Sensitivity Analysis in Nonrandomized Longitudinal Mediation Analysis

Mediation analysis relies on an untestable assumption of the no omitted confounders, which posits that an omitted variable that confounds the relationships between the antecedent, mediator, and outcome variables cannot exist. One common model in alcohol addiction studies is a nonrandomized latent growth curve mediation model (LGCMM), where the antecedent variable is not randomized, the two covarying mediators are latent intercept and slope modeling longitudinal effect of the repeated measures mediator, and an outcome variable that measures alcohol use. An important gap in the literature is lack of sensitivity analysis techniques to assess the effect of the violation of the no omitted confounder assumption in a nonrandomized LGCMM. We extend a sensitivity analysis technique, termed correlated augmented mediation sensitivity analysis (CAMSA), to a nonrandomized LGCMM. We address several unresolved issues in conducting CAMSA for the nonrandomized LGCMM and present: (a) analytical results showing how confounder correlations model a confounding bias, (b) algorithms to address admissible values for confounder correlations, (c) accessible R code within an SEM framework to conduct our proposed sensitivity analysis, and (d) an empirical example. We conclude that conducting sensitivity analysis to ascertain robustness of the mediation analysis is critical.

Landslide Susceptibility in Relation to Correlation of Groundwater Development and Ground Condition

Rainfall is inevitably one of the main factors that trigger landslides. However, not much study has been conducted on the impact of groundwater rise on slope stability. Thus, this study is intended to focus on the rise of the groundwater level from the bottom of the slope which would lead to landslides due to pore pressure development by eliminating other landslide-triggering factors (i.e., infiltration and surface runoff). Saturated sand was used for slope modeling, and sand densities of 1523 kg/m3, 1562 kg/m3, and 1592 kg/m3 were tested with a constant slope angle of 45°. Another set of experiments was also performed on slopes having angles of 25°, 45°, and 60° and with a maintained density of sand at 1562 kg/m3. Through observation, failure was initiated first at the toe of the slope before minor and major slips or total collapse occurs. Dimensions of slip surfaces were measured and included in SLOPE/W for the computation of the safety factor. In conclusion, safety factors are found to be higher in denser soil and in the lowest slope angle. However, faster occurrence of collapse in denser soil was identified and could be contributed by the faster pore water pressure development.

Three-dimensional numerical analysis for rock slope stability using shear strength reduction method

Existing numerical modeling of three-dimensional (3D) slopes is performed mainly by using the shear strength reduction (SSR) technique based on the linear Mohr–Coulomb (MC) criterion, whereas the nonlinear failure criterion for rock slope stability is seldom used in slope modeling. However, it is known that rock mass strength is a nonlinear stress function and that, therefore, the linear MC criterion does not agree with the rock mass failure envelope very well. In this research, a nonlinear SSR technique is proposed that can use the Hoek–Brown (HB) criterion to represent the nonlinear behavior of a rock mass in the FLAC3D program to analyze 3D slope stability. Extensive case studies are carried out to investigate the influence of the convergence criterion and boundary conditions on the 3D slope modeling. Results show that the convergence criterion used in the 3D model plays an important role, not only in terms of calculation of the factor of safety (FOS), but also in terms of the shape of the failure surface. The case studies also demonstrate that the value of the FOS for a given slope will be significantly influenced by the boundary condition when the slope angle is less than 50°.