Should the weights of a neural network without hidden layer and a logistic activation function be the same as the parameters of a logistic regression? Mine are not the same but roughly 5-7 times larger?

    nnallnohidden=nnet(
        PartialPrepayzo~FIXPER+MEDSAL2+DREL+LEEFTIJD+HH2CRED+LTV_curr+
        rate1Y+rate5Y+CIremFIRP+URB+WELSTAN2+OutNot+mover+SavRate+CRate,
        data=test,
        size=0,
        skip=T)

    log <- glm(PartialPrepayzo~FIXPER+MEDSAL2+DREL+
    LEEFTIJD+HH2CRED+LTV_curr+rate1Y+rate5Y+CIremFIRP+URB+WELSTAN2+OutNot+mover+SavRate+CRate, data = test, family = "binomial")
    summary(log)

                     [,1]           [,2]
     [1,] -1.029560622391 -9.56664018566
     [2,] -0.078225500455 -0.46536644222
     [3,]  0.410455341173  2.57036107254
     [4,]  0.006961510972 -0.11463794856
     [5,]  0.473629162069  2.70074482878
     [6,]  0.614550199698  2.83536187570
     [7,] -0.612837570442 -3.48086112696
     [8,] -0.743739495966 -5.26994471577
     [9,]  0.200419240204  1.83957097597
    [10,] -0.166568966328 -0.90583277715
    [11,]  0.017640270701  0.12678131085
    [12,] -0.005947704128 -0.04248886193
    [13,] -0.428175932694 -2.69521649738
    [14,]  0.049657239050  0.26482261363
    [15,]  1.602200661890 10.50479250068
    [16,]  0.367771764513  1.96127873663