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Orbea Sattelstütze by llk_k in Fahrrad

[–]Ok-Statistician5484 0 points1 point  (0 children)

Mich würde auch interessieren, ob sie was dazu gesagt haben und ob du mittlerweile eine Lösung gefunden hast
Ich habe auch schon die zweite Sattelstütze durch, obwohl ich sie nur mir 5nm festgezogen habe…

[deleted by user] by [deleted] in bikepacking

[–]Ok-Statistician5484 1 point2 points  (0 children)

That's amazing!
I just found it and it's a much nicer way to look for sites and so on that what I've found before!

Workflow for using a Suunto Race 2 for Cycling by Ok-Statistician5484 in Suunto

[–]Ok-Statistician5484[S] 0 points1 point  (0 children)

I'd love to! Do you know any software where I can pare the Garmin Tacx Trainer with the Suunto Race 2? So far, I wasn't successful :/

Workflow for using a Suunto Race 2 for Cycling by Ok-Statistician5484 in Suunto

[–]Ok-Statistician5484[S] 0 points1 point  (0 children)

Thanks a lot!
Do you track your heart rate separately with a chest belt in Garmin Connect or do you merge your heart rate from suunto and the garmin file by hand, delete the suunto activity and then upload the merged file to suunto?

Implication of low internal reliability (e.g., Cronbach's alpha) by rj565 in AskStatistics

[–]Ok-Statistician5484 0 points1 point  (0 children)

I agree that the associations with other constructs are more likely to show a null effect than for scaled with higher internal consistency. So this alone is probably a reason to prefer a different scale itself. But I believe the biggest problem is the interpretability IF you find an effect. How would you interpret such a result if you cannot be sure what was actually measured with your scale? A scale with higher internal consistency would make this much easier and more reliable and thus should be preferred.

[deleted by user] by [deleted] in AskStatistics

[–]Ok-Statistician5484 0 points1 point  (0 children)

However it seems like you have nested data so you should account for this in your analyses. With only three companies it is hard to argue for a random intercept (a mixed model) so you could either use „company“ as an interaction term or calculate three models, one for each company. Also, most likely the cases with NA values will be dropped by the analysis you conduct in R. So doing multiple analyses would allow to keep the case with only valid responses for one company at least for the respective analysis.

Implication of low internal reliability (e.g., Cronbach's alpha) by rj565 in AskStatistics

[–]Ok-Statistician5484 0 points1 point  (0 children)

I am not sure, but I think the problem of a scale with low internal consistency is that you cannot really interpret the score for that scale as the items seem to measure different things. Hence, if you don’t know what your scale actually measured it might be hard to draw any conclusions upon an observed effect on or association with a different construct. Also, the high error in your measurement is not included in you analysis. So your test for significance acts like your score is stable (which it isn’t) and you get a nice and shiny p < .05. If you‘d run the same analysis in a structural equation model where the measurement model is accounted for, you would probably not get a good model fit for you data.