Logistic regression and Ising networks: prediction and estimation when violating lasso assumptions
In: Behaviormetrika, Band 46, Heft 1, S. 49-72
ISSN: 1349-6964
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In: Behaviormetrika, Band 46, Heft 1, S. 49-72
ISSN: 1349-6964
In: Behaviormetrika, Band 44, Heft 2, S. 513-534
ISSN: 1349-6964
SSRN
Working paper
In: Statistica Neerlandica: journal of the Netherlands Society for Statistics and Operations Research, Band 73, Heft 3, S. 351-372
ISSN: 1467-9574
We propose to use the squared multiple correlation coefficient as an effect size measure for experimental analysis‐of‐variance designs and to use Bayesian methods to estimate its posterior distribution. We provide the expressions for the squared multiple, semipartial, and partial correlation coefficients corresponding to four commonly used analysis‐of‐variance designs and illustrate our contribution with two worked examples.