Comparison to control in logistic regression

被引:7
|
作者
Dasgupta, N
Spurrier, JD
Martinez, E
Moore, BC
机构
[1] Washington State Univ, Program Stat, Pullman, WA 99164 USA
[2] Univ S Carolina, Dept Stat, Columbia, SC 29208 USA
[3] Washington State Univ, Dept Nat Resource Sci, Pullman, WA 99164 USA
关键词
binary response; likelihood ratio; maximum Likelihood; multivariate chi-square; simultaneous test; step-down; sequentially rejective; marginal power;
D O I
10.1080/03610910008813653
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
We are interested in comparing logistic regressions for several test treatments or populations with a logistic regression for a standard treatment or population. The research was motivated by some real life problems, which are discussed as data examples. We propose a step-down likelihood ratio method for declaring differences between the test treatments or populations and the standard treatment or population. Competitors based on the sequentially rejective Bonferroni Wald statistic, sequentially rejective exact Wald statistic and Reiersol's statistic are also discussed. It is shown that the proposed method asymptotically controls the probability of type I error. A Monte Carlo Simulation shows that the proposed method performs well for relatively small sample sizes, outperforming its competitors.
引用
收藏
页码:1039 / 1057
页数:19
相关论文
共 50 条
  • [1] Comparison of logistic regression and linear regression in modeling percentage data
    Zao, LH
    Chen, YH
    Schaffner, DW
    [J]. APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2001, 67 (05) : 2129 - 2135
  • [2] A Comparison of Classification/Regression Trees and Logistic Regression in Failure Models
    Irimia-Dieguez, A. I.
    Blanco-Oliver, A.
    Vazquez-Cueto, M. J.
    [J]. 2ND GLOBAL CONFERENCE ON BUSINESS, ECONOMICS, MANAGEMENT AND TOURISM, 2015, 23 : 9 - 14
  • [3] Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?
    Lin, Yingzhi
    Deng, Xiangzheng
    Li, Xing
    Ma, Enjun
    [J]. FRONTIERS OF EARTH SCIENCE, 2014, 8 (04) : 512 - 523
  • [4] Comparison of multinomial logistic regression and logistic regression: which is more efficient in allocating land use?
    Yingzhi Lin
    Xiangzheng Deng
    Xing Li
    Enjun Ma
    [J]. Frontiers of Earth Science, 2014, 8 : 512 - 523
  • [5] Comparison of multinomial logistic regression and logistic regression:which is more efficient in allocating land use?
    Yingzhi LIN
    Xiangzheng DENG
    Xing LI
    Enjun MA
    [J]. Frontiers of Earth Science., 2014, 8 (04) - 523
  • [6] A Comparison of Classification/Regression Trees and Logistic Regression in Failure Models
    Irimia-Dieguez, A. I.
    Blanco-Oliver, A.
    Vazquez-Cueto, M. J.
    [J]. 4TH WORLD CONFERENCE ON BUSINESS, ECONOMICS AND MANAGEMENT (WCBEM-2015), 2015, 26 : 23 - 28
  • [7] A benchmark and comparison of active learning for logistic regression
    Yang, Yazhou
    Loog, Marco
    [J]. PATTERN RECOGNITION, 2018, 83 : 401 - 415
  • [8] A comparison of ordinary least squares and logistic regression
    Pohlmann, JT
    Leitner, DW
    [J]. OHIO JOURNAL OF SCIENCE, 2003, 103 (05) : 118 - 125
  • [9] A comparison of model choice strategies for logistic regression
    Markku Karhunen
    [J]. Journal of Data and Information Science, 2024, 9 (01) : 37 - 52
  • [10] Functional logistic regression: a comparison of three methods
    Mousavi, Seyed Nourollah
    Sorensen, Helle
    [J]. JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, 2018, 88 (02) : 250 - 268