The major transit systems operating in San Francisco are San Francisco Municipal (MUNI), Bay Area Rapid Transit (BART), and Caltrain. The system of interest for this paper is MUNI, in particular the bus and light rail systems. During the past decade transit ridership in the area has experienced diverging growth, with bus ridership declining while rail ridership is growing significantly (Erhardt et al. 2017). Our data show that between 2009 and 2016, MUNI rail ridership increases from 146,000 to 171,400, while MUNI bus ridership decreases from 520,000 to 450,000. Direct ridership models (DRMs) are used to determine what factors are influencing MUNI light rail and bus ridership. The DRMs predict ridership fairly well, within 10% of the observed change. However, the assumption of no multi-collinearity is voided. Variables, such as employment and housing density, are found to be collinear. Fixed-effects panel models are used to combat the multi-collinearity issue. Fixed-effects panel models assign an intercept to every stop, so that any spatial correlation is removed. A transportation network company, Uber and Lyft, variable is introduced (TNC) to the panel models, to quantify the effect they have on MUNI bus and light rail ridership. The addition of a TNC variable and elimination of multi-collinearity helps the panel models predict ridership better than the daily and time-of-day DRMs, both within 5% of the observed change. TNCs are found to complement MUNI light rail and compete with MUNI buses. TNCs contributed to a 7% growth in light rail ridership and a 10% decline in bus ridership. These findings suggest that the relationship TNCs have with transit is complex and that the modes cannot be lumped together.