Can someone suggest handbook(s) that explain
classes of statistical models like in this link ?
(https://support.sas.com/documentation/cdl/en/statug/63347/HTML/default/viewer.htm#statug_intromod_a0000000333.htm)
Does it much important to explain to readers
the class of statistical model I have used ?
Hi there!
As far as I read, you have two main questions:
1st. Books about statistical models:
If you are a R lover (like me) you will enjoy these books:
https://uk.sagepub.com/en-gb/eur/discovering-statistics-using-r/book236067%20
https://www.amazon.com/Analysis-Regression-Multilevel-Hierarchical-Models/dp/052168689X
If you are very new to R, the first one is awesome.
2nd. Does it much important to explain to readers the class of statistical model I have used ?
I'm reviewer of several scientific journals and my answer is YES (yes, with capital letters! :) ), because data analysis must be replicable, I mean, you need to include and explain all the details you need to perform the analysis, if some details are missing or not included, the analysis would not be replicable. In some scientific journals, you can attach the syntax, in others, if you need to explain a lot of details, you can include it as supplementary material.
Hope this helps.
Best regards,
Merche Ovejero
Besides what Merche wrote you can also look into these books:
First four chapters of Norm MacLeod newsletter to grasp some ideas behind regression (and others if you are interested in multivariate statistics): http://www.palass.org/publications/newsletter/palaeomath-101
Basics: Sokal R.R., Rohlf F.J Biometry https://www.amazon.com/Biometry-Robert-R-Sokal/dp/0716786044
Slightly complicated stuff: Zuur, A., Ieno, E.N., Walker, N., Saveliev, A.A., Smith, G.M. Mixed Effects Models and Extensions in Ecology with R https://www.springer.com/in/book/9780387874579
Dear Muhamad
I hope the following links will be useful:
https://support.sas.com/documentation/onlinedoc/stat/131/intromod.pdf
and :
https://www.jmp.com/support/downloads/pdf/jmp1002/Modeling-and-Multivariate-Methods.pdf
Good Luck
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