Model Validation: Interpreting Residual Plots

includes "idealized plots

bias

homoskedasticidy

visualization - categorical data - SAS - R

Michael Friendly 
http://www.datavis.ca/courses/VCD/

cf vcd package
vcdExtra

CrossValidation1_JDS_May2011.pdf tutorial from interesting website (Objekt application/pdf)

CrossValidation1_JDS_May2011.pdf (Objekt application/pdf)

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regularized logistic regression - andrew gelman

priors11.pdf (Objekt application/pdf)

cf problems of logistic model overfitting /cf iterative optimiztion /, data sparsity, complete separation, multicolinearity in LOGISITIC REGRESSION
- one solution - exclude variables that cause complete separation, multicolinearity etc. - however these variables may be the strongest, and of importance.
- new solution - adding some data into model /priors/, which may improve/stabilize model performance

technical

Harrell cross validation - old doc 1998 logistic.val.pdf (Objekt application/pdf)

logistic.val.pdf (Objekt application/pdf)

Statistical Modeling, Causal Inference, and Social Science

Statistical Modeling, Causal Inference, and Social Science

BLOG by andrew gelman et al.

RSS R Introduction Course

RSS R Introduction Course XXXXXXXXXXXXXXXXXXXXXXXXXXX