A note on convergence of calibration weights to inverse probability weights

被引:0
|
作者
Fushiki, Tadayoshi [1 ]
机构
[1] Niigata Univ, Fac Educ, 8050 Ikarashi,2-no-cho,Nishi Ward, Niigata, Japan
关键词
calibration; missing data; nonresponse bias; propensity score;
D O I
10.1111/stan.12356
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
Recently, nonresponse rates in sample surveys have been increasing. Nonresponse bias is a serious concern in the analysis of sample surveys. The calibration and propensity score methods are used to adjust nonresponse bias. The propensity score method uses the weights of the inverse probability of response. The inverse probability of response is estimated by the auxiliary variables observed in respondents and nonrespondents. The calibration method can use additional auxiliary variables observed only in respondents if the population distributions of the variables are known. The calibration method is widely used; however, the theoretical property in the nonresponse situation has not been investigated. This study provides a condition that the calibration weights asymptotically go to the inverse probability of response and clarifies the relationship between the calibration and propensity score methods.
引用
收藏
页数:8
相关论文
共 50 条
  • [41] A note on the accuracy of discrimination of weights and lengths
    Thorndike, EL
    PSYCHOLOGICAL REVIEW, 1909, 16 (05) : 340 - 346
  • [42] A NOTE ON REPRESENTATION FUNCTIONS WITH DIFFERENT WEIGHTS
    Qu, Zhenhua
    COLLOQUIUM MATHEMATICUM, 2016, 143 (01) : 105 - 112
  • [43] Note on weights of paths in polyhedral graphs
    Madaras, T
    DISCRETE MATHEMATICS, 1999, 203 (1-3) : 267 - 269
  • [44] Note on "On the normalization of interval and fuzzy weights"
    Li, De-Qing
    Wang, Jia-Yin
    Li, Hong-Xing
    FUZZY SETS AND SYSTEMS, 2009, 160 (18) : 2722 - 2725
  • [45] Inverse Probability Weights for Quasicontinuous Ordinal Exposures With a Binary Outcome: Method Comparison and Case Study
    Sack, Daniel E.
    Shepherd, Bryan E.
    Audet, Carolyn M.
    De Schacht, Caroline
    Samuels, Lauren R.
    AMERICAN JOURNAL OF EPIDEMIOLOGY, 2023, 192 (07) : 1192 - 1206
  • [46] A flexible parametric approach for estimating continuous-time inverse probability of treatment and censoring weights
    Saarela, Olli
    Liu, Zhihui
    STATISTICS IN MEDICINE, 2016, 35 (23) : 4238 - 4251
  • [47] Limitation of Inverse Probability-of-Censoring Weights in Estimating Survival in the Presence of Strong Selection Bias
    Howe, Chanelle J.
    Cole, Stephen R.
    Chmiel, Joan S.
    Munoz, Alvaro
    AMERICAN JOURNAL OF EPIDEMIOLOGY, 2011, 173 (05) : 569 - 577
  • [48] How should we estimate inverse probability weights with possibly misspecified propensity score models?
    Katsumata, Hiroto
    POLITICAL SCIENCE RESEARCH AND METHODS, 2024,
  • [49] Prior probability weights and neural network learning
    Matsuyama, Y
    Furukawa, S
    Ikeda, T
    PROGRESS IN CONNECTIONIST-BASED INFORMATION SYSTEMS, VOLS 1 AND 2, 1998, : 267 - 270
  • [50] Optimal Probability Weights for Inference With Constrained Precision
    Santacatterina, Michele
    Bottai, Matteo
    JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2018, 113 (523) : 983 - 991