help blogit_2P

clear
insheet using mwf.raw, comma
sort d z x

// compute expected Phase One numbers from fixed Phase Two numbers and 
// expected proportions

gen NN=nij/tau_ij
qui summ NN if d==0
scalar N0=r(max)
qui summ NN if d==1
scalar N1=r(max)
drop NN
gen Nij=N0*tau_ij if d==0
replace Nij=N1*tau_ij if d==1

// compute expected numbers by detailed exposure in Phase Two
gen nijk=nij*pi_ijk

list, noobs sepby(d)

// fit ML estimate for the logistic regression of 2 phase data
//       using expected Phase One (Nij) and Phase Two (nijk) data

blogit_2P d z Nij nijk x,design method(ML)

// extract the (expected) coefficient and variance/covariance matrix
mat b=e(b)
mat cov=e(V)
// extract the expected coefficient (exp(.6931474)=2) and its standard error for x 
scalar betaX=b[1,1]
display "betaX=" %9.7f betaX
scalar se_betaX=sqrt(cov[1,1])
display "standard error(betaX)=" %9.7f se_betaX
// compute the power for a bilateral Wald test at the 5% level 
scalar power=100*normal(betaX/se_betaX-1.96)
di "Power=" %4.1f power "%"