The majority of current smokers in the United States want to quit smoking; however, long-term abstinence rates do not improve beyond 30%, despite the availability of effective pharmaco-behavioral treatments and increased outreach of awareness programs on quitting benefits. One of the reasons is non-adherence to pharmacological treatment. Pharmacological treatments are developed to alleviate withdrawal symptoms experienced during a quit attempt. However, without continued treatment adherence, especially in the first few weeks of a quit attempt (when withdrawal symptoms fluctuate the most), the chances of relapse peak. Thus, adherence to pharmacological treatments must be improved to sustain long-term smoking abstinence. Moreover, smoking cessation is a complex and time-varying process. Therefore, the time-varying causal structure of adherence and smoking cessation must be studied carefully.The time-varying mechanisms underlying the smoking cessation process can be captured efficiently through intensive longitudinal data and quantified through appropriate methods. Mediation analysis is an efficient tool for studying such mechanisms. However, despite the time-varying nature of the data, existing approaches for assessing mediation provide overall average (in)direct effects over time and omit describing the temporal characteristic of the dynamic effect. This dissertation research aims to develop a new approach to estimating time-varying causal (in)direct effects of pharmacological treatments on daily smoking cessation outcome(s) mediated via daily treatment adherence. Additionally, it is hypothesized that adherence is influenced by daily stress events related to social contextual factors, not treatment-induced. The purpose of this research is to derive time-varying causal (in)direct effects. A local polynomial regression-based approach integrated with the mediational g-formula was proposed as a possible solution. Furthermore, since no other studies have studied time-specific mediation effects using a potential outcomes framework-based method, the performance of the proposed method was tested using two simulation studies. Finally, the optimum analytical approach (based on the findings from the simulation studies) was applied to answer the substantive research questions on smoking cessation using empirical data from a smoking cessation clinical trial. This dissertation is divided into six chapters. A brief overview of the chapters is as follows: Chapter 1 provides a comprehensive background and rationale for the methodological and substantive research that motivated this work. The chapter concludes with the three specific aims addressed in this research and a summary of the next steps. In Chapter 2, the longitudinal causal frameworks and the assumptions required to interpret the estimated time-varying (in)direct effects as causal are described in detail. These frameworks were further used in Chapters 3 and 4 for the two simulation studies that evaluated the performance of the proposed new approach. The simulation study in Chapter 3 evaluates the time-varying (in)direct effects in a longitudinal study in the absence of exposure-induced time-varying confounding of a mediator-outcome pathway. Four outcome scenarios with a binary exposure, a binary mediator, and a time-varying binary confounder of the mediator-outcome pathway were examined: 1) continuous outcome, 2) rare binary outcome, 3) common binary outcome, and 4) count outcome that is not zero-inflated. Two types of path-specific causal estimands are identifiable for these scenarios. The findings suggest good performance of the proposed analytical approach in producing accurate effect estimates (reduced bias and reasonable coverage) of these estimands for all the outcome scenarios. The simulation study in Chapter 4 evaluates the time-varying (in)direct effects in a longitudinal study in the presence of exposure-induced time-varying confounding of a mediator-outcome pathway. A zero-inflated count outcome scenario with a binary exposure, a binary mediator, and a time-varying binary confounder of the mediator-outcome pathway was examined. Four types of path-specific causal estimands are identifiable for this scenario, and the findings suggest good performance of the proposed analytical approach in producing accurate effect estimates. Chapter 5 uses the Wisconsin Smokers Health Study II data to assess the mechanisms via which pharmacological smoking cessation treatments affect the cessation-related outcome(s) in the presence of time-varying confounding that is not exposure induced. We found that individuals randomized to Nicotine Patch only group have better smoking cessation outcome(s) compared to individuals on Varenicline or combination Nicotine Replacement Therapy. This is due to better adherence among Nicotine Patch-only users. Finally, Chapter 6 presents the concluding remarks, including key findings from the three studies, limitations, and recommendations for future research. / Epidemiology