ST 790 Statistical Methods for Analysis With Missing Data
نویسندگان
چکیده
منابع مشابه
Performance evaluation of different estimation methods for missing rainfall data
There are numerous methods to estimate missing values of which some are used depending on the data type and regional climatic characteristics. In this research, part of the monthly precipitation data in Sarab synoptic station, east Azerbaijan province, Iran was randomly considered missing values. In order to study the effectiveness of various methods to estimate missing data, by seven classic s...
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Data missing, which occurs for different reasons, is an unavoidable problem in epidemiological studies. It is quite widespread and, therefore, it is considered as a challenge in research design and data analysis by many methodologists. Complete case analysis is often used in studies with missing data however, this approach may result in inaccurate estimates and inferences due to bias associated...
متن کاملA blended model for estimating of missing precipitation data (Case study of Tehran - Mehrabad station)
Meteorological stations usually contain some missing data for different reasons.There are several traditional methods for completing data, among them bivariate and multivariate linear and non-linear correlation analysis, double mass curve, ratio and difference methods, moving average and probability density functions are commonly used. In this paper a blended model comprising the bivariate expo...
متن کاملMarginal Analysis of A Population-Based Genetic Association Study of Quantitative Traits with Incomplete Longitudinal Data
A common study to investigate gene-environment interaction is designed to be longitudinal and population-based. Data arising from longitudinal association studies often contain missing responses. Naive analysis without taking missingness into account may produce invalid inference, especially when the missing data mechanism depends on the response process. To address this issue in the ana...
متن کاملMissing Data in Randomized Clinical Trials for Weight Loss: Scope of the Problem, State of the Field, and Performance of Statistical Methods
BACKGROUND Dropouts and missing data are nearly-ubiquitous in obesity randomized controlled trails, threatening validity and generalizability of conclusions. Herein, we meta-analytically evaluate the extent of missing data, the frequency with which various analytic methods are employed to accommodate dropouts, and the performance of multiple statistical methods. METHODOLOGY/PRINCIPAL FINDINGS...
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تاریخ انتشار 2015