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A Semiparametric Missing-Data-Induced Intensity Method for Missing Covariate Data in Individually Matched Case-Control Studies

Mulugeta Gebregziabher, Bryan Langholz
2009 Biometrics  
Our results indicate that, under the assumption of predictable missingness, the suggested method provides valid estimation of parameters, is more efficient than CCA, and is competitive with other, more  ...  We derive the asymptotic properties of the estimates from the proposed method and, using an extensive simulation study, assess the finite sample performance in terms of bias, efficiency, and 95% confidence  ...  We would like to thank Drs Kiros Berhane and Larry Goldstein for their insights and Wendy Cozen for the data example.  ... 
doi:10.1111/j.1541-0420.2009.01322.x pmid:19751251 pmcid:PMC2910202 fatcat:ahvmnftwxfe3xjjl27e3ag32by

Efficient Integration of Aggregate Data and Individual Patient Data in One-Way Mixed Models [article]

Neha Agarwala, Junyong Park, Anindya Roy
2021 arXiv   pre-print
For many different models design constraints under which the AD estimators are the IPD estimators, and hence fully efficient, are known.  ...  Often both Aggregate Data (AD) studies and Individual Patient Data (IPD) studies are available for specific treatments.  ...  We also look at an interesting application of our novel selection algorithm in the context of the recently popular ‘Split and Conquer’ approach to analysis of ‘Big Data’.  ... 
arXiv:2105.01157v2 fatcat:kichydlapjdlnmiwwguhgyx3fe

Capture–recapture abundance estimation using a semi-complete data likelihood approach

Ruth King, Brett T. McClintock, Darren Kidney, David Borchers
2016 Annals of Applied Statistics  
The semi-complete likelihood approach is flexible and applicable to a range of models, including spatially explicit capture-recapture models.  ...  Model-fitting algorithms to estimate abundance most notably include a numerical approximation for the likelihood or use of a Bayesian data augmentation technique considering the complete data likelihood  ...  1:n , n+1:N } where N is a parameter to be estimated.  ... 
doi:10.1214/15-aoas890 fatcat:msq2mp7ribg75f7iofpzyw5k4q

Data-Driven Modeling and the Influence of Objective Function Selection on Model Performance in Limited Data Regions

Thelma Dede Baddoo, Zhijia Li, Yiqing Guan, Kenneth Rodolphe Chabi Boni, Isaac Kwesi Nooni
2020 International Journal of Environmental Research and Public Health  
The identification of unit hydrographs and component flows from rainfall, evapotranspiration and streamflow data (IHACRES) model has been proven to be an efficient yet basic model to simulate rainfall–runoff  ...  processes due to the difficulty in obtaining the comprehensive data required by physical models, especially in data-scarce, semi-arid regions.  ...  Then the temporal data resolutions are up-scaled or downscaled to compare parameter stability and independence, mostly on a continuous modeling basis and, therefore, cases where sub-daily event data are  ... 
doi:10.3390/ijerph17114132 pmid:32531896 fatcat:taneyyethzf53kvvvlfwsrrj3a

Ice Model Calibration Using Semi-continuous Spatial Data [article]

Won Chang, Bledar A. Konomi, Georgios Karagiannis, Yawen Guan, Murali Haran
2019 arXiv   pre-print
To overcome challenges due to high-dimensionality we use likelihood-based generalized principal component analysis to impose low-dimensional structures on the latent variables for spatial dependence.  ...  Calibration of ice sheet models is often challenging because the relevant model output and observational data take the form of semi-continuous spatial data, with a point mass at zero and a right-skewed  ...  Acknowledgement This material was based upon work partially supported by the National Science Foundation under Grant DMS-1638521 to the Statistical and Applied Mathematical Sciences Institute.  ... 
arXiv:1907.13554v1 fatcat:4yae7zga25fthgrb3ogpkcnolm

Semi-Parametric Models for Longitudinal Data Analysis

Liu Yang, Xu-Feng Niu
2021 Journal of Finance and Economics  
Financial market data is a major component of data analysis; thus, we focus on the financial market in the application part.  ...  The profile kernel estimator and the seemingly unrelated kernel estimator (SUR) will be used to obtain consistent and efficient semi-parametric estimators.  ...  Application Credit card loan data are a major type of financial data owned by banks and other financial institutions and play an important role for longitudinal data analysis as we discussed in the introduction  ... 
doi:10.12691/jfe-9-3-1 fatcat:naih7lnr2zfj3fgrgicwj567xa

Robust and Efficient Parameter Estimation based on Censored Data with Stochastic Covariates [article]

Abhik Ghosh, Ayanendranath Basu
2016 arXiv   pre-print
The resulting estimator also has competitive efficiency with respect to the maximum likelihood estimator under pure data.  ...  In this paper, we propose a robust parametric estimator for the censored data with stochastic covariates based on the minimum density power divergence approach.  ...  Acknowledgments: The authors gratefully acknowledge the comments of two anonymous referees which led to an improved version of the manuscript.  ... 
arXiv:1410.5170v3 fatcat:tkmaf67c6jbxfaix6ezg4msynu

Data Integration by combining big data and survey sample data for finite population inference [article]

Jae-kwang Kim, Siu-Ming Tam
2020 arXiv   pre-print
An advantage of the approach advocated in this paper is that we do not have to make unrealistic missing-at-random assumptions for the methods to work.  ...  Finally, we develop a two-step regression data integration estimator to deal with measurement errors in the probability sample.  ...  Acknowledgements The authors are grateful to two anonymous referees and the co-editor for the very constructive comments.  ... 
arXiv:2003.12156v3 fatcat:64ilctf3vzftdpnkh5ohihixk4

Semiparametric analysis of case series data

C. P. Farrington, H. J. Whitaker
2006 Journal of the Royal Statistical Society, Series C: Applied Statistics  
The case series model for estimating the association between an age-dependent exposure and an outcome event requires information only on cases and implicitly adjusts for all age-independent multiplicative  ...  confounders, while allowing for an age-dependent baseline incidence.  ...  Relative efficiency An attractive feature of the case series method is its limited data requirements compared to other commonly used methods.  ... 
doi:10.1111/j.1467-9876.2006.00554.x fatcat:2mkm4ne6mjezhiylfb5zuanhfa

Nonparametric Bayesian Data Analysis

Fernando A. Quintana, Peter M�ller
2004 Statistical Science  
The discussion follows a list of important statistical inference problems, including density estimation, regression, survival analysis, hierarchical models and model validation.  ...  For each inference problem we review relevant nonparametric Bayesian models and approaches including Dirichlet process (DP) models and variations, Polya trees, wavelet based models, neural network models  ...  Doss (1994) studied an MDP model for survival data subject to more general censoring schemes.  ... 
doi:10.1214/088342304000000017 fatcat:mvoghgfpefej7dwzlj2dfl2poa

Learning Classification with Both Labeled and Unlabeled Data [chapter]

Jean-Noël Vittaut, Massih-Reza Amini, Patrick Gallinari
2002 Lecture Notes in Computer Science  
A key difficulty for applying machine learning classification algorithms for many applications is that they require a lot of handlabeled examples.  ...  text span classification for text summarization to e-mail spam detection and text classification.  ...  Usually, for continuous variables, density components are assumed to be gaussian especially for performing asymptotic analysis.  ... 
doi:10.1007/3-540-36755-1_39 fatcat:tfbjd3q5onacxfzp6qfhxnqoqi

Anomaly Detection Framework for Wearables Data: A Perspective Review on Data Concepts, Data Analysis Algorithms and Prospects

Jithin S. Sunny, C. Pawan K. Patro, Khushi Karnani, Sandeep C. Pingle, Feng Lin, Misa Anekoji, Lawrence D. Jones, Santosh Kesari, Shashaanka Ashili
2022 Sensors  
The continuous monitoring of physiological parameters offers a potential solution to assess personal healthcare.  ...  In this article, we review the nature of the wearables-associated data and the downstream processing methods for detecting anomalies.  ...  Acknowledgments: The authors would like to thank Manasa Tata and Omnia Heikal from Rhenix Lifesciences for their contributions in reviewing the manuscript and preparing the figures, respectively.  ... 
doi:10.3390/s22030756 pmid:35161502 pmcid:PMC8840097 fatcat:nlju2m7btjccxk6xz6tfl6jyt4

Missing data imputation of high‐resolution temporal climate time series data

E Afrifa‐Yamoah, U. A. Mueller, S. M. Taylor, A. J. Fisher
2020 Meteorological Applications  
Analysis of high-resolution data offers greater opportunity to understand the nature of data variability, behaviours, trends and to detect small changes.  ...  It can be concluded that the modelling approaches studied have demonstrated suitability in imputing missing data in hourly temperature, humidity and wind speed data and are therefore recommended for application  ...  The formulation guarantees that the ARIMA models are responsive to the application of the Kalman filter and smoothing for the estimation of the model parameters and the extraction of unobserved components  ... 
doi:10.1002/met.1873 fatcat:lhljazrsibax3omiqe7huywzdm

An overview of approaches to insurance data analysis and suggestions for warranty data analysis

Ming Luo, Shaomin Wu
2016 Recent Patents on Engineering  
The paper concludes with suggestions for improving warranty data analysis.  ...  It then reviews existing approaches to insurance data analysis with regard to modelling of claim frequency, modelling of claim size and policy pricing.  ...  thus is suitable for modelling the semi-continuous claim data.  ... 
doi:10.2174/1872212110666160617092705 fatcat:7pccv7brgbgglbemta2ytnj2pq

Advances in longitudinal data analysis [chapter]

Garrett Fitzmaurice, Geert Molenberghs
2008 Chapman & Hall/CRC Handbooks of Modern Statistical Methods  
parameters could be estimated efficiently via likelihoodbased methods.  ...  For example, to improve upon efficiency, Prentice (1988) proposed joint estimating equations for both the main regression parameters, β, and the nuisance association parameters, α.  ... 
doi:10.1201/9781420011579.pt1 fatcat:yp6cuhnlljat5it4yulletjnvm
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