A　variable　selection　procedure　is　proposed　using　smooth-threshold　generalized　estimating　equations　based　on　quadratic　inference　functions　(SGEE-QIF).　The　proposed　procedure　automatically　eliminates　inactive　predictors　by　setting　the　corresponding　parameters　to　be　zero,　and　simultaneously　estimates　the　nonzero　regression　coefficients　by　solving　the　SGEE-QIF.　The　proposed　procedure　avoids　the　convex　optimization　problem　and　is　flexible　and　easy　to　implement.　We　establish　the　consistency　and　asymptotic　normality　of　the　resulting　estimators.　Extensive　Monte　Carlo　simulation　studies　are　conducted　to　examine　the　finite　sample　performance　of　the　proposed　variable　selection　procedure.