Two algorithms for producing multiple imputations for missing data are evaluated with simulated data. Software using a propensity score classifier with the approximate Bayesian boostrap produces badly biased estimates of regression coefficients when data on predictor variables are missing at random or missing completely at random. On the other hand, a regression-based method employing the data ...

Models for survival data generally assume that covariates are fully observed. However, in medical studies it is not uncommon for biomarkers to be censored at known detection limits. A computationally-efficient multiple imputation procedure for modeling survival data with covariates subject to detection limits is proposed. This procedure is developed in the context of an accelerated failure time...

Media mix modeling is a statistical analysis on historical data to measure the return on investment (ROI) on advertising and other marketing activities. Current practice usually utilizes data aggregated at a national level, which often suffers from small sample size and insufficient variation in the media spend. When sub-national data is available, we propose a geo-level Bayesian hierarchical m...

Missing data are common wherever statistical methods are applied in practice. They present a problem in that they require that additional assumptions be made about the mechanism leading to the incompleteness of the data. By incorporating two models for the missing data process, doubly robust (DR) weighting-based methods offer some protection against misspecification bias since inferences are va...

from the perspective of the states that their foreign policy is based on geo-economy, the economy is the most important mechanism of influence in target areas. therefore, with the strengthening of trade relations would be in an appropriate level to increase the mutual relations.  after the independence of central eurasian states, geographical - political events of central eurasia led to the cre...

A Sensor Web (SW) consists of a large collection of small nodes providing collaborative and distributed sensing abilities in unpredictable environments. Nodes composing such a SW are characterized by resource restrictions, especially energy, processing power, and communication capacities. A sensor web can be thought of as a spatially and functionally distributed complex system evolving in and i...

A dividend imputation tax system provides shareholders with a tax credit that can be used to offset personal tax on dividend income. The size of this credit depends on tax paid at the corporate level so that the “double taxation” of dividends is effectively eliminated. This paper shows how to infer the value of imputation tax credits (which is an important input into the weighted-average cost o...

We deal with the effect of missing data under a ”Missing at Random Model” on classification of variables with non hierarchical methods. The partitions are compared by the Rand’s index.

Economists are giving more attention to the issue of subjective well-being. This study examines the factors that determine financial well-being for households in Oklahoma County, Oklahoma, using multiple imputation to estimate missing survey values. The study is motivated by the availability of extensive household-level data for a six year period for Oklahoma County.

In this paper, we develop analytic techniques that can be used to produce appropriate inferences from a data set in which imputation for missing values has been carried out using predictive means. Our derivations are based on asymptotic expansions of point estimators and their associated variance estimators, and the resulting formulas can be thought of as first-order approximations to the estim...