The effect of latent and error non-normality on corrections to the test statistic in structural equation modeling

In structural equation modeling, several corrections to the likelihood-ratio model test statistic have been developed to counter the effects of non-normal data. Previous robustness studies investigating the performance of these corrections typically induced non-normality in the indicator variables. However, non-normality in the indicators can originate from non-normal errors or non-normal latent factors. We conducted a Monte Carlo simulation to analyze the effect of non-normality in factors and errors on six different test statistics based on maximum likelihood estimation by evaluating the effect on empirical rejection rates and derived indices (RMSEA and CFI) for different degrees of non-normality and sample sizes. We considered the uncorrected likelihood-ratio model test statistic and the Satorra–Bentler scaled test statistic with Bartlett correction, as well as the mean and variance adjusted test statistic, a scale-shifted approach, a third moment-adjusted test statistic, and an approach drawing inferences from the relevant asymptotic chi-square mixture distribution. The results indicate that the values of the uncorrected test statistic—compared to values under normality—are associated with a severely inflated type I error rate when latent variables are non-normal, but virtually no differences occur when errors are non-normal. Although no general pattern regarding the source of non-normality for all analyzed measures of fit can be derived, the Satorra–Bentler scaled test statistic with Bartlett correction performed satisfactorily across conditions.

Outlier analysis of sloshing impact loads on liquid ship cargo

This paper introduces an outlier analysis which can improve the convergence of the statistical analysis results of sloshing model test data. The paper classify possible outliers in the sloshing model test into three categories and present a treatment method for each outlier. The developed outlier analysis is adapted to the model test results for the cargo of the liquefied-natural-gas (LNG) carrier in operation. The results of the present new method are compared with those of the conventional procedure, particularly focusing on long-term sloshing prediction. Through this study, the effectiveness of the present method is observed, and it is found that the present method provides is robust and reliable results in the application of experimental data for load prediction.

Optimal portfolio analysis of manufacturing entities in the Indonesia Sharia Stock Index

The purpose of this research is to determine the optimal portfolio for manufacturing entities listed on the Indonesian Sharia Stock Index based on a single index model test. The population of this research is manufacturing entities that have been listed in the Indonesian Sharia Stock Index on the Indonesia Stock Exchange for the Period 2019-2020. This study uses a purposive sampling technique using several criteria. Based on this technique, 31 entities meet the criteria. The results showed that the expected return was 5.65%, and the possible risk was 0.22% for 15 (fifteen) stocks included in the optimal portfolio category.

Reducing Settlement and Collapse of Gypseous Soil Using Geotextile Reinforcement

Collapsible soils are problematic soils that have substantial strength while dry but lose strength when wet, resulting in excessive settlements. Soil collapse occurs when increasing moisture weakens chemical or physical connections between soil particles, allowing the soil structure to collapse. The existence of these soils, often with significant gypsum concentration, created serious challenges for structures and major projects. The primary goal of this study is to conduct a series of model tests subjected to static vertical stress to assess the ability of soil stabilization using geosynthetics material by employing single, double, and triple geotextile layers put at various places. A unique model test configuration was employed for this testing. The gypseous soil used was brought from near Sawa Lake by coordinates (31◦18′42.83″N, 45◦00′49.36″E) in Al-Muthanna Governorate. The gypsum content was more than (37%). It was found that, the ultimate bearing capacity of dry and wet gypseous soil models had been determined by using Two Tangent Intersection technique. The results show the Settlement Reduction Factor (SRF) % and the ratio of decreasing the collapse magnitude (Δed )