From Deepthi.Kolady at sdstate.edu Fri Sep 10 01:53:59 2021 From: Deepthi.Kolady at sdstate.edu (Kolady, Deepthi) Date: Thu, 9 Sep 2021 15:53:59 +0000 Subject: [Limdep Nlogit List] interpreting Poe test result Message-ID: Hello All, I have a discrete choice experiment model where I estimate marginal willingness to pay (mWTP) using WTP space model. I have included an attribute on whether the livestock is raised using conventional production method ot not. I have a control and information treatment for the survey. My objective is to test whether the mWTP for conventional control sample is statistically different from mWTP for conventional treatment. I ran the following code for Poe Test where vector 1=CONV (conventional control) and Vector 2=CONVT(conventional treatment). I am new to NLOGIT and has not used Poe test before. I have used the code below after reading through many papers. Can somebody confirm whether the code is correct? I got the result for Poe test using the code, but I am not sure how to interpret the results. I do not see any p Values to see whether we accept or reject the null hypothesis. |-> IMPORT;FILE="C:\Users\mariam.ishaq\OneDrive - South Dakota State University - SDSU\Desktop\Mariam Ishaq\Consumer behavior for sustaianable beef\Pork data\Porkdata for Poe test in N logitCSV.csv"$ Last observation read from data file was 328 |-> crea ; x=CONV ; y = CONVT $ |-> calc ; m = 328 ; l = 328 ; ixy=0 ; nd0 = 0 $ |-> matrix ; ones = init(m,1,1)$ |-> matr ; my = y $ |-> crea ; vd = 0 $ |-> sample ; 1 - m $ |-> proc $ |-> calc ; ixy=ixy+1 ; xi = x(ixy) $ |-> matrix ; md = xi*ones - my $ |-> crea ; vd = md $ |-> crea ; vd = vd < 0 $ |-> calc ; nd0 = nd0 + sum(vd) $ |-> endproc |-> exec;n=m$ |-> calc; list ; h0= nd0 / (m*l)$ Maximum repetitions of PROC ************************************************************************************* The output I got from the code above was |-> calc; list ; h0= nd0 / (m*l)$ [CALC] H0 = .3534262 |-> calc; list ; Log_prob = 1 - h0 $ [CALC] LOG_PROB= .6465738 |-> |-----------> ?Kr_Prob is essentially the p-value Thanks, Deepthi Sent from Mail for Windows