference data set with six different patterns of missing values are used to investigate the performance of the considered methods. The patterns are simulated according to three percentages (5, 10 and 15) of missing values with respect to two different sizes (3 and 7) of maximum gap lengths (consecutive missing points). By means of the mean absolute error, the index of agreement and the coefficient of determination as the performance indicators, the results have showed that the iterative imputation method using the roughness penalty approach is more flexible and superior to other methods.
A good quality of rainfall data is highly necessary in hydrological and meteorological analyses. Lack
of quality in rainfall data will influence the process of analyses and subsequently, produce misleading
results. Thus, this study is aimed to propose modified missing rainfall data treatment methods that
produced more accurate estimation results. In this study, the old normal ratio method and the
modified normal ratio based on trimmed mean are combined with geographical coordinate method.
The performances of these modified methods were tested on various levels of the missing data of 36
years complete daily rainfall records from eighteen meteorology stations in Peninsular Malaysia. The
results indicated that both modified methods improved the estimation of missing rainfall values at the
target station based on the least error measurements. Modified normal ratio based on trimmed mean
with geographical coordinate method is found to be the most appropriate method for station Batu
Kurau and Sg. Bernam while modified old normal ratio with geographical coordinate is the most
accurate in estimating the missing data at station Genting Klang.
This study attempts to trace changes in the wet spells over Peninsular Malaysia based on the daily rainfall data from 32 selected rainfall stations which include four sub-regions; northwest, west, south and east, for the period of 1975 to 2004. Six wet spells indices comprising of the main characteristics (maximum, mean, standard deviation), the persistency of two consecutive wet days and the frequency of the short and long duration of wet spells will be used to identify whether or not these indices increase or decrease over Peninsular Malaysia during the monsoon seasons. The study indicates that the eastern areas of the peninsula could be considered as the wettest areas since almost all the indices of wet spells over these areas are higher than over the other regions during the northeast monsoon (NE). The Mann-Kendall (MK) trend test revealed that almost all of the stations located in the eastern areas of the peninsula exhibited a positive trend in the mean, variability and persistency of wet spells indices during the NE monsoon, while a negative trend was observed during the southwest monsoon (SW) in these areas. Moreover, these indices showed a positive trend, and at the same time a decreasing trend was observed in the frequency of the long wet spells in most stations located over the west coast of Peninsular Malaysia during the SW monsoon for the period of 1975 to 2004.
This study investigated the spatial pattern and trends of the daily rainfall data in Peninsular Malaysia based on seasonal rainfall indices. Five rainfall indices which describe the main characteristics of rainfall, the total amount of rainfall, frequency of wet days, rainfall intensity, extreme frequency, and extreme intensity, were employed in this study. The statistics of rainfall indices were calculated in terms of their means for four regions in Peninsular Malaysia for the period 1975 to 2004. The findings indicate that the southwest monsoon had the greatest impact on the western part of the Peninsula, particularly in characterizing the rainfall pattern of the northwest region. During this season, the northwest region could be considered as the wettest region since all rainfall indices tested are higher than in other regions of the Peninsula. Otherwise, the northwest region is denoted as the driest part of the Peninsula during the northeast monsoon period. The northwest region is less influenced by the northeast monsoon because of the existence of the Titiwangsa Range, which blocks the region from receiving heavy rainfall. On the other hand, it is found that the lowlands areas such as the eastern part of the Peninsula are strongly characterized by the northeast monsoonal flow. Based on the results of the Mann-Kendall test, as the trend of the total amount of rainfall and the frequency of wet days during the southwest monsoon decrease at most of the stations, the rainfall intensity increases. In contrast, increasing trends in both the total amount of rainfall and the frequency of wet days were observed at several stations during the northeast monsoon, which give rise to the increasing trend of rainfall intensity. The results for both seasons indicate that there are significantly decreasing trends in the frequency of wet days during the extreme events for most of the stations on the peninsula. However, a smaller number of significant trends was found for extreme intensity.