Hi Markus M, Thanks for your input. But one thing is still confusing me. From what I understood, the multiple comparison problem would arise if I calculated one p-value for all the regressions in a computational region. Say I have a 100 x 100 raster, chances are one of those 10,000 pixels would yield me a significant regression. But in my case, I'm calculating a p-value raster that is, each pixel has it's own p-value and I'm interested in the slopes that have a significant trend (p <= 0.05). Thus each pixel regression is (sort of) independent.
In essence. If I generate a raster with regression slope and p-value, and I mask out the areas with high p (above 5%), the slope values in the remaining regions would be significant correct? What you are saying is that I might be overestimating the area with significant slope? Cheers and thanks Daniel On Wed, Oct 18, 2017 at 6:06 PM Markus Metz <[email protected]> wrote: > > > On Wed, Oct 18, 2017 at 7:19 PM, Daniel Victoria < > [email protected]> wrote: > > > > I just read on the p-value regression ticket a comment from Markus Metz > [1]. If I understood correctly, he mentions that the chances of getting > small p-values at random is high and we should do a correction. But this > would result in non-significant p-values. He concludes that it would be > more "appropriate to make prior assumptions about slope, intercept, and > effect size, then judge the results according to these prior assumptions". > > > > Does this means that I should not rely on the p-value obtained? > > Yes and no. The p-value needs to be interpreted correctly. Commonly used > thresholds are alpha = 0.05 and alpha = 0.01. That means if p <= alpha, the > result is statistically significant. Problems occur if you repeat the test > with the same dataset several times: > https://en.wikipedia.org/wiki/Multiple_comparisons_problem > > In these cases, alpha needs to be corrected in order to decide if a > p-value is significant or not. Regarding r.series, millions of repeated > tests might be performed (one for each cell in the current computational > region). Any standard correction method would thus render pretty much all > p-values non-significant. Instead, Bayesian statistics might be a solution. > > Markus M > > > > > Where can I find more information about this? Some colleagues and I are > in the process of finishing a paper that uses applies a regression to > annual NDVI data and right now, we are discussing if we should (or not) > consider the p-values obtained. > > > > Thanks and sorry if this is a bit of topic > > > > Cheers > > Daniel > > > > [1] https://trac.osgeo.org/grass/ticket/2376#comment:3 > > > > > > On Mon, Oct 16, 2017 at 2:12 PM Daniel Victoria < > [email protected]> wrote: > >> > >> Replying to self and in case helps anyone. > >> > >> Solved it by using R and the raster package. Here is a Stackoverflow > post about it > >> > >> > https://stackoverflow.com/questions/20262999/how-to-output-regression-summarye-g-p-value-and-coeff-into-a-rasterbrick > >> > >> Cheers > >> Daniel > >> > >> On Wed, Oct 11, 2017 at 10:44 AM Daniel Victoria < > [email protected]> wrote: > >>> > >>> OK, dumb question since I'm a bit (or very) bad at stats. > >>> > >>> I'm calculating the slope from a series of rasters using r.series. I > see that I can also get the t-value and the coefficient of determination. > Is there a way to get the p-value for the regression? > >>> > >>> I've seen that this question has been asked before (in 2012) [1] and > it ended with the addition of the t-value calculation in r.series. But I > failed to see how the p-value can be obtained. > >>> > >>> I also found this ticket [2], related to the p-value question. > >>> > >>> Thanks > >>> Daniel > >>> > >>> [1] - > http://osgeo-org.1560.x6.nabble.com/Calculate-p-value-for-regression-slope-in-r-series-td5014228.html > >>> > >>> [2] https://trac.osgeo.org/grass/ticket/2376 > >>> > > > > _______________________________________________ > > grass-user mailing list > > [email protected] > > https://lists.osgeo.org/mailman/listinfo/grass-user > >
_______________________________________________ grass-user mailing list [email protected] https://lists.osgeo.org/mailman/listinfo/grass-user
