In　this　paper,　we　consider　the　problem　of　variable　selection　for　varying　coefficient　partially　linear　models　with　longitudinal　data.　A　new　variable　selection　procedure　is　proposed　based　on　smooth-threshold　generalized　estimating　equation　(SGEE).　The　proposed　procedure　simultaneously　selects　significant　variables　in　the　parametric　components　and　the　nonparametric　components.　The　approach　avoids　the　convex　optimization　problem　and　is　flexible　and　easy　to　implement.　The　consistency　and　asymptotic　normality　of　the　resulting　estimators　are　established.　Extensive　Monte　Carlo　simulation　studies　are　conducted　to　examine　the　finite　sample　performance　of　the　proposed　variable　selection　procedure.　The　proposed　procedure　is　further　illustrated　by　an　application.　(C)　2015　The　Korean　Statistical　Society.　Published　by　Elsevier　B.V.　All　rights　reserved.