Results 21 to 30 of about 576,589 (159)
Propensity Score Weighting for Causal Inference with Clustered Data
Journal of Causal Inference, 2018 Propensity score weighting is a tool for causal inference to adjust for measured confounders in observational studies. In practice, data often present complex structures, such as clustering, which make propensity score modeling and estimation challenging.
Yang Shu
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CoRRThe reconstruction of unknown functions from a finite number of samples is a fundamental challenge in pure and applied mathematics. This survey provides a comprehensive overview of recent developments in sampling recovery, focusing on the accuracy of various algorithms and the relationship between optimal recovery errors, nonlinear approximation, and ...
Feng Dai, Vladimir N. Temlyakov
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Robust Särndal-Type Mean Estimators with Re-Descending Coefficients
AxiomsWhen extreme values or outliers occur in asymmetric datasets, conventional mean estimation methods suffer from low accuracy and reliability. This study introduces a novel class of robust Särndal-type mean estimators utilizing re-descending M-estimator ...
Khudhayr A. Rashedi +7 more
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Interactive Linear Models in Survey Sampling [PDF]
Journal of Statistical Theory and Applications (JSTA), 2014 Considered is a linear ‘interactive’ model in the context of survey sampling. This situation arises when investigator and/or supervisor interventions are contemplated in the responses.
Bikas K. Sinha, Pulakes Maiti
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Application of Randomized Response Techniques Using Dichotomous Response for Mean Wage in Czechia and Slovakia [PDF]
Statistika: Statistics and Economy JournalResearch of controversial topics (drug consumption, corruption) requires reliable estimates of population means of sensitive variables (spending on drugs, illegal sources of income). To avoid non-response and fabricated responses surveys using randomized
Ondřej Vozár, Luboš Marek
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Preventive Oncology & EpidemiologyBackground:The Together for Health-Virginia (T4H-VA) Research Program aimed to advance cancer prevention, education, and outreach in Virginia. Creating a representative and inclusive cohort is critical to the program’s mission and quality of outcomes ...
Bernard F. Fuemmeler +9 more
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Resampling methods in survey sampling
Lietuvos Matematikos Rinkinys, 2000 Aim of this paper is to estimate variances of the estimates of the population totals using resampling methods and to compare them with the known variances of the estimates.
Danutė Krapavickaitė +1 more
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Statistical Theory and Related Fields, 2019 The goals of any major business transformation programme in an official statistical agency often include improving data collection efficiency, data processing methodologies and data quality.
Xichuan (Mark) Zhang +2 more
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On Bootstrap Algorithms in Survey Sampling
Zeszyty Naukowe Uniwersytetu Ekonomicznego w KrakowieObjective: The aim of this paper is to present bootstrap algorithms for measuring the accuracy of estimation and prediction in design-based and model-based approaches in survey sampling and small area estimation.
Tomasz Żądło
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ComTech, 2014 As a Free Trade Zone (FTZ), the province of Riau Islands has a different pattern of strategic commodity (such as rice) marketing comparing to other regions in Indonesia. To anticipate and control the negative effects of the implementation of FTZ policy,
Herena Pudjihastuti
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