LogXact

LogXact® 11: Exact Inference for Logistic Regression. The complexity of conducting regression analysis over multiple covariates is well-documented. The challenge only intensifies when coupled with small sample sizes or missing data sets. LogXact aims to provide simple and accurate solutions for such difficulties. LogXact can handle many varieties of response data including continuous and binary, polytonomous, count, and missing data. Users of the software can be confident of in their results derived from LogXact’s advanced regression techniques.


References in zbMATH (referenced in 14 articles )

Showing results 1 to 14 of 14.
Sorted by year (citations)

  1. Yu, Shun; Huang, Xianzheng: Random-intercept misspecification in generalized linear mixed models for binary responses (2017)
  2. Heiberger, Richard M.; Holland, Burt: Statistical analysis and data display. An intermediate course with examples in R (2015)
  3. Juned Siddique; Ofer Harel: MIDAS: A SAS Macro for Multiple Imputation Using Distance-Aided Selection of Donors (2009) not zbMATH
  4. Maiti, Tapabrata; Pradhan, Vivek: Bias reduction and a solution for separation of logistic regression with missing covariates (2009)
  5. Kojima, Tsutomu; Hasegawa, Toru; Misumi, Munechika; Nakamura, Tsuyoshi: Risk analysis of software process measurements. (2008) ioport
  6. Torsten Hothorn; Kurt Hornik; Mark van de Wiel; Achim Zeileis: Implementing a Class of Permutation Tests: The coin Package (2008) not zbMATH
  7. Agresti, Alan; Gottard, Anna: Nonconservative exact small-sample inference for discrete data (2007)
  8. David Zamar; Brad McNeney; Jinko Graham: elrm: Software Implementing Exact-Like Inference for Logistic Regression Models (2007) not zbMATH
  9. Tchetgen, Eric J.; Coull, Brent A.: A diagnostic test for the mixing distribution in a generalised linear mixed model (2006)
  10. Karavasilis, G. J.; Kotti, V. K.; Tsitsis, D. S.; Vassiliadis, V. G.; Rigas, A. G.: Statistical methods and software for risk assessment: Applications to a neurophysiological data set (2005)
  11. Han, Karen E.; Catalano, Paul J.; Senchaudhuri, Pralay; Mehta, Cyrus: Exact analysis of dose response for multiple correlated binary outcomes (2004)
  12. Simonoff, Jeffrey S.: Analyzing categorical data (2003)
  13. Bilder, Christopher R.; Loughin, Thomas M.: Testing for conditional multiple marginal independence (2002)
  14. Bull, Shelley B.; Mak, Carmen; Greenwood, Celia M. T.: A modified score function estimator for multinomial logistic regression in small samples. (2002)