I am conducting a population genetic study on several species of fishes using microsatellite alleles. I have used BayesAss (http://www.rannala.org/software/) to estimate migration percentages to and from each population in my datasets for each species. Superficially, the outputs provided seem to be apparently correct and adhere to pre-conceived hypotheses. However, the output data do not provide me with p-values to indicate if the estimates are statistically significant. For each estimate (mean) the SD is provided in the output file, and after reading the generated Trace file (https://www.beast2.org/tracer-2/ ) several other outputs are calculated (SE, SD, variance, upper and lower 95% CIs) but no p-value. Could anyone help me either a) identify the p-value in the output that I am somehow missing? or b) calculate the p-value from the outputs provided? Unfortunately statistics aren't my strong suit so I feel like the answer might be obvious with the results I've been given but I can't figure it out from what I've looked up so far.
Thanks!
Hi,
first of: I assume you have decided on the "best" run using the trace files (viewed for example in the Tracer software) as well as a comparison of runs by their Bayesian Deviance (which is thankfully easily calculated with the R script provided by Meirmans (2013) himself (see article below).
If so, you can calculate the 95% confidence intervalls as alternative to a p-value (actually the concept of p-values is more and more under critical review lately), by multiplying the standard error with 1.96. You will find various good explanations online for this if you look for "calculate confidence intervall from standard error". Then, a common approach would be to interpret migration rates as significant if their 95% confidence intervall does not include zero.
Hope this helps,
Cheers
Article Nonconvergence in Bayesian estimation of migration rates
Edit: typesetting
Thanks Florian Kunz. That helps a lot. I hadn't considered just relying on the CIs, just been using p-values for everything up until this point. I agree that they often do need to be taken with grain of salt too.
I did decide on the best run using tracer, however I haven't compared them using that R script which sounds wise.
Thank you very much!
Calculate the z statistic, which is (x – μ) / (σ / √n). Or you could use the Chi squared statistic instead
Then choose significance level, usually 0.05
Decide if the test is one or two tailed
Then use tables or an online calculator to calculate the p value using the above information
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