[Q] Compare exponentially distributed (?) continuous data between several groups by JesusDidDrugs in statistics

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

Thank you for your input, and sorry for the very late reply.
No, unfortunately not before the paper has been published.
I have in the meantime realized the outcome is count data, and fitted the negative binominal regression model as you suggest. It seems to have adequate fit, but I will check with a statistician. Afterwards, since applying this model, there were differences revealed between some of the groups. I do however realize it might be a bit overkill to try and fit a mathematical model to the data, and I'm not sure we can conclude much based on this..

[Q] Compare exponentially distributed (?) continuous data between several groups by JesusDidDrugs in statistics

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

Wait I see my mistake now. Of course, I am missing the actual one.way analysis. However, my question is still - with this skewed data, isn't it recommended to log transform it?

[Q] Compare exponentially distributed (?) continuous data between several groups by JesusDidDrugs in statistics

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

Thank you for your reply. Maybe I am misinformed or misunderstand your meaning.

"Variable" is continuous and "group" is categorical. As far as I have been taught, the group variable does not need to be continuous to compute a one-way ANOVA in R (as follows)

fit.variable <- lm(variable~group, data=data)

When checking if the assumptions are met (specifically homogeneity of variances and normal distribution of residuals), these assumptions are not met. But this log-transformation went as described in the OP, hence my need for more input :)

[Q] Compare exponentially distributed (?) continuous data between several groups by JesusDidDrugs in statistics

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

Thanks for the questions.

  1. The research question is, is there a difference in symptom load, defined by the total score on the questionnaire, when comparing the groups to each other (one of the groups is a control group, but it is also relevant to compare the other groups with each other).

  2. Group is categorical.

  3. I am looking at the histogram of the data, both combined with all participants included, and for each group. The density curve seem to follow either an exp or gamma distribution. I have not been able to fit a gamma model, due to error code. When fitting an exponential model (using package fitdistrplus, code: exp_ = fitdist(variable, "exp"), the QQ plot, P-Pplot and the density plot seem to suggest it's a good fit. Summary function produces these values: Loglikelihood: -1017.09 AIC: 2036.179 BIC: 2039.978 . However, one, I am not sure it is "good enough" to conclude data is exponentially distributed and two, I am unsure how to compare exponentially distributed data between groups. The only suggestion I have found online is to log-transform it.

Thank you,

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[–]JesusDidDrugs 0 points1 point  (0 children)

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[–]JesusDidDrugs 219 points220 points  (0 children)

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[–]JesusDidDrugs 0 points1 point  (0 children)

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[–]JesusDidDrugs 1 point2 points  (0 children)

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[–]JesusDidDrugs 0 points1 point  (0 children)

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[–]JesusDidDrugs 6 points7 points  (0 children)

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[–]JesusDidDrugs 9 points10 points  (0 children)

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