Explained variation for logistic regression - Small sample adjustments, confidence intervals and predictive precision

Biometrical Journal

Volumn 44, Issue 3, 2002, Pages 263-272

  Mittlbock M ^a   Schemper, M ^a  

^a UNIVERSITY OF VIENNA   (Austria)

Author keywords

Prediction error; Predictive accuracy; Proportion of explained variation; R2 measures; Shrinkage

Indexed keywords

DIRECT ANALOGS; REGRESSION ANALYSIS;

CONFIDENCE INTERVAL; GENERAL LINEAR MODELING; LOGISTICS REGRESSIONS; PREDICTION ERRORS; PREDICTIVE ACCURACY; PREDICTIVE PRECISION; PROGNOSTIC FACTORS; PROPORTION OF EXPLAINED VARIATION; R2 MEASURE; SMALL SAMPLES;

SHRINKAGE;

EID: 0036013105     PISSN: 03233847     EISSN: None     Source Type: Journal    
DOI: 10.1002/1521-4036(200204)44:3<263::AID-BIMJ263>3.0.CO;2-7     Document Type: Article

References (17)

1. 2: A useful measure of model performance when predicting a dichotomous outcome
2. Using regression models for prediction: Shrinkage and regression to the mean
3. A comment on the coefficient of determination for binary responses
4. Tutorial in biostatistics: Multivariable prognostic models: Issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors
5. 2 in regression analysis
6. The area under the ROC curve and its competitors
7. Explained residual variation, explained risk, and goodnes of fit
8. Coefficients of determination for multiple logistic regression analysis
9. Explained variation for logistic regression
10. Predictive value of statistical models
11. 2: Its use in weighted least-squares regression analysis
12. Summarizing the predictive power of a generalized linear model