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  • Teffects aipw

    Hi there,
    I am using teffects aipw but keep receiving errors and I would be very very grateful if someone can help me out. For convenience I wrote my questions in bold.

    This is the command I used:
    Code:
    teffects aipw (anxiety cancer geslacht herkomstgroep c.leeftijd sted dutch, poisson) (treatment c.leeftijd cancer bmi geslacht herkomstgroep sted, hetprobit(leeftijd)), wnls vce(cluster nomem_encr) osample(test1)
    - I chose poisson because anxiety is measured on a scale of 1-6 (Stata Guide says poisson should be used for counts or nonnegative outcomes).
    - I chose hetprobit because I don't think the error terms are homoskedastic (is there a way I can check this?)
    - I chose WNLS because this estimator may be more robust to outcome model misspecification than maximum likelihood.
    - I chose vce(cluster nomem_encr) because I have longitudinal data (nomem_encr is personal identifier).

    Then I receive this error:
    Code:
    treatment 1 has 174 propensity scores less than 1.00e-05
    treatment overlap assumption has been violated by observations identified in variable osample(test1)
    Can I just delete observations that violate the overlap assumption?

    If yes, this would be my next code:
    Code:
    drop if test1==1
    teffects aipw (anxiety cancer geslacht herkomstgroep c.leeftijd sted dutch, poisson) (treatment c.leeftijd cancer bmi geslacht herkomstgroep sted, hetprobit(leeftijd)), wnls vce(cluster nomem_encr)
    But then I receive this error:
    Code:
    Iteration 0:   EE criterion =  .05195572  (not concave)
    Iteration 1:   EE criterion =    -1.#IND  (backed up)
    Hessian is not positive semidefinite
    gmm estimation failed
    What does "Hessian is not positive semidefinite" mean?

    Is there a way I can make this gmm estimation work?

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