Literature doesnt have similar studies. So I am unable to use prior data.
You should look for critical effect size (see the papers by Dr. Kelly Munkittrick ) i.e. to define what differences in the biomarkers responses between a reference and an impacted site you are looking for, and then to define the sampling size considering the variability in the response of the reference site. We have done some work on that please see the paper by Chiang et al defining the correct sample size for biomarkers responses of fish in a river impacted by a pulp mill (Ecotoxicology and Environmental safety 86:147-155, 2012)
Hi
I think selecting a sample for any problem from any population has similar statistical principles and techniques:
Research studies are usually carried out on sample of subjects rather than whole populations. The most challenging aspect of fieldwork is drawing a random sample from the target population to which the results of the study would be generalized. The key to a good sample is that it has to be typical of the population from which it is drawn. When the information from a sample is not typical of that in the population in a systematic way, we say that error has occurred. In actual practice, the task is so difficult that several types of errors, i.e. sampling error, non-sampling error, Response error, Processing error,… In addition, the most important error is the Sampling error, which is statistically defined as the error caused by observing a sample instead of the whole population. The underlying principle that must be followed if we are to have any hope of making inferences from a sample to a population is that the sample be representative of that population. A key way of achieving this is through the use of “randomization”.
There several types of random samples, Some of which are: Simple Random Sampling, Stratified Random Sampling, Double-stage Random Sampling... Moreover, the most important sample is the simple random sample which is a sample selected in such a way that every possible sample of the same size is equally likely to be chosen. In order to reduce the sampling error, the simple random sample technique and a large sample size have to be developed.
Regards,
Zuhair
You should look for critical effect size (see the papers by Dr. Kelly Munkittrick ) i.e. to define what differences in the biomarkers responses between a reference and an impacted site you are looking for, and then to define the sampling size considering the variability in the response of the reference site. We have done some work on that please see the paper by Chiang et al defining the correct sample size for biomarkers responses of fish in a river impacted by a pulp mill (Ecotoxicology and Environmental safety 86:147-155, 2012)
Hi, I do not fully understand your question. Do you want to cluster known biomarkers? How many biomarkers would that be? Do you have prior knowledge or assumptions regarding those biomarkers in your study population?
10 to 12 known biomarkers. Each of them was studied separately before. If you plan a study to measure all of these biomarkers simultaneously in each patient with the goal of clustering patients into risk strata for death, how do you calculate a sample size to ensure adequate power?
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