The advantages of permutation methods over approximate methods (AP, methods based on distribution assumptions) are explained in Chapter 1.2 and worked out in Chapter 1.3. It is shown how confounding variables are controlled (Chap. 1.4). In Chapter 1.5 experiments with repeated measurement designs are dealt with.
%0 Journal Article
%1 Schrausser94993376
%A Scambor, C.
%A Schrausser, D. G.
%D 2023
%I Academia
%J Thesis Chapters
%K Exact Permutationtests Statistics myown
%R 10.13140/RG.2.2.28632.06405
%T Introduction (part II, permutation tests for repeated measurement designs)
%U https://www.academia.edu/94993376
%X The advantages of permutation methods over approximate methods (AP, methods based on distribution assumptions) are explained in Chapter 1.2 and worked out in Chapter 1.3. It is shown how confounding variables are controlled (Chap. 1.4). In Chapter 1.5 experiments with repeated measurement designs are dealt with.
@article{Schrausser94993376,
abstract = {The advantages of permutation methods over approximate methods (AP, methods based on distribution assumptions) are explained in Chapter 1.2 and worked out in Chapter 1.3. It is shown how confounding variables are controlled (Chap. 1.4). In Chapter 1.5 experiments with repeated measurement designs are dealt with.},
added-at = {2023-06-27T02:14:13.000+0200},
author = {Scambor, C. and Schrausser, D. G.},
biburl = {https://www.bibsonomy.org/bibtex/2e4fea7ee7090a4b706dbf86b52d682b6/schrausser},
doi = {10.13140/RG.2.2.28632.06405},
interhash = {38dc75ffe330f0027fc10621abf3d9cf},
intrahash = {e4fea7ee7090a4b706dbf86b52d682b6},
journal = {Thesis Chapters},
keywords = {Exact Permutationtests Statistics myown},
language = {en},
month = {01},
note = {translation},
publisher = {Academia},
timestamp = {2023-06-28T05:32:41.000+0200},
title = {Introduction (part II, permutation tests for repeated measurement designs)},
url = {https://www.academia.edu/94993376},
year = 2023
}