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Same data but different results when using `drm()` on different OSs
Hi there,
I'd like to highlight some differences that I found when running the drm() function on my Mac (Processor 2.6 GHz 6-Core Intel Core i7) vs an Amazon Linux machine.
I attached the example dataset input_data.txt.
Example:
input_data = read.table(file.path(here(), "tests/test-data/input_data.txt"))
drm(response ~ dose, data = input_data, fct = L.4())
Results from my Mac
Model fitted: Logistic (ED50 as parameter) (4 parms)
Parameter estimates:
Estimate Std. Error t-value p-value
b:(Intercept) -2.3306e-01 7.0496e-01 -0.3306 0.7434100
c:(Intercept) 4.4357e+05 1.3346e+05 3.3236 0.0024854 **
d:(Intercept) 1.3001e+06 3.2732e+05 3.9720 0.0004529 ***
e:(Intercept) 5.2777e+01 1.2060e+01 4.3763 0.0001521 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error:
654792.8 (28 degrees of freedom)
When running on an Amazon Linux machine:
Model fitted: Logistic (ED50 as parameter) (4 parms)
--
|
| Parameter estimates:
|
| Estimate Std. Error t-value p-value
| b:(Intercept) -2.3552e-01 7.2686e-01 -0.3240 0.7483338
| c:(Intercept) 4.4373e+05 1.3397e+05 3.3122 0.0025592 **
| d:(Intercept) 1.2999e+06 3.2735e+05 3.9711 0.0004540 ***
| e:(Intercept) 5.2747e+01 1.2068e+01 4.3709 0.0001543 ***
| ---
| Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
|
| Residual standard error:
|
| 654788.4 (28 degrees of freedom)
All the estimates are slightly but I believe not negligibly different.
Do you have any insights into how I can improve the reproducibility of the results?
Thanks for all your work and your help,
Anna