Thank you so much for this video! This was exactly what I was looking for. :) For upcoming videos, it will be extra helpful if you can briefly discuss how we interpret the results as well as how people typically report the results in academic papers (e.g., F(2, 87) = 1.52, p = 0.22)
Thanks. Presentation style/format of statistical results can vary from journal to journal. Some journals would like the statistical test result and degrees of freedom presented, some don't. In relation to p-value, I would recommend not presenting to 2dp - too rounded in my opinion and may impact a conclusion. I generally present my p-values to 3dp or 4dp. This number often dependent on journal requirements.
Thank you for demonstrating this piece of work on mixed models, but, would have been easier if you can also deliver the syntaxes used (downloadable) for people like me.
Not really. This is for the user to ensure that if there are multiple explanatory continuous variables in the model, that these variables are not autocorrelated, e.g., using variance inflation factor. Also, it's important that if the purpose is model fitting, that the model residuals are checked for normality and randomness.
@@LaceyMathsStatsConsultancy Thanks! Sorry I actually meant temporal autocorrelation. I find it difficult to get my head around that concept or how to properly implement it in repeated measures models!
@@designedfore I'd imagine in this case, it would be a matter of checking the autocorrelation of the residuals from the model. So if the model residuals are not approximately normally distributed and random, then there is a potential issue with the model. I can look to do a video on this, if you feel it may be of help?
Thank you so much for this video! This was exactly what I was looking for. :) For upcoming videos, it will be extra helpful if you can briefly discuss how we interpret the results as well as how people typically report the results in academic papers (e.g., F(2, 87) = 1.52, p = 0.22)
Thanks. Presentation style/format of statistical results can vary from journal to journal. Some journals would like the statistical test result and degrees of freedom presented, some don't. In relation to p-value, I would recommend not presenting to 2dp - too rounded in my opinion and may impact a conclusion. I generally present my p-values to 3dp or 4dp. This number often dependent on journal requirements.
Thank you for the video and scripts!!!
It was a very good video for me, please do the next video...
Thank you...a follow-up video is on the to-do list.
Thank you for demonstrating this piece of work on mixed models, but, would have been easier if you can also deliver the syntaxes used (downloadable) for people like me.
Thanks for the clear video! I was wondering if the presented models account for autocorrelation (and whether they even should or not)?
Not really. This is for the user to ensure that if there are multiple explanatory continuous variables in the model, that these variables are not autocorrelated, e.g., using variance inflation factor. Also, it's important that if the purpose is model fitting, that the model residuals are checked for normality and randomness.
@@LaceyMathsStatsConsultancy Thanks! Sorry I actually meant temporal autocorrelation. I find it difficult to get my head around that concept or how to properly implement it in repeated measures models!
@@designedfore I'd imagine in this case, it would be a matter of checking the autocorrelation of the residuals from the model. So if the model residuals are not approximately normally distributed and random, then there is a potential issue with the model. I can look to do a video on this, if you feel it may be of help?
@@designedfore - some interesting info on temporal autocorrelation on www.flutterbys.com.au/stats/tut/tut8.3a.html
I mean, some of the syntaxes and descriptions are hidden on the right side of the Rstudio
Hope the script from the following link is a help: drive.google.com/drive/folders/1qxJh5U5hzqznJG-vXlW7XvZ4uDk-S0g5?usp=sharing
Hi, I'm wondering what would be the method to find partial eta squared for the repeated measures ANOVA using lme function?
A few options out there, but I generally use the eta_sq() function in the sjstats package.