**Hi Statalist,**

**I am running a cross classified model using runmlwin. Previously, I had used meqrlogit and then I used the following code to predict fixed and random effects and to graph them:**

Code:

predict v0*, reffectspredict v0se*, reffectspredict probAllpredict pfx, xbgen probPeriod = 1 /(1+exp(-1*(pfx + v01)))gen probPrL = probPeriod-1.96*v0se1gen probPrU = probPeriod+1.96*v0se1collapse (mean) probP = probPeriod (semean) probPs = probPeriod, by(Period)gen probPrL = probP-1.96*probPsgen probPrU = probP+1.96*probPstwoway (connected probP Period, mcolor(black) lcolor(black)) ///(connected probPrL Period, mcolor(black) lcolor(black) lpattern(dash)) ///(connected probPrU Period, mcolor(black) lcolor(black) lpattern(dash)), ///ytitle(Predicted probability with 95% confidence band) xtitle(Period) xlabel(#3) legend(off)

**In an attempt to predict and graph my results using runmlwin I tried the following code:**

Code:

runmlwin ID cons, level2(Period:cons, , residuals(v)) level1(Cohort: cons, residuals(u)) discrete(dist(binomial) link(logit) denom(denom)) mcmc(cc) initsprevious nopause

**which returns error: invalid â€™residualsâ€™**

**Would anyone be able to provide any insight into how to calculate this when using the runmlwin package? Thanks.**

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