Hi all!
I have estimated a mi estimate: heckprob model, but are having trouble understanding how to obtain lambda and its corresponding p-value when I am dealing with multiple imputed data. My code and results are as follows:
If anyone could help me understand how to calculate the value for lambda based on these values, it would be greatly appreciated!
I have estimated a mi estimate: heckprob model, but are having trouble understanding how to obtain lambda and its corresponding p-value when I am dealing with multiple imputed data. My code and results are as follows:
Code:
mi estimate, cmdok post: heckprobit nonviolent_success lagfpe, select(nonongoing=lagfpe lagelection) vce(cluster country_name)
Multiple-imputation estimates Imputations = 10
Probit model with sample selection Number of obs = 11,973
Average RVI = 0.0528
Largest FMI = 0.1634
DF: min = 357.09
avg = 108,875.71
DF adjustment: Large sample max = 227,928.36
F( 1, .) = .
Within VCE type: Robust Prob > F = .
(Within VCE adjusted for 195 clusters in country_name)
------------------------------------------------------------------------------------
| Coefficient Std. err. t P>|t| [95% conf. interval]
-------------------+----------------------------------------------------------------
nonviolent_success |
lagfpe | .1464942 .2132728 0.69 0.492 -.2715179 .5645063
_cons | 1.737143 .1213538 14.31 0.000 1.499293 1.974994
-------------------+----------------------------------------------------------------
nonongoing |
lagfpe | -.0270054 .1966883 -0.14 0.891 -.4125111 .3585003
lagelection | .0274804 .0234866 1.17 0.242 -.0185544 .0735152
_cons | -1.713432 .1140081 -15.03 0.000 -1.936885 -1.489979
-------------------+----------------------------------------------------------------
/athrho | -5.718097 1.487884 -3.84 0.000 -8.644214 -2.791981
-------------------+----------------------------------------------------------------
rho | -.9999784 .0000643 -.9999999 -.9925128
------------------------------------------------------------------------------------
