Creating a PP plot from a linear regression model with sampling weights

[Humphrey Mulenga]

I have a dataset that has sampling weights. I have fitted a multivariable linear regression model and i would like to check if the residuals are normally distributed. the pnorm command in stata doesn't take either probability or frequency weights. How can I create a custom pp plot like the one produced by the 'pnorm' command that will accommodate either probability or frequent weights. How can I get the observed and expected probabilities so that I can try and plot them using the scatter command. I converted my sampling weights to frequency weights because some commands like "histogram" only take frequency weights. My weighted histogram looks pretty normal but the pp plot shows deviation which I suspect is because of not applying weights. Below is my code and sample dataset

regress lgtcorscore corall rhino influenzall prevcase [pw=pweighting] if enrolled==1
predict res, residuals // Predict the residuals
histogram res [fw=fweighting3], normal title("A. Distribution of residuals") graphregion(color(white)) bgcolor(white) // Overall - Normality of errors (residuals)
graph save Graph "C:\norm1.gph" , replace
pnorm res, title("B. P-P plot") ytitle(Observed Probabilities) xtitle(Expected Probabilities) graphregion(color(white)) bgcolor(white)
graph save Graph "C:\norm2.gph" , replace
graph combine C:\norm1.gph C:\norm2.gph , ysize(1) xsize(2) iscale(*.8) row(1)
graph save Graph "C:\normAll.gph", replace

* Example generated by -dataex-. For more info, type help dataex
clear
input float(lgtcorscore corall rhino influenzall) byte prevcase float(pweighting    fweighting3)
2.995732 0 0 0 1 1.263 10
2.456736 0 0 0 1 1.263 10
4.0386543 0 0 0 1 1.263 10
.5409555 0 0 0 1 1.263 10
-.5223864 0 0 0 1  7.92 63
.4643055 0 0 0 1 1.263 10
1.7917595 0 0 0 1 1.263 10
4.3307376 0 0 0 1 1.263 10
3.6243405 0 0 0 1 1.263 10
-2.154665 0 0 0 1  7.92 63
-2.6936615 0 0 0 1  7.92 63
1.0928487 0 0 0 0 1.263 10
-2.904165 0 0 0 0  7.92 63
-.9162908 0 0 0 0  7.92 63
1.3638216 0 0 0 0 1.263 10
5.438088 1 0 0 0 1.263 10
.7323679 0 1 0 0 1.263 10
3.811095 0 1 0 0 1.263 10
-2.995732 0 0 0 0  7.92 63
-.1997962 0 1 0 0  7.92 63
-.11267325 0 1 0 0  7.92 63
2.995732 0 0 0 0 1.263 10
-2.904165 0 1 0 0  7.92 63
4.3307376 0 1 0 0 1.263 10
-1.1667502 0 1 0 0  7.92 63
.26157087 1 0 0 0  7.92 63
-1.261131 1 0 0 0  7.92 63
1.9409716 1 0 0 0 1.263 10
-1.2114916 0 0 0 0  7.92 63
1.9661127 0 0 1 0 1.263 10
2.904165 0 1 0 0 1.263 10
-1.2697606 1 0 0 0  7.92 63
1.1394342 0 1 0 0 1.263 10
1.2361418 0 0 0 0 1.263 10
2.904165 0 1 0 0 1.263 10
2.995732 1 0 0 0 1.263 10
1.475242 0 1 0 0 1.263 10
-2.74084 0 1 0 0  7.92 63
2.995732 0 1 0 0 1.263 10
3.465735 1 0 0 0 1.263 10
-.9591107 0 1 0 0  7.92 63
-2.47092 0 1 0 0  7.92 63
3.3277304 0 1 0 0 1.263 10
2.3561258 0 1 0 0 1.263 10
.9376007 1 0 0 0 1.263 10
-1.446919 1 0 0 0  7.92 63
2.3561258 0 1 0 0 1.263 10
2.2637453 0 0 1 0 1.263 10
-1.069957 0 1 0 0  7.92 63
1.981001 0 1 0 0 1.263 10
2.819545 1 0 0 0 1.263 10
.991367 0 0 0 0 1.263 10
-1.940972 0 0 0 0  7.92 63
4.3307376 0 0 0 0 1.263 10
-3.32773 0 0 0 0  7.92 63
-3.1593616 0 0 0 0  7.92 63
2.819545 0 0 0 0 1.263 10
1.5040773 0 0 0 0 1.263 10
-1.6894807 0 0 0 0  7.92 63
-1.7227665 0 0 0 0  7.92 63
.4685658 0 0 0 0 1.263 10
-1.7917595 0 0 0 0  7.92 63
2.3561258 0 0 0 0 1.263 10
1.827569 0 0 0 0 1.263 10
-2.1453996 0 0 0 0  7.92 63
1.286474 0 0 0 0 1.263 10
-2.667228 0 0 0 0  7.92 63
-2.819546 0 0 0 0  7.92 63
-2.9285235 0 0 0 0  7.92 63
-1.3121864 0 0 0 0  7.92 63
2.751535 0 0 0 0 1.263 10
2.5980496 0 0 0 0 1.263 10
3.160035 0 0 0 0 1.263 10
-1.563394 0 0 0 0  7.92 63
-1.375121 0 0 0 0  7.92 63
-2.3561258 0 0 0 0  7.92 63
-2.10515 0 0 0 0  7.92 63
-3.465736 0 0 0 0  7.92 63
3.095578 0 0 0 0 1.263 10
-2.412147 0 0 0 0  7.92 63
.7126917 0 0 0 0 1.263 10
2.3025846 0 0 0 0 1.263 10
-2.412147 0 0 0 0  7.92 63
-1.625104 0 0 0 0  7.92 63
-2.532763 0 0 0 0  7.92 63
-2.819546 0 0 0 0  7.92 63
-.3053816 0 0 0 0  7.92 63
-2.397895 0 0 0 0  7.92 63
4.7405767 0 0 0 0 1.263 10
-.3766861 0 0 0 0  7.92 63
-2.412147 0 0 0 0  7.92 63
-2.758061 0 0 0 0  7.92 63
-2.3025851 0 0 0 0  7.92 63
-1.430746 0 0 0 0  7.92 63
3.811095 0 0 0 0 1.263 10
-2.434645 0 0 0 0  7.92 63
-1.261131 0 0 0 0  7.92 63
-.09962995 0 0 0 0  7.92 63
1.267235 0 0 0 0 1.263 10
-1.3121864 0 0 0 0  7.92 63
end
label values influenzall pstatus
label values rhino pstatus
label values corall pstatus
label def pstatus 0 "negative", modify
label def pstatus 1 "positive", modify
label values prevcase casetype
label def casetype 0 "No", modify
label def casetype 1 "Yes", modify

Thanks
Humphrey