We propose a broad class of so-called Cox–Aalen transformation models that incorporate both multiplicative and additive covariate effects on the baseline hazard function within a transformation. The proposed models provide a highly flexible and versatile class of semiparametric models that include the transformation models and the Cox–Aalen model as special cases. Specifically, it extends the transformation models by allowing potentially time-dependent covariates to work additively on the baseline hazard and extends the Cox–Aalen model through a predetermined transformation function. We propose an estimating equation approach and devise an expectation-solving (ES) algorithm that involves fast and robust calculations. The resulting estimator is shown to be consistent and asymptotically normal via modern empirical process techniques. The ES algorithm yields a computationally simple method for estimating the variance of both parametric and nonparametric estimators. Finally, we demonstrate the performance of our procedures through extensive simulation studies and applications in two randomized, placebo-controlled human immunodeficiency virus (HIV) prevention efficacy trials. The data example shows the utility of the proposed Cox–Aalen transformation models in enhancing statistical power for discovering covariate effects.

Background/Objectives: Community health nursing (CHN) clinical experiences are essential for preparing undergraduate nursing students to deliver safe and effective home-based care; however, access to placements is often limited. Escape room simulation (ERS) has been used in nursing education, yet its feasibility in CHN remains underexplored. This exploratory study aimed to examine the feasibility of using ERS in undergraduate CHN education by evaluating students’ perceived competence, confidence, and learning experiences following participation in the simulation. Methods: A quasi-experimental, single-group pre–post design was conducted with 56 undergraduate nursing students. Data were collected at three time points: prior to the simulation, immediately after, and ten weeks post-intervention. Measures included standardized assessments of CHN competence and confidence, as well as student perceptions of the simulation experience. Linear mixed-effects modeling was used to examine changes over time. Results: Significant improvements were observed in both competence (t = 6.413, p < 0.001) and confidence (t = 8.142, p < 0.001) following the simulation, with gains maintained at ten weeks. Variability in competence decreased across participants over time, while confidence gains varied individually, with larger improvements among participants with lower baseline scores. Participants reported high levels of satisfaction with the simulation despite limited prior exposure. Conclusions: ERS was associated with improvements in undergraduate nursing students’ perceived competence and confidence, suggesting that it may represent a feasible and acceptable supplemental educational strategy for undergraduate CHN education. Additional research is needed to better evaluate the educational impact and underlying mechanisms of ERS in CHN education, and to support the development of evidence-based ERS approaches that enhance student preparedness for community-based nursing practice in settings where clinical placements are limited.