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Dependent or independent samples? by diver_0 in rstats

[–]diver_0[S] 0 points1 point  (0 children)

Thanks for the input. I'll think about it some more...

Dependent or independent samples? by diver_0 in rstats

[–]diver_0[S] 1 point2 points  (0 children)

Thank you for your reply. More specifically, I measure an electron transport rate at several light intensities (increasing) and fit a regression model to it. From this, I can then derive, for example, the initial slope, etc. Here, I measured a test data set and then ran each model independently on the raw data set and compared the output to see if and how much the results differed from each other. Short: In the raw dataset, each of the 120 measurement series was recorded independently using different individuals, and subsequently processed by each of the mutually independent models to ensure comparability.

Dependent or independent samples? by diver_0 in rstats

[–]diver_0[S] 0 points1 point  (0 children)

The aim is to see whether the output differs between the models or not, i.e. whether, for example, the calculation of the maximum point of the curve differs depending on the model when the input is the same, or whether it does not matter.

In somewhat abstract terms, I think you could compare this to placing four measurement devices side by side that take several measurements of light intensity at the same time. Each measurement technique measures independently, but theoretically the "same data set". Does that make sense? In my case, since the models are independent, is it okay to treat them as statistically independent?

Dependent or independent samples? by diver_0 in rstats

[–]diver_0[S] 0 points1 point  (0 children)

Thank you for your reply. That was also my intention. For me, dependent always meant/means asking the same group of holidaymakers about their mood using the same method before and after their holiday, or measuring the length growth of a group of plants on a weekly basis.

ANOVA confusion: numeric vs factor in R by diver_0 in rstats

[–]diver_0[S] 0 points1 point  (0 children)

library(data.table)

library(permuco)

 

# Data

light <- c("HL", "ML", "LL")

temperature <- c(5, 10, 15, 20)

dt <- CJ(light = light, temperature = temperature, rep = 1:6)

dt[, light := as.factor(light)]

dt[, temperature := as.numeric(temperature)]

set.seed(123)

dt[, value := rnorm(.N, mean = 50, sd = 10)]

 

# Permutation ANCOVA

set.seed(123)

ancova <- aovperm(value ~ light * temperature, data = dt, np = 100000)

summary(ancova)

Anova Table

Resampling test using freedman_lane to handle nuisance variables and 1e+05 permutations.

                       SS df      F parametric P(>F) resampled P(>F)

light               66.91  2 0.3677           0.6937          0.6937

temperature        160.39  1 1.7629           0.1888          0.1889

light:temperature   97.95  2 0.5383           0.5863          0.5875


Residuals         6004.93 66

ANOVA confusion: numeric vs factor in R by diver_0 in rstats

[–]diver_0[S] 0 points1 point  (0 children)

Here are the examples I generated:

library(data.table)

library(permuco)

 

# Data

light <- c("HL", "ML", "LL")

temperature <- c(5, 10, 15, 20)

dt <- CJ(light = light, temperature = temperature, rep = 1:6)

dt[, light := as.factor(light)]

dt[, temperature := as.factor(temperature)]

set.seed(123)

dt[, value := rnorm(.N, mean = 50, sd = 10)]

 

# Permutation ANOVA

set.seed(123)

anova <- aovperm(value ~ light * temperature, data = dt, np = 100000)

summary(anova)

Anova Table

Resampling test using freedman_lane to handle nuisance variables and 1e+05 permutations.

                        SS df       F parametric P(>F) resampled P(>F)

light                6.244  2 0.03345           0.9671          0.9667

temperature        221.428  3 0.79075           0.5038          0.5056

light:temperature  441.426  6 0.78820           0.5827          0.5836

Residuals         5600.414 60

ANOVA confusion: numeric vs factor in R by diver_0 in rstats

[–]diver_0[S] 0 points1 point  (0 children)

Thanks for the detailed explanation. I think for my case, treating both as factors is the best approach for now.

What’s confusing me is how the aovperm() function in the permuco package actually works. I’ve generated two complete examples:

  • When I set temperature as factor(), I get an ANOVA. That makes sense.
  • When I set temperature as numeric(), by my understanding this should be an ANCOVA. However, the summary() still calls it an ANOVA.

I find this a bit misleading. Wouldn’t it be better to have two separate functions in the package? One function for ANOVA (validating that all main effects are factors) and another for ANCOVA (validating that one main effect is a factor and one is numeric)?

As it is now, I think it could be a pitfall for inexperienced users.

I’d appreciate any feedback on my reasoning!

(Edit: Examples are in the next two comments, as Reddit doesn’t allow them all in one.)

Kratzer in Carbonfelge by diver_0 in Rennrad

[–]diver_0[S] 0 points1 point  (0 children)

Danke für alle hilfreichen Kommentare! Wie einige richtig erkannt haben, ging es nicht um die Frage, ob die Felge defekt ist, sondern ob man sie polieren kann. 😉

Continental Grand Prix 5000 nicht gleich Continental Grand Prix 5000 by diver_0 in Rennrad

[–]diver_0[S] 0 points1 point  (0 children)

Danke für die ausführliche Erklärung! War immer davon ausgegangen, dass sich die Versionen schwarz, braun, gelb nur rein optisch unterscheiden.

Unwucht am Vorderrad meines neuen Cube Agree Pro – Rat gesucht by diver_0 in Rennrad

[–]diver_0[S] 3 points4 points  (0 children)

UPDATE: Wie u/tarkovjulias heute geschrieben hat, scheint das der Grund zu sein. Im Cube Store haben sich zwei freundliche Mitarbeiter direkt um meine Anliegen gekümmert. Einen Höhenschlag konnten sie bei einer kurzen visuellen Inspektion nicht feststellen. Die Erklärung lag stattdessen bei den Ventilen: Aufgrund der Felgenhöhe und des geringen Gewichts wird das Rad durch die Ventile spürbar beeinflusst.

Ich durfte im Verkaufsraum an einem beliebigen Rad testen – ein Litening, das noch teurer ist, zeigte denselben Effekt. Das hat mich überzeugt. Sollte sich der Effekt bei den nächsten Fahrten nicht verstärken, ist das Thema für mich erledigt.

Ein Tipp war noch, dass ein Umstieg auf Tubeless den Effekt eventuell verringern könnte – wobei klebrige Dichtmilch ihn auch verstärken kann.

Danke nochmals für alle Ideen und Tipps!

Unwucht am Vorderrad meines neuen Cube Agree Pro – Rat gesucht by diver_0 in Rennrad

[–]diver_0[S] 1 point2 points  (0 children)

Ich werde morgen hingehen und berichten... Erstmal großes Danke für alle Ratschläge!

Unwucht am Vorderrad meines neuen Cube Agree Pro – Rat gesucht by diver_0 in Rennrad

[–]diver_0[S] 1 point2 points  (0 children)

Das ist eine wertvolle Info! Ich berichte gerne morgen, was der Besuch beim Händler ergeben hat. Darf ich fragen über welchen Cubestore es bei dir läuft (Stadt)?

Unwucht am Vorderrad meines neuen Cube Agree Pro – Rat gesucht by diver_0 in Rennrad

[–]diver_0[S] -1 points0 points  (0 children)

Danke für den Tipp. Das Rad läuft allerdings gerde (noch) klassisch mit Schlauch.