Simple Logistic Regression

#1
Five different doses of insecticide were applied under standardized conditions to an insect species. The data are as followed:

Dose (mg/l): 2.6 3.8 5.1 7.7 10.2
Number of insects: 60 60 59 57 60
Number killed: 7 16 20 48 54

I was asked to build a logistic regression model which says the logit of the chance of death changes linearly with the natural logarithm of dose.

I did this in SAS.

I'm asked to give a 95% Likelihood Ratio Confidence Interval for B. Further, translate this interval into an interval for the effect on the odds of death of increasing the dose by 50% (i.e, multiplying the dose factor by 1.5) and interpret. Hint: First translate the multiplying dose factor to the natural log scale.

I'm not sure how to do this, I've attached the appropriate SAS output I think I need to do the question with. I'm thinking take the B estimate (logc in the output is my B estimate) and exponentiate it, then times that value by 1.5. If thats right, what do i do next? same thing to the end points of the confidence interval associated with B?

Please advise!

Thx
 
#2
This is ahead of what I've learned so far, but partially as my trying to help you and partially as my trying to learn myself, here's my stab at it.

I can't figure out what your SAS output means, as I'm getting different numbers. Using a Log regression of ln(Dose) to %Killed, I get %Killed=.0298*4.6535^(ln(Dose)), with a .9645 r^2 and a .1856 standard error.

Using a Linear regression of ln(Dose) to logit(%Killed), I get logit(%Killed)=-5.367+3.26*ln(Dose), with a .956 r^2 and a .4382 standard error.

I'm also not sure what B means. If it's beta coefficient of a standardized regression, I've got .97922 +/- 1.96*.2413. If it's the unstandardized slope, it's 3.26 +/- 1.96*.438205.

So basically, if you increase a dose by 50%, here's how it would play into the Linear regression formula two paragraphs above:

(1) logit(%Killed)=-5.367+3.26*Ln(Dose)

(2) %Killed=exp(-5.367+3.26*Ln(Dose))/(1+exp(-5.367+3.26*Ln(Dose))

(3) x*%Killed=exp(-5.367+3.26*Ln(1.5*Dose))/(1+exp(-5.367+3.26*Ln(1.5*Dose))

(4) x*%Killed=exp(-5.367+1.3218+3.26*Ln(Dose))/(1+exp(-5.367+1.3218+3.26*Ln(Dose))

(5) x=(exp(-5.367+1.3218+3.26*Ln(Dose))/(1+exp(-5.367+1.3218+3.26*Ln(Dose)))/(exp(-5.367+3.26*Ln(Dose))/(1+exp(-5.367+3.26*Ln(Dose)))

And that's where I can't go further, so breaking that down is up to you haha. Hope something there helps/makes sense?