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Evaluating the effect of optimized cutoff values in the assessment of prognostic factors

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  • Lausen, Berthold
  • Schumacher, Martin

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  • Lausen, Berthold & Schumacher, Martin, 1996. "Evaluating the effect of optimized cutoff values in the assessment of prognostic factors," Computational Statistics & Data Analysis, Elsevier, vol. 21(3), pages 307-326, March.
    • Handle: RePEc:eee:csdana:v:21:y:1996:i:3:p:307-326
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    Cited by:

    1. Tunes-da-Silva, Gisela & Klein, John P., 2011. "Cutpoint selection for discretizing a continuous covariate for generalized estimating equations," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 226-235, January.
    2. Heinzl, Harald & Tempfer, Clemens, 2001. "A cautionary note on segmenting a cyclical covariate by minimum P-value search," Computational Statistics & Data Analysis, Elsevier, vol. 35(4), pages 451-461, February.
    3. Saptarshi Chatterjee & Shrabanti Chowdhury & Sanjib Basu, 2021. "A model‐free approach for testing association," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 70(3), pages 511-531, June.
    4. Hollander, Norbert & Schumacher, Martin, 2006. "Estimating the functional form of a continuous covariate's effect on survival time," Computational Statistics & Data Analysis, Elsevier, vol. 50(4), pages 1131-1151, February.
    5. Boulesteix, Anne-Laure & Strobl, Carolin, 2007. "Maximally selected Chi-squared statistics and non-monotonic associations: An exact approach based on two cutpoints," Computational Statistics & Data Analysis, Elsevier, vol. 51(12), pages 6295-6306, August.
    6. Contal, Cecile & O'Quigley, John, 1999. "An application of changepoint methods in studying the effect of age on survival in breast cancer," Computational Statistics & Data Analysis, Elsevier, vol. 30(3), pages 253-270, May.
    7. Sauerbrei, W. & Meier-Hirmer, C. & Benner, A. & Royston, P., 2006. "Multivariable regression model building by using fractional polynomials: Description of SAS, STATA and R programs," Computational Statistics & Data Analysis, Elsevier, vol. 50(12), pages 3464-3485, August.
    8. Taylor, Jeremy M. G. & Yu, Menggang, 2002. "Bias and Efficiency Loss Due to Categorizing an Explanatory Variable," Journal of Multivariate Analysis, Elsevier, vol. 83(1), pages 248-263, October.
    9. John O'Quigley & Loki Natarajan, 2004. "Erosion of Regression Effect in a Survival Study," Biometrics, The International Biometric Society, vol. 60(2), pages 344-351, June.
    10. Yu-Min Huang, 2019. "Binary surrogates with stratified samples when weights are unknown," Computational Statistics, Springer, vol. 34(2), pages 653-682, June.
    11. Anning Hu, 2017. "Using a discretized measure of academic performance to approximate primary and secondary effects in inequality of educational opportunity," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(4), pages 1627-1643, July.
    12. Torsten Hothorn & Achim Zeileis, 2008. "Generalized Maximally Selected Statistics," Biometrics, The International Biometric Society, vol. 64(4), pages 1263-1269, December.
    13. Qiu, Zhiping & Peng, Limin & Manatunga, Amita & Guo, Ying, 2019. "A smooth nonparametric approach to determining cut-points of a continuous scale," Computational Statistics & Data Analysis, Elsevier, vol. 134(C), pages 186-210.
    14. Hothorn, Torsten & Lausen, Berthold, 2003. "On the exact distribution of maximally selected rank statistics," Computational Statistics & Data Analysis, Elsevier, vol. 43(2), pages 121-137, June.
    15. López-Ratón, Mónica & Rodríguez-Álvarez, María Xosé & Cadarso-Suárez, Carmen & Gude-Sampedro, Francisco, 2014. "OptimalCutpoints: An R Package for Selecting Optimal Cutpoints in Diagnostic Tests," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i08).

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