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Abstract Background Observational longitudinal data often feature irregular, informative visit times. We propose descriptive measures to quantify the extent of irregularity to select an appropriate analytic outcome approach. Methods We divided the study period into bins and calculated the mean proportions of individuals with 0, 1, and > 1 visits per bin. Perfect repeated measures features everyone with 1 visit per bin. Missingness leads to individuals with 0 visits per bin while irregularity leads to individuals with > 1 visit per bin. We applied these methods to: 1) the TARGet Kids! study, which invites participation at ages 2, 4, 6, 9, 12, 15, 18, 24 months, and 2) the childhood-onset Systemic Lupus Erythematosus (cSLE) study which recommended at least 1 visit every 6 months. Results The mean proportions of 0 and > 1 visits per bin were above 0.67 and below 0.03 respectively in the TARGet Kids! study, suggesting repeated measures with missingness. For the cSLE study, bin widths of 6 months yielded mean proportions of 1 and > 1 visits per bin of 0.39, suggesting irregular visits. Conclusions Our methods describe the extent of irregularity and help distinguish between protocol-driven visits and irregular visits. This is an important step in choosing an analytic strategy for the outcome.