1. Deaths of snails vs exposure by species

2. Deaths of snails vs exposure by temperature

3. Deaths of snails vs exposure by relative humidity

4. SAS code for deaths of snails vs species, exposure temperature and relative humidity proc genmod data=linear.lab13_1; class species exposure temp rel_humidity; model deaths/total=species exposure temp rel_humidity/dist=binomial; run;  When each observation in the input data set contains the number of events (for example, successes) and the number of trials from a set of binomial trials, use the events/trials syntax.  This form is applicable only to summarized binomial response data.

5. SAS code for deaths of snails vs species, exposure temperature and relative humidity Analysis Of Parameter Estimates Standard Wald 95% Confidence Chi- Parameter DF Estimate Error Limits Square Pr > ChiSq Intercept 1 -0.3840 0.2224 -0.8199 0.0519 2.98 0.0842 Exposure 1 1 -26.6454 32246.14 -63227.9 63174.62 0.00 0.9993 Exposure 2 1 -3.1841 0.2990 -3.7702 -2.5979 113.37 <.0001 Exposure 3 1 -0.9451 0.1635 -1.2656 -0.6246 33.40 <.0001 Exposure 4 0 0.0000 0.0000 0.0000 0.0000.. Species A 1 -1.2895 0.1618 -1.6066 -0.9724 63.51 <.0001 Species B 0 0.0000 0.0000 0.0000 0.0000.. Temp 10 1 -0.9444 0.1942 -1.3250 -0.5638 23.65 <.0001 Temp 15 1 -0.3688 0.1798 -0.7212 -0.0163 4.21 0.0403 Temp 20 0 0.0000 0.0000 0.0000 0.0000.. Rel_humidity 60 1 1.5872 0.2290 1.1383 2.0361 48.03 <.0001 Rel_humidity 65.8 1 0.9732 0.2335 0.5155 1.4310 17.37 <.0001 Rel_humidity 70.5 1 0.3311 0.2464 -0.1518 0.8141 1.81 0.1790 Rel_humidity 75.8 0 0.0000 0.0000 0.0000 0.0000.. Scale 0 1.0000 0.0000 1.0000 1.0000

6. Interpretation of SAS output for the study of deaths among snails in relation to species, exposure, temperature and relative humidity.  The model parameters represent estimates of  The presence of interaction effects can be tested by computing

7. Survival probability vs age, sex and passenger class PClass_Sex_Rel. frequencyN1 1stfemale0.937063143 1stmale0.329609179 2ndfemale0.878505107 2ndmale0.144509173 3rdfemale0.377358212 3rdmale0.116232499 Missing values?

8. Relative frequency of myocardial infarction vs coffee and cigarrette consumption

9. Main effects? Interaction effects?

10. SAS code for the study of myocardial infarction vs coffee and cigarrette consumption proc genmod data=linear.lab14_1; class coffee cigarrettes; model cases/total = coffee cigarrettes/dist=binomial; run;  When each observation in the input data set contains the number of events (for example, successes) and the number of trials from a set of binomial trials, use the events/trials syntax.  This form is applicable only to summarized binomial response data.

11. SAS code for the study of myocardial infarction vs coffee and cigarrette consumption Quantitative inputs (scores) Qualitative inputs.

12. Rail accidents Observed data may be regarded as rates (number of accidents per mile)