Results 31 to 40 of about 1,729,359 (279)
Spontaneous breaking of rotational symmetry in the presence of defects [PDF]
, 2013 We prove a strong form of spontaneous breaking of rotational symmetry for a simple model of two-dimensional crystals with random defects in thermal equilibrium at low temperature.
Heydenreich, Markus +2 more
core +2 more sources
BMC Medical Research Methodology, 2019 Background In many clinical trials continuous outcomes are dichotomized to compare proportions of patients who respond. A common and recommended approach to handling missing data in responder analysis is to impute as non-responders, despite known biases.
Lysbeth Floden, Melanie L. Bell
doaj +1 more source
Regularized approach for data missing not at random [PDF]
Statistical Methods in Medical Research, 2017 It is common in longitudinal studies that missing data occur due to subjects’ no response, missed visits, dropout, death or other reasons during the course of study. To perform valid analysis in this setting, data missing not at random (MNAR) have to be considered.
Chi-Hong, Tseng, Yi-Hau, Chen
openaire +2 more sources
Comparison of Different LGM-Based Methods with MAR and MNAR Dropout Data
Frontiers in Psychology, 2017 The missing not at random (MNAR) mechanism may bias parameter estimates and even distort study results. This study compared the maximum likelihood (ML) selection model based on missing at random (MAR) mechanism and the Diggle–Kenward selection model ...
Meijuan Li +5 more
doaj +1 more source
Random Intersection Graphs and Missing Data
Proceedings of the AAAI Conference on Artificial Intelligence, 2020 Random-graphs and statistical inference with missing data are two separate topics that have been widely explored each in its field. In this paper we demonstrate the relationship between these two different topics and take a novel view of the data matrix as a random intersection graph.
Dror Salti, Yakir Berchenko
openaire +2 more sources
Problems in dealing with missing data and informative censoring in clinical trials
Current Controlled Trials in Cardiovascular Medicine, 2002 A common problem in clinical trials is the missing data that occurs when patients do not complete the study and drop out without further measurements. Missing data cause the usual statistical analysis of complete or all available data to be subject to ...
Shih Weichung
doaj +1 more source
Collaborative Filtering and the Missing at Random Assumption
CoRR, 2012 Rating prediction is an important application, and a popular research topic in collaborative filtering. However, both the validity of learning algorithms, and the validity of standard testing procedures rest on the assumption that missing ratings are missing at random (MAR).
Benjamin M. Marlin +3 more
openaire +3 more sources
Randomly and Non-Randomly Missing Renal Function Data in the Strong Heart Study: A Comparison of Imputation Methods. [PDF]
PLoS ONE, 2015 Kidney and cardiovascular disease are widespread among populations with high prevalence of diabetes, such as American Indians participating in the Strong Heart Study (SHS).
Nawar Shara +7 more
doaj +1 more source
Inference for partial correlation when data are missing not at random
, 2017 We introduce uncertainty regions to perform inference on partial correlations when data are missing not at random. These uncertainty regions are shown to have a desired asymptotic coverage.
de Luna, Xavier, Gorbach, Tetiana
core +1 more source
Evaluation of missing data mechanisms in two and three dimensional incomplete tables
, 2018 The analysis of incomplete contingency tables is a practical and an interesting problem. In this paper, we provide characterizations for the various missing mechanisms of a variable in terms of response and non-response odds for two and three dimensional
Ghosh, S., Vellaisamy, P.
core +1 more source