r - Logistic Regression in SAS -

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i have data below.

enter image description here

i wish apply logistic regression. here response variable proportion of dead. here how analyzed data in r:

dose <- c(1.6907, 1.7242, 1.7552, 1.7842,            1.8113, 1.8369, 1.8610,1.8839) total<- c(59,60,62,56,63,59,62,60) dead<- c(6,13,18,28,52,53,61,60) y <- dead/total  lineer.model <- glm(y ~ dose,family=binomial(link=logit), weights=total)

i want same analysis in sas. can please me that? here did in sas, thats not working. idea why

data beetle_data; input dose total dead; y = dead/total; datalines; 1.6907  59 6 1.7242  60 13 1.7552  62 18 1.7842  56 28 1.8113  63 52 1.8369  59 53 1.8610  62 61 1.8839  60 60 ;  proc logistic data=beetle_data; model y =dose/link=logit dist=binomial; run;

based on this sas document (google "sas proc logistic binomial") looks should it:

proc genmod data=beetle; model dead/total=dose / link=logit dist=binomial;

based on this looks data above same, standard bliss (1935) data set referred in link above.


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