R中如何計算固定效應(yīng)截距

用R做面板分析，為何固定效應(yīng)模型(fixedeffect)沒有給出截距項的結(jié)果，而隨機效應(yīng)模型又給出截距項的結(jié)果。固定效應(yīng)：grun.fev-plm(inv?value+capital,data=Grunfeld,model="within")summary(grun.fe)Oneway(individual)effectWithinModelCall:plm(formula=inv?value+capital,data=Grunfeld,model="within")BalancedPanel:n=10,T=20,N=200Residuals:Min.1stQu.Median3rdQu.Max.-184.000-17.6000.56319.200251.000Coefficients:EstimateStd.Errort-valuePr(>ltl)value0.1101240.0118579.2879<2.2e-16***capital0.3100650.01735517.8666<2.2e-16***Signif.codes:0‘***'0.001‘**'0.01‘*'0.05‘.'0.1‘'1TotalSumofSquares:2244400ResidualSumofSquares:523480R-Squared:0.76676Adj.R-Squared:0.72075F-statistic:309.014on2and188DF,p-value:<2.22e-16隨機效應(yīng)：grun.rev-plm(inv?value+capital,data=Grunfeld,model="random")summary(grun.re)Oneway(individual)effectRandomEffectModel(Swamy-Arora'stransformation)Call:plm(formula=inv?value+capital,data=Grunfeld,model="random")BalancedPanel:n=10,T=20,N=200Effects:varstd.devshareidiosyncratic2784.4652.770.282individual7089.8084.200.718theta:0.8612Residuals:Min.1stQu.Median3rdQu.Max.-178.00-19.704.6919.50253.00Coefficients:EstimateStd.Errort-valuePr(>ltl)(Intercept)-57.83441528.898935-2.00130.04674*value0.1097810.01049310.4627<2e-16***capital0.3081130.01718017.9339<2e-16***Signif.codes:0‘***'0.001‘**'0.01‘*'0.05‘.'0.1‘'1TotalSumofSquares:2381400ResidualSumofSquares:548900R-Squared:0.7695Adj.R-Squared:0.75796F-statistic:328.837on2and197DF,p-value:<2.22e-16我用同樣的數(shù)據(jù)在Stata也跑了一遍，結(jié)果是一樣的，但Stata給出了固定效應(yīng)模型的截距項的結(jié)果。請問如何在R中得到截距項的結(jié)果。library(plm)data(Grunfeld)grun.fe1<-plm(inv~value+capital,data=Grunfeld,model="within",type="dmean")summary(fixef(grun.fe1,type="level"))EstimateStd.Errort-valuePr(>|t|)1-70.296749?7080-1.41420.157302101.905824.93834.08634.383e-05***3-235.571824.4316-9.6421<2.2e-16***4-27.809314.0778-1.97540.04822*5-114.616814.1654-8.09136.661e-16***6-23.161312.6687-1.82820.06752.7-66.553512.8430-5.18212.194e-07***8-57.545713.9931-4.11243.915e-05***9-87.222312.8919-6.76571.327e-11***10-6.567811.8269-0.55530.57867

Signif.codes:0‘***'0.001‘**'0.01‘*'0.05‘?'0.1‘'1>summary(fixef(grun.fe1,type="dmean"))EstimateStd?Errort-valuePr(>|t|)1-11.552849.7080-0.23240.8162172160.649824.93836.44191.180e-10***3--176.827924.4316-7.23774.565e-13***430.934614.07782.19740.027991*5-55.872914.1654-3.94438.003e-05***635.582612.66872.80870.004974**7-7.809512.8430-0.60810.54313681.198313.99310.08560.9317589-28.478312.8919-2.20900.027174*1052.176111.82694.4116