We used Bland Altman plots to compare agreement between a self-report diary and five different non-wear time algorithms [an algorithm that uses ≥60 min of consecutive zeroes (Troiano) and four variations of an algorithm that uses ≥90 min of consecutive zeroes to define a non-wear period] for estimating community-dwelling older adults' (n = 106) sedentary behaviour and wear time (min/day) as measured by accelerometry. We found that the Troiano algorithm may overestimate sedentary behaviour and wear time by ≥30 min/day. Algorithms that use ≥90 min of continuous zeroes more closely approximate participants' sedentary behaviour and wear time. Across the self-report diary vs. ≥90 min algorithm comparisons, mean differences ranged between -4.4 to 8.1 min/day for estimates of sedentary behaviour and between -10.8 to 1.0 min/day for estimates of wear time; all 95% confidence intervals for mean differences crossed zero. We also found that 95% limits of agreement were wide for all comparisons, highlighting the large variation in estimates of sedentary behaviour and wear time. Given the importance of reducing sedentary behaviour and encouraging physical activity for older adult health, we conclude that it is critical to establish accurate approaches for measurement.