A recursive algorithm on estimating the parameters in multilevel models subject to the measurement errors on the covariates

Multilevel models are popular models for analysing data inheriting a hierarchical structure. They are used in diverse fields including social, medical, economical and biological sciences. These models encounter some problems in estimating the parameters, if there are measurement errors in either exp...

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Vydané v:Journal of statistical computation and simulation Ročník 86; číslo 2; s. 252 - 261
Hlavní autori: Golalizadeh, Mousa, Mahmoudnejad, Hashem
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Abingdon Taylor & Francis 22.01.2016
Taylor & Francis Ltd
Predmet:
Algorithms
Computer simulation
Consumer spending
cost and expenditure
Data analysis
Error analysis
Errors
Estimating
iterative algorithm
Mathematical models
measurement error
Measurement errors
Multilevel
multilevel models
Obstacles
Parameter estimation
Simulation
simulation extrapolation
Statistical methods
Teheran Iran
ISSN:0094-9655, 1563-5163
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Popis
Shrnutí:Multilevel models are popular models for analysing data inheriting a hierarchical structure. They are used in diverse fields including social, medical, economical and biological sciences. These models encounter some problems in estimating the parameters, if there are measurement errors in either explanatory or response variables. A common approach to tackle this obstacle is to consider the pseudo variables and follow some simulation methods to estimate the parameters. We propose a new algorithm constituting the iterative and simulation extrapolation steps in turn. To evaluate the proposed algorithm, various simulation studies are also conducted. Moreover, we investigate the implementation of our method on a real data set concerning the cost and expenditure of the households in Tehran city in the year 2007.
Bibliografia:SourceType-Scholarly Journals-1
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ISSN:0094-9655
1563-5163
DOI:10.1080/00949655.2014.1003560