[R] Question about implementing statistical test in R
tebert @end|ng |rom u||@edu
Wed May 3 21:23:46 CEST 2023
Start with defining your dependent variable and independent variable(s). As an equation like y equals some function of x, the y is the dependent variable. It is often continuous, but does not have to be.
If your continuous variable is the dependent variable and you have one categorical independent variable then the ANOVA would be a general comparison tests determining if there are differences. This can be further broken down by a multiple comparison test. The Tukey test is commonly used if you assume normal distributions. The Kruskal-Wallis test would be the start of a non-parametric approach.
From: R-help <r-help-bounces using r-project.org> On Behalf Of RIDDHI BABEL via R-help
Sent: Wednesday, May 3, 2023 11:42 AM
To: r-help using r-project.org
Subject: [R] Question about implementing statistical test in R
I am a new user and have a stats question that I need help implementing in R.
I have 4 groups and I want to assess whether there is a statistical difference between these groups at baseline first in a global comparison test and then a pairwise comparison test.
There are about 2 continuous variables and 10 categorical variables
For the group wise comparison for continuous variables-I am using the Mann Whitney test
For the categorical variables-I am using either chi square or Fisher exact test for both global comparison and pairwise comparison.
What packages should I use to implement this in R? Is there any example code that I use? I was thinking tbl_summary but don't think that's the right one.
Would really appreciate any help with this!
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