[GRASS-user] P value for slope from r.series

[Markus Metz]

On Wed, Oct 18, 2017 at 7:19 PM, Daniel Victoria <daniel.victoria at gmail.com>
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 <daniel.victoria at gmail.com>
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 <
daniel.victoria at gmail.com> 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
>>>
>
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