Hi, all

I am trying to calculate z scores from p-values to get SEs using a logistic regression summary statistics data, a part of which is presented below.
SNP P P(R) OR OR(R) Q I
rs3094315 0.4913 0.4913 0.9420 0.9420 0.3873 0.00
rs12562034 0.9737 0.9737 1.0022 1.0022 0.5991 0.00
This is a meta-analysis data conducted by others.
P is p value and (R) indicates random effect models. Q is Q statistic and I I2 index to assess the heterogeneity of the data.

Since they did not provide SEs or 95% CIs in this summary statistics, I am using the following formulas to get SEs:
SE=beta/z=ln(OR)/invnormal(p)
beta=ln(OR)
z=invnormal(p)

Then, I got these results.
SNP β z z(R) SE SE(R)
rs3094315 -0.05975 -0.021809 -0.021809 2.739642 2.739642
rs12562034 0.0021976 1.938190 1.938190 0.001134 0.001134
I am wondering whether my calculation is correct or not, because the same calculations using a different data set, such as 1978 Automobile data, gave me completely different results.

Code:
logistic foreign price mpg rep78

Logistic regression                             Number of obs     =         69
                                                LR chi2(3)        =      34.08
                                                Prob > chi2       =     0.0000
Log likelihood = -25.362394                     Pseudo R2         =     0.4018

------------------------------------------------------------------------------
     foreign | Odds Ratio   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
       price |   1.000141   .0001379     1.03   0.305     .9998712    1.000412
         mpg |    1.18063   .0966693     2.03   0.043     1.005583    1.386148
       rep78 |   5.321595   2.656576     3.35   0.001     2.000398    14.15687
       _cons |   .0000112    .000032    -4.00   0.000     4.23e-08    .0029816
------------------------------------------------------------------------------
If I am wrong, could you point out what is wrong about my calculations, please?

I will really appreciate any help and comments.