![]() ![]() ![]() 13.5.2 Analysis of the dependent groups using compare_dependent_groups.13.3 Visualization and analysis of the two independent groups.13.2 Visualization and analysis of a single group (or variable).12 bmbstats: Bootstrap Magnitude-based Statistics package.10.5 Extending the Classical Test Theory.10.4 What to do when we know the error?.10.3 Interpreting individual changes using SESOI and SDC.10.1 Estimating TE using ordinary least products regression.7.8 Summarizing prior and posterior distributions with MAP and HDI.6.4.2 Two one-sided tests of equivalence.6.3 New Statistics: Confidence Intervals and Estimation.6.1 Null-Hypothesis Significance Testing.5.1 Two kinds of uncertainty, probability, and statistical inference.4.7.3 Direct and indirect effect, covariates and then some.4.7.2 Counterfactual analysis and Individual Treatment Effects.4.7.1 Analysis of the individual residuals: responders vs non-responders.4.7 Prediction as a complement to causal inference.4.6 Example of randomized control trial.4.3 Potential outcomes or counterfactuals.4.1 Necessary versus sufficient causality.3.6 Practical example: MAS and YoYoIR1 prediction.3.5 Magnitude-based prediction estimators.3.3 Bias-Variance decomposition and trade-off.3.2.1 Sample mean as the simplest predictive model.2.3 Describing relationship between two variables.2.1.3 The Smallest Effect Size Of Interest.2.1.1 Sample mean as the simplest statistical model. ![]()
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