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I am using the R package robustlmm for some analysis due to its characteristics. I have read in posts like this one that with this type of models is better to use confidence intervals than $p$-values, however, I couldn't find any literature which says that.

Does anyone know any reference to cite for saying that I use confidence intervals instead of $p$-values?

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Confidence intervals can be used for a decision regarding a hypothesis test. My suggestion would be to rather use it to back up the information that the p-value has already given. Here is an article for you https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2689604/

Hope it helps!

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  • $\begingroup$ Thanks @Niel. I am quite new in which refers to the statistic language so I would like to comment you why I need it for. In my case, I am testing if different predictors are "significant" or not for explaining my response variable, and after some reading, I decided to use confidence intervals for that. Besides, I am also calculating the r2m (variance explained by fixed factors) and the r2c (variance explained by fixed and random terms) to know how well my predictors explain my response variable. Am I doing well to your knowledge? Thanks for your time Niel. $\endgroup$
    – Dekike
    May 16 '20 at 10:52

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