The innovative time series methodology that is presented was used to examine the relationship between the safety impact of longitudinal pavement markings and their retroreflectivity. The need for the methodology was determined through an examination of the pavement marking safety literature, the desire to build on previous retroreflectivity research, and an understanding of how retroreflectivity is a function of the age of pavement markings and markers. The time series methodology involves solving for multipliers that represent the change in the expected number of crashes as a function of pavement marking retroreflectivity while simultaneously solving for seasonal effect multipliers. The time series methodology is explained in detail; its usefulness has been demonstrated through the analysis of 8 years of pavement marking and marker installation data, traffic volumes, and crash data. Safety effect multipliers were solved for yellow and white pavement markings separately and in combination. The multipliers covered different road types and crash severities by using retroreflectivity models and California's data for more than 118,000 nonintersection, nondaylight (night, dawn, and dusk) recorded crashes. To apply the time series methodology, it was necessary to develop retroreflectivity models as a function of age, color, marking material type or marker type, climate region, and amount of snow removal. The results showed that retroreflectivity levels have no effect to a small effect on the safety performance of those roadways maintained to a reasonable level of pavement marking.