Analyzing the changing gender wage gap based on multiply imputed right censored wages [PDF]
"In order to analyze the gender wage gap with the German IAB-employment sample we have to solve the problem of censored wages at the upper limit of the social security system. We treat this problem as a missing data problem.
Gartner, Hermann, Rässler, Susanne
core
Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma
Molecular Oncology, EarlyView.Cervical adenocarcinoma patients face worse outcomes than squamous cell carcinoma counterparts despite similar treatment. The identification of IGFL2‐AS1's differential expression provides a molecular basis for distinguishing these histotypes, paving the way for personalized therapies and improved survival in vulnerable populations globally.
Ricardo Cesar Cintra +6 more
wiley +1 more source
An equivalence result for moment equations when data are missing at random
Statistical Theory and Related Fields, 2019 We consider general statistical models defined by moment equations when data are missing at random. Using the inverse probability weighting, such a model is shown to be equivalent with a model for the observed variables only, augmented by a moment ...
Marian Hristache, Valentin Patilea
doaj +1 more source
Multiple imputation of missing data under missing at random: compatible imputation models are not sufficient to avoid bias if they are mis-specified. [PDF]
J Clin Epidemiol, 2023 Curnow E +7 more
europepmc +1 more source
RIPK4 function interferes with melanoma cell adhesion and metastasis
Molecular Oncology, EarlyView.RIPK4 promotes melanoma growth and spread. RIPK4 levels increase as skin lesions progress to melanoma. CRISPR/Cas9‐mediated deletion of RIPK4 causes melanoma cells to form less compact spheroids, reduces their migratory and invasive abilities and limits tumour growth and dissemination in mouse models.
Norbert Wronski +9 more
wiley +1 more source
Empirical likelihood for quantile regression models with response data missing at random
Open Mathematics, 2017 This paper studies quantile linear regression models with response data missing at random. A quantile empirical-likelihood-based method is proposed firstly to study a quantile linear regression model with response data missing at random.
Luo S., Pang Shuxia
doaj +1 more source
Linear mixed models to handle missing at random data in trial-based economic evaluations. [PDF]
Health Econ, 2022 Gabrio A +3 more
europepmc +1 more source
Molecular Oncology, EarlyView.Loss of the miR‐214/199a cluster is associated with recurrence in ovarian cancer. Engineered small extracellular vesicles (m214‐sEVs) elevate miR‐214‐3p/miR‐199a‐5p in tumor cells, suppress β‐catenin, TLR4, and YKT6 signaling, reprogram tumor‐derived sEV cargo, reduce chemoresistance and migration, and enhance carboplatin efficacy and survival in ...
Weida Wang +12 more
wiley +1 more source
Sample size calculation for randomized trials via inverse probability of response weighting when outcome data are missing at random. [PDF]
Stat Med, 2023 Harrison LJ, Wang R.
europepmc +1 more source
Interrogating the immune landscape of microsatellite stable RAS‐mutated colon cancer
Molecular Oncology, EarlyView.COLOSSUS project RAS‐mutated MSS colon cancer study explored transcriptomics and immune cell density by immunohistochemistry (IHC), Immunoscore (IS), ISIC/TuLIS scores, mutation counts, and detected different prevalences but similar microenvironment composition across immune markers with clinical relevance for future immunotherapy combination ...
Rodrigo Dienstmann +61 more
wiley +1 more source