This　study　aims　to　explore　the　variability　of　risk　factors　affecting　injury　severity　in　rear-end　crashes　when　different　struck　vehicle　groups　are　involved.　Two　types　of　rear-end　crash　data,　vehicle-strike-car　data,　vehicle-strike-truck　data,　are　extracted　from　the　Fatality　Analysis　Reporting　System　(FARS).　Two　likelihood　ratio　(LR)　tests　are　firstly　performed　to　validate　the　struck　vehicle　group　variations,　and　then　two　separate　random　thresholds　random　parameters　hierarchical　ordered　probit　(RRHOP)　models　(Model　1　and　Model　2)　are　established　to　capture　unobserved　heterogeneity.　The　results　of　LR　test　show　significant　differences　in　the　effects　of　factors　included　in　each　model.　Moreover,　the　model　results　suggest　that　SUVs,　vans,　and　large　trucks　as　striking　vehicles　are　significant　related　to　injury　severity　in　both　models　with　different　effects.　Factors　such　as　speeding　related,　pickup,　model　year　(struck　vehicle),　disabled　damage,　adverse　weather,　speed　limit　(＞=　60　mile/h),　and　young　driver　(struck　vehicle)　are　found　to　be　statistically　significant　in　only　model　1.　These　results　provide　a　better　understanding　of　differences　in　contributing　factors　of　rear-end　crashes,　which　help　to　propose　effective　countermeasures　to　mitigate　its　injury　severity.