a simple question about sample size is: how large a sample is needed to get a 95% confidence interval no longer than 2d for the [unknown] mean of the data distribution. another variant is: how large a sample is needed to have power 0.9 at $\theta = 1$ when testing H$_0: \theta = 0$. you don't seem to specify any criterion for choosing a sample size.

actually, it sounds as tho your study will be conducted in a sequential fashion. in that case, it may pay to make that an explicit part of the experiment. sequential sampling can often be more efficient than a fixed sample-size experiment [fewer observations needed, on average].

farrel: i'm adding this in reply to your comment.

to get at a sample size, one usually specifies some sort of precision criterion for an estimate [such as length of a CI] OR power at a specified alternative of a test to be carried out on the data. you seem to have mentioned both of these criteria. there is nothing wrong with that, in principle: you just have to then do two sample size calculations - one to achieve the desired estimation precision - and another to get the desired power at the stated alternative. then the larger of the two sample sizes is what is required. [btw - other than saying 80% power - you don't seem to have mentioned what test you plan to perform - or the alternative at which you want the 80% power.]

as for using sequential analysis: if subjects are enrolled in the study all at the same time, then a fixed sample size makes sense. but if the subjects are few and far between, it may take a year or two [or more] to get the required number enrolled. thus the trial could go on for three or four years [or more]. in that case, a sequential scheme offers the possibility of stopping sooner than that - if the effect[s] you are looking for become statistically significant earlier in the trial.