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Three Essays on Matching Estimators
Flossmann, Anton - 2008
This dissertation is a collection of three stand-alone research papers. Thereby, the class of local polynomial matching estimators is the central object of investigation. The first essay concentrates on applying local polynomial matching methods in order to account for missing data when...
Persistent link: https://www.econbiz.de/10009471602
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Gender Equality in Central and Eastern Europe : A Comparison of Labour Market Attitudes, Educational Achievement and Poverty between East and West
Schnepf, Sylke Viola - 2005
tremendous increase in poverty and income inequality in Central and Eastern Europe (CEE). Much of the literature argues that the …’s economic empowerment: the labour market, education and poverty. Large and complex data sets on peoples’ attitudes and … greater in transition than in OECD countries.On the other hand, once the feminisation of poverty is concerned data on …
Persistent link: https://www.econbiz.de/10009449678
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Bayesian model estimation and comparison for longitudinal categorical data
Tran, Thu Trung - 2008
In this thesis, we address issues of model estimation for longitudinal categorical data and of model selection for these data with missing covariates. Longitudinal survey data capture the responses of each subject repeatedly through time, allowing for the separation of variation in the measured...
Persistent link: https://www.econbiz.de/10009437884
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Model selection criteria in the presence of missing data based on the Kullback-Leibler discrepancy
Sparks, JonDavid - 2009
An important challenge in statistical modeling involves determining an appropriate structural form for a model to be used in making inferences and predictions. Missing data is a very common occurrence in most research settings and can easily complicate the model selection problem. Many useful...
Persistent link: https://www.econbiz.de/10009466074
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Multiple Imputation for Measurement Error Correction Based on a Calibration Sample.
Guo, Ying - 2010
In much of applied statistics variables of interest are measured with error. In particular, regression with covariates that are subject to measurement error requires adjustment to avoid biased estimates and invalid inference. We consider two aspects of this problem. Detection Limits (DL) arise...
Persistent link: https://www.econbiz.de/10009476534
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Missing Covariates in Longitudinal Data with Informative Dropouts: Bias Analysis and Inference
Roy, Jason; Lin, Xihong - 2005
We consider estimation in generalized linear mixed models (GLMM) for longitudinal data with informative dropouts. At the time a unit drops out, time-varying covariates are often unobserved in addition to the missing outcome. However, existing informative dropout models typically require...
Persistent link: https://www.econbiz.de/10009476551
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Some Topics in Missing Data and Adaptive Confidence Intervals. Some Topics in Missing Data and Adaptive Confidence Intervals.
Zhou, Yan - 2009
When data are missing at random, the missing-data mechanism can be ignored but this assumption is not always intuitive for general patterns of missing data. In part I, we consider maximum likelihood (ML) estimation for a non-ignorable mechanism which is called almost missing at random (AMAR). We...
Persistent link: https://www.econbiz.de/10009476653
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Latent Variable Models for Longitudinal Data with Multiple Continuous Outcomes
Roy, Jason; Lin, Xihong - 2000
variables are also calculated. This method is illustrated using data from a national panel study on changes in methadone …
Persistent link: https://www.econbiz.de/10009476960
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Using Auxiliary Time-Dependent Covariates to Recover Information in Nonparametric Testing with Censored Data
Murray, Susan; Tsiatis, Anastasios A. - 2001
Murrayand Tsiatis (1996) described a weighted survival estimate thatincorporates prognostic time-dependent covariate informationto increase the efficiency of estimation. We propose a test statisticbased on the statistic of Pepe and Fleming (1989, 1991) thatincorporates these weighted survival...
Persistent link: https://www.econbiz.de/10009477089