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Biometrics, ISSN 0006-341X, 3/2012, Volume 68, Issue 1, pp. 129 - 137
Journal Article
European Journal of Operational Research, ISSN 0377-2217, 11/2016, Volume 255, Issue 1, pp. 103 - 109
Journal Article
Journal of Econometrics, ISSN 0304-4076, 2007, Volume 141, Issue 2, pp. 1281 - 1301
Journal Article
Medical Care, ISSN 0025-7079, 03/2019, Volume 57, Issue 3, pp. 237 - 243
BACKGROUND:The use of marginal structural models (MSMs) to adjust for time-varying confounding has increased in epidemiologic studies. However, in the setting... 
CAUSAL INFERENCE | multiple imputation | FULLY CONDITIONAL SPECIFICATION | missing data | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | HEALTH CARE SCIENCES & SERVICES | HEALTH POLICY & SERVICES | marginal structural models | plasmode simulation | VALUES | inverse probability weighting | KNEE OSTEOARTHRITIS | EXPOSURE
Journal Article
Statistics in Medicine, ISSN 0277-6715, 07/2019, Volume 38, Issue 15, pp. 2783 - 2796
The inverse probability weighted estimator is often applied to two‐phase designs and regression with missing covariates. Inverse probability weighted... 
missing at random | inverse selection weighting | two‐phase design | case‐control sampling | two-phase design | case-control sampling
Journal Article
Journal of Mathematical Analysis and Applications, ISSN 0022-247X, 01/2017, Volume 445, Issue 1, pp. 374 - 393
We study the Matsumoto–Yor property in free probability. We prove that the limiting empirical eigenvalue distribution of the GIG matrices and the... 
Free Generalized Inverse Gaussian distribution | Conditional moments | Matsumoto–Yor property | Freeness | Free Poisson distribution | Matsumoto-Yor property | REGRESSION | MATHEMATICS, APPLIED | GIG | FREE RANDOM-VARIABLES | CONVOLUTION | POLYNOMIALS | MATHEMATICS | NON-CROSSING PARTITIONS | GAMMA-LAWS | INDEPENDENCE PROPERTY
Journal Article
Journal of the American Statistical Association, ISSN 0162-1459, 01/2018, Volume 113, Issue 521, pp. 369 - 379
The development of coherent missing data models to account for nonmonotone missing at random (MAR) data by inverse probability weighting (IPW) remains to date... 
Augmented IPW | Nonmonotone missing at random data | Bayes | REGRESSION | RESPONSES | STATISTICS & PROBABILITY | MULTIPLE IMPUTATION | OUTCOMES | GENERALIZED LINEAR-MODELS | LIKELIHOOD | Missing data | Economic models | Weighting | Computer simulation | Estimation | Maximum likelihood estimators | Infants | Bayesian analysis | Inverse probability weighting | Missing at random
Journal Article
American Journal of Epidemiology, ISSN 0002-9262, 03/2018, Volume 187, Issue 3, pp. 585 - 591
Abstract Missing data is a common occurrence in epidemiologic research. In this paper, 3 data sets with induced missing values from the Collaborative Perinatal... 
inverse probability weighting | missing-at-random data | nonmonotone missingness | missing data | PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH | Pregnancy | Data Interpretation, Statistical | Data Accuracy | Humans | Probability | Female | Statistics as Topic - methods | Practice of Epidemiology
Journal Article