Dear _all,
I am not sure what is going on here, but this does not
look correct. My conditional logistic regression fails
with a "Hessian has become unstable or asymmetric"
error message, however the return list and the
coefficient matrices are populated:
. use cdata.dta, clear
. mat drop _all
. eret clear
. cap noi mat list e(b)
matrix e(b) not found
. clogit case expose, group(race)
note: multiple positive outcomes within groups
encountered.
Iteration 0: log likelihood = -939.77277
Hessian has become unstable or asymmetric
r(504);
. mat list e(b)
e(b)[1,2]
expose _cons
y1 .04772761 .71262832
. eret list
scalars:
e(N) = 1514
e(ll_0) = -954.663128837389
e(ll) = -954.5735647746089
e(df_m) = 1
e(chi2) = .1791281255600552
e(r2_p) = .0000938174525386
e(N_cdf) = 0
e(N_cds) = 0
macros:
e(cmdline) : "logit __000002 expose if
__000001 , "
e(title) : "Logistic regression"
e(vce) : "oim"
e(depvar) : "__000002"
e(cmd) : "logit"
e(crittype) : "log likelihood"
e(predict) : "logit_p"
e(properties) : "b V"
e(estat_cmd) : "logit_estat"
e(chi2type) : "LR"
matrices:
e(b) : 1 x 2
e(V) : 2 x 2
e(rules) : 1 x 4
functions:
e(sample)
The hessian becoming unstable or asymmetric is also
strange. Race has 3 levels and >60 observations per
race.
Thank you,
Ricardo
Ricardo Ovaldia, MS
Statistician
Oklahoma City, OK
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