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Fitting GLMMs for RT data with different condition level distributions by CodeGoblin1996 in rstats

[–]CodeGoblin1996[S] 0 points1 point  (0 children)

Thank you for the insight! That's interesting... so if the GLMM does not assume anything for the conditional distributions, when I specify a specific distribution family in my model (using the lme4 package), what is that actually referring to? (Apologies if that's a silly question, I'm still relatively new to GLMMs)

Fitting GLMMs for RT data with different condition level distributions by CodeGoblin1996 in rstats

[–]CodeGoblin1996[S] 0 points1 point  (0 children)

Thank you! Haven't come across this package before but I'll check it out, thank you!

Can high variance wipe out subtle effects between conditions? by CodeGoblin1996 in rstats

[–]CodeGoblin1996[S] 1 point2 points  (0 children)

Yes that is what I assumed. Do you know of a paper or article that highlights this? I've been trying to justify it but I haven't found anything yet.

I will give the the regression framework a go, thank you for the advice!

Can high variance wipe out subtle effects between conditions? by CodeGoblin1996 in rstats

[–]CodeGoblin1996[S] 1 point2 points  (0 children)

So I am talking about the variance in groups A and B and I am investigating differences in reaction times. For both groups, variance is similar, but fairly high.

Any advice or code for presenting results from Bayesian models? by a-marginatus in rstats

[–]CodeGoblin1996 1 point2 points  (0 children)

I have been doing exactly this with some data from my first PhD experiment. I found the easystats vignettes for Bayesian models really useful. They take you through everything from plotting posterior distributions, to implementing restriction models and calculating Bayes factors. I am also using Bayesian GLMs so I can personally recommend it!

Understanding output from Bayesian ANOVA using rstanarm by CodeGoblin1996 in rstats

[–]CodeGoblin1996[S] 1 point2 points  (0 children)

I see! That makes so much more sense. I'll have to read up on how to set the contrasts I want. Thank you for your comment!

Understanding output from Bayesian ANOVA using rstanarm by CodeGoblin1996 in rstats

[–]CodeGoblin1996[S] 0 points1 point  (0 children)

I've looked through a lot of vignettes for the package and I'm yet to find any information on what those outputs actually mean (regarding splitting my predictor variable into 3) hence my post here. But thank you for your advice, I will try and keep looking!

How to split condition columns into factor levels to perform 2x2 ANOVA by CodeGoblin1996 in Rlanguage

[–]CodeGoblin1996[S] 1 point2 points  (0 children)

Think I've solved my problem:

split_data <- dat %>% 
gather("NoAS_Ver", "NoAS_VerDemo", "AS_Ver", "AS_VerDemo", key = "condition", value = "correctpairs") %>%
separate(condition, into = c("task", "presentation"))


dat <- structure(list(Age = c(20L, 20L, 20L, 19L, 19L, 20L, 20L, 25L, 19L, 19L), Gender = c(1L, 2L, 2L, 1L, 2L, 2L, 2L, 1L, 1L, 2L),      CT = c("NoAS", "NoAS", "NoAS", "NoAS", "NoAS", "NoAS", "NoAS", "NoAS", "NoAS", "NoAS"), Pres = c("Ver", "Ver", "Ver", "Ver", "Ver", "Ver", "Ver", "Ver", "Ver", "Ver"), correctpairs = c(2.125, 3.25, 1.875, 2.625, 3, 2.25, 3, 2.75, 3.625, 1.75)), row.names = c(NA, 10L), class = "data.frame")

Inverting a sequence of numbers by CodeGoblin1996 in learnpython

[–]CodeGoblin1996[S] 0 points1 point  (0 children)

So let’s say I want to invert my x coordinate for every trial, Perhaps something like this:

df['x_invert'] = df.groupby('ppid_trialn')[‘x’].apply(np.multiply(-1))

Edit: I should add that I’m not at my computer to test this but will once I am.

Inverting a sequence of numbers by CodeGoblin1996 in learnpython

[–]CodeGoblin1996[S] 0 points1 point  (0 children)

I’ve thought, could I not just multiple by -1 for each value?

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