Titlebook: Regression Analysis in Medical Research; for Starters and 2nd Ton J. Cleophas,Aeilko H. Zwinderman Textbook 20181st edition Springer Intern

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Laplace Regressions, Multi-instead of Mono-exponential Regressions,ans. The term mixed effect models refers to the random effect statistical regression models applied. More information of mixed effects linear models is given in the Chap. 8. This chapter addressed mixed effect . models, particularly mixed effects multi-exponential models. Especially, concentration-t

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Standardized Regression Coefficients,e factors. Path analysis, structural equation modeling, and Bayesian networks are able to account not only Bayesian Networks direct but also indirect relationships across a network of variables. Unfortunately, p-values are not provided, but Akaike information indexes can be used to assess and compar

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Multivariate Analysis of Variance and Canonical Regression,ables it can handle and due to the flaw of positive correlations between variables minimizing the statistical power of the models. Also overall statistics are lacking. Canonical analysis is wonderful, because it can handle many more variables than Manova, accounts for the relative importance of the

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Regression Trend Testing,xpected and we need, particularly, sensitive tests. A standard approach to the analysis of such data is multiple groups analysis of variance (Anova) and multiple groups chi-square tests, but a more sensitive approach may be a trend-analysis. A trend means an association between the order of treatmen

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