Large biases may occur in cognitive decline studies due to informative dropout, where participants with the worst cognitive decline also have more missing outcomes due to competing dementia/death/other events. Shared parameter models (SPM) jointly estimate longitudinal submodels with event submodels through a set of “shared parameters” (latent/random effects) to address this selection bias. We compare cerebrovascular infarct relationships with cognitive decline using SPM versus standard models in the Atherosclerosis Risk in Communities (ARIC) study. Infarct burden was assessed using 1.5T MRI in 1,835 stroke-free participants of the ARIC study (V3:1993–1995; mean age 62.8, range 51–73 years; 60% women) and categorized as no-burden (no infarct like lesions (ILL)<3mm nor any infarcts>3mm, n=1580), small-burden (ILL<3mm only, n=48), large-burden (infarcts≥3 mm only, n=174), and double-burden (co-existingILL<3mm plus infarcts≥3 mm (n=30)). Global cognition z-scores over 20 years were available in up to five visits; dementia and death events were available via cohort surveillance. Random-slope linear mixed models (LMM) estimated associations of infarct burden with 10-year cognitive decline under inherent missing at random (MAR) assumptions. SPM approaches used this LMM submodel alongside cause-specific Weibull survival submodels for dementia and death events, sharing the random intercepts and slopes between the longitudinal and event submodels under missing not at random (MNAR) assumptions. The double-burden group experienced triple the dementia (Cox-PHM HR=2.8, [1.5, 5.2]) and double the death rates (HR=2.3, [1.4, 3.7]) compared to the no-burden group. LMM gave 10-year cognitive change estimates for the double-burden group which were counterintuitively positive (change=+0.10 SD) and statistically supported as better (p<0.001) than the no-burden group (change= -0.32 SD). Conversely, SPM gave 10-year cognitive change estimates for the double-burden group which were modestly negative (change=-0.05 SD) and non-supported (p=0.220) as being different from the no-burden group (change=-0.34 SD). SPM estimates of informative relationships connecting the longitudinal (cognitive decline) submodel with the survival submodels (dementia and death) were highly supported (p<0.0001 for both). Including informative competing events such as dementia and deaths in studies of cognitive decline can improve estimates and understanding of the interplay between cognitive decline and cause-specific dropout mechanisms.