The　framework　for　performance-based　seismic　design　and　assessment　of　bridges　grapples　with　the　pressing　challenge　of　precisely　estimating　the　seismic　capacities　correlation　amongst　bridge　piers.　To　address　this　issue,　a　Bayesian　semiparametric　hierarchical　model　is　proposed　in　this　study　to　characterize　such　correlation.　This　model　was　applied　to　a　database　populated　with　multiple-column　tests　conducted　by　distinct　research　cohorts.　Given　that　each　group　performed　tests　under　analogous　conditions,　the　model　could　be　operationalized　on　the　database　to　derive　intraclass　correlation　coefficients　that　reflect　the　statistical　correlation　among　piers　tested　by　individual　research　groups.　It　is　postulated　that　these　coefficients　also　typify　the　capacity　correlation　across　multiple　bridge　piers　within　a　bridge　system.　After　a　thorough　examination　of　the　data　set,　particularly　focusing　on　the　nature　of　missing　values,　an　appropriate　multiple　imputation　technique　was　selected　to　address　the　missing　data,　aiming　to　approximate　the　most　accurate　intraclass　correlation.　The　analysis　revealed　that,　among　the　various　damage　limit　states,　the　correlation　coefficients　spanned　between　0.386　and　0.883.　This　suggests　that　the　seismic　capacity　of　bridge　piers　is　influenced　not　only　by　design　parameters　but　also　by　the　experimental　group.　Utilizing　independent　or　fully　correlated　relationships　between　capacities,　rather　than　true　correlation　coefficients,　can　lead　to　significant　deviations　in　the　fragility　curve,　which　increase　with　the　number　of　bridge　piers.　Such　observations　accentuate　the　necessity　of　integrating　authentic　pier　capacity　correlations　in　the　bridge　system　fragility　analysis.