Thanks for the comments and suggestions. Some of my terminology was not the best. The use of the work survival and infected is miss leading. A lab populates the medium with viable spores. The focus is viable spores on the medium and specifically the probability of viable spores on the medium. Let me see clarify what we are doing. This is a sanitation study. The two mediums are steel washers and a square piece of wool. So no spores would live on the medium if they sprouted. The treatments are to sanitize. The spore counts are viable spores. We want to know how effective the treatments are at cleaning up the spores. The initial counts on the wool averaged 2.2 million, the steel washer averaged 8500. Knowing the probability of a viable spore on the medium after treatment is valuable. The counts are integers. They are not continuous. I have used GLM with the Pioson distribution as Mark suggested. I find significance but not as much as with the binomial. The probability of a viable spore on the medium is of interest and the treatments that significantly affect it. Is the binomial telling me this? A low probability of a viable spore tell us there is a low likelihood of spreading viable spores. If the binomial is not the correct approach could the GLM Pioson treatment estimates be divided by the initial spore estimates to produce the probability of a viable spore on the medium. Would this be a better way to estimate this probability? Or do you have another approach to suggest. Thanks.
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