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st: Interpreting dots in regression tables
Dear All,
Here is a sample of the output that I got for a random effects probit
model. Some other specifications yield good results. I wanted to know
the interpretation when coefficient value is printed, but values for
standard errors, Z and p are all printed as ".". For better output,
refer the attached txt file.
Thanks,
Prabhu
STATA Output:
++++++++++++++++++++++++++++++++++++++++++++++++
Fitting comparison model:
Iteration 0: log likelihood = -1127.9569
:
:
Iteration 4: log likelihood = -989.4746
Fitting full model:
rho = 0.0 log likelihood = -989.4746
:
rho = 0.8 log likelihood = -500.78809
Iteration 0: log likelihood = -532.11552
:
Iteration 8: log likelihood = -438.43288
Random-effects probit regression Number of obs = 1797
Group variable (i): srno Number of groups = 388
Random effects u_i ~ Gaussian Obs per group: min = 3
avg = 4.6
max = 10
Wald chi2(7) = .
Log likelihood = -438.43288 Prob > chi2 = .
yesno_h Coef. Std. Err. z P>z [95% Conf. Interval]
price -.0139144 .0013292 -10.47 0.000 -.0165195 -.0113093
eff .557588 . . . . .
prim_h -.7117068 . . . . .
sec_h .3701428 . . . . .
hisec_h .3932863 . . . . .
ageh .125057 . . . . .
agehsq -.0027808 .0001407 -19.76 0.000 -.0030566 -.0025051
spouseh -.0170838 .2274981 -0.08 0.940 -.4629719 .4288044
son .334153 .2197415 1.52 0.128 -.0965324 .7648385
daughter .1851827 .232607 0.80 0.426 -.2707187 .641084
dowry .6840383 . . . . .
placre1_h .0012098 .001105 1.09 0.274 -.0009559 .0033755
somerisk_h .7461116 . . . . .
largrisk_h -1.406053 .5931395 -2.37 0.018 -2.568585 -.2435213
_cons -1.557819 . . . . .
/lnsig2u 2.723256 .1212345 2.485641 2.960871
sigma_u 3.902541 .2365612 3.465373 4.394859
rho .938385 .0070096 .923129 .9507748
Likelihood-ratio test of rho=0: chibar2(01) = 1102.08 Prob >= chibar2 =
0.000
.
Attachment:
how2interpret.doc
Description: MS-Word document
