Results 111 to 120 of about 764,403 (277)

Imputation strategies for missing binary outcomes in cluster randomized trials

BMC Medical Research Methodology, 2011
Background Attrition, which leads to missing data, is a common problem in cluster randomized trials (CRTs), where groups of patients rather than individuals are randomized.
Akhtar-Danesh Noori, Ma Jinhui, Dolovich Lisa, Thabane Lehana   +3 more
doaj   +1 more source

Performance Comparison of Various Imputation Methods for Missing Data Mechanisms (MAR, MCAR, and MNAR) in a Nonstationary Time Series

International Journal of Mathematics and Mathematical Sciences
Handling missing data in a time series is necessary for forecasting as they can significantly impact representation and pose serious problems such as loss of efficiency and unreliable results.
Chantha Wongoutong
doaj   +1 more source

An Alternative Sensitivity Approach for Longitudinal Analysis with Dropout

Journal of Probability and Statistics, 2019
In any longitudinal study, a dropout before the final timepoint can rarely be avoided. The chosen dropout model is commonly one of these types: Missing Completely at Random (MCAR), Missing at Random (MAR), Missing Not at Random (MNAR), and Shared ...
Amal Almohisen, Robin Henderson, Arwa M. Alshingiti   +2 more
doaj   +1 more source

MICE vs PPCA: Missing data imputation in healthcare

Informatics in Medicine Unlocked, 2019
Retrospective analyses of real-world clinical data face challenges owing to the absence of some data elements. Historically, missing data was addressed by first classifying its presence into one of three categories: missing completely at random (MCAR ...
Harshad Hegde, Neel Shimpi, Aloksagar Panny, Ingrid Glurich, Pamela Christie, Amit Acharya   +5 more
doaj   +1 more source

Model Averaging for Generalized Linear Model with Covariates that are Missing completely at Random

, 2017
In this paper, we consider the estimation of generalized linear models with covariates that are missing completely at random. We propose a model averaging estimation method and prove that the corresponding model averaging estimator is asymptotically optimal under certain assumptions. Simulaiton results illustrate that this method has better performance
Liu, Qingfeng, Zheng, Miaomiao
openaire   +2 more sources

Applicability of mitotic figure counting by deep learning: a development and pan‐cancer validation study

FEBS Open Bio, EarlyView.
In this study, we developed a deep learning method for mitotic figure counting in H&E‐stained whole‐slide images and evaluated its prognostic impact in 13 external validation cohorts from seven different cancer types. Patients with more mitotic figures per mm2 had significantly worse patient outcome in all the studied cancer types except colorectal ...
Joakim Kalsnes, Maria X. Isaksen, Frida Julbø, Manohar Pradhan, Andreas Kleppe, Sepp De Raedt, Ole‐Johan Skrede, Turid Torheim, John Arne Nesheim, Hans Martin Mohn, Hanne A. Askautrud, Karolina Cyll, Wanja Kildal, Emma Rewcastle, Melinda Lillesand, Vebjørn Kvikstad, Emiel Janssen, Robert Jones, Odd Terje Brustugun, Bjørn Brennhovd, Erik Skaaheim Haug, Lill‐Tove Rasmussen Busund, Elin Richardsen, Sigve Andersen, Tom Dønnem, Kristina Lindemann, Gunnar Kristensen, Neil A. Shepherd, Marco Novelli, Knut Liestøl, David Kerr, Håvard E. Danielsen, Tarjei S. Hveem   +32 more
wiley   +1 more source

Messy Data Modelling in Health Care Contingent Valuation Studies [PDF]

This study addresses the complexity in modeling contingent valuation surveys with true zeros and non-ignorable missing responses including “don’t knows†and protest responses. An endogenous switching tobit model is specified to simultaneously estimate
Kostas Mavromaras, Mandy Ryan, Maria Ana Odejar   +2 more
core  

Analysing the significance of small conformational changes and low occupancy states in serial crystallographic data

FEBS Open Bio, EarlyView.
This protocol paper outlines methods to establish the success of a time‐resolved serial crystallographic experiment, by means of statistical analysis of timepoint data in reciprocal space and models in real space. We show how to amplify the signal from excited states to visualise structural changes in successful experiments.
Jake Hill, Yelyzaveta Pulnova, Elke De Zitter, Helen M. Ginn, Briony A. Yorke   +4 more
wiley   +1 more source

Proteasomal degradation of intracellularly expressed Amblyomin‐X limits suicide gene therapy potential in melanoma cells

FEBS Open Bio, EarlyView.
This study explores the feasibility of expressing the antitumoral protein Amblyomin‐X through a suicide gene therapy approach and investigates its intracellular fate after gene delivery. Although the gene is efficiently expressed, melanoma cells rapidly degrade the Amblyomin‐X protein via proteasome activity.
Victor Dal Posolo Cinel, Carlos DeOcesano Pereira, Aline Ramos Maia Lobba, Melissa Regina Fessel, Ana Marisa Chudzinski‐Tavassi   +4 more
wiley   +1 more source

Missing Treatments [PDF]

The existing literature on treatment e¤ects assumes perfect observability of the treatments received by the population of interest. Even in cases of imperfect compliance, it is usually as- sumed that both the assigned and administered treatment are ...
Molinari, Francesca
core