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Measurement error models.
Author:
ISBN: 0470095717 9780470095713 Year: 2006 Publisher: Hoboken John Wiley & sons

Disturbances in the linear model, estimation and hypothesis testing
Author:
ISBN: 9020707728 1468469568 0898380944 9789020707724 Year: 1978 Publisher: Leiden Nijhoff Social Sciences Division

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Abstract

1. 1. The general linear model All econometric research is based on a set of numerical data relating to certain economic quantities, and makes infer­ ences from the data about the ways in which these quanti­ ties are related (Malinvaud 1970, p. 3). The linear relation is frequently encountered in applied econometrics. Let y and x denote two economic quantities, then the linear relation between y and x is formalized by: where {31 and {32 are constants. When {31 and {32 are known numbers, the value of y can be calculated for every given value of x. Here y is the dependent variable and x is the explanatory variable. In practical situations {31 and {32 are unknown. We assume that a set of n observations on y and x is available. When plotting the ob­ served pairs (x l' YI)' (x ' Y2)' . . . , (x , Y n) into a diagram with x 2 n measured along the horizontal axis and y along the vertical axis it rarely occurs that all points lie on a straight line. Generally, no b 1 and b exist such that Yi = b + b x for i = 1,2, . . . ,n. Unless 2 l 2 i the diagram clearly suggests another type of relation, for instance quadratic or exponential, it is customary to adopt linearity in order to keep the analysis as simple as possible.

Theory of the combination of observations least subjects to errors
Authors: ---
ISBN: 0898713471 9780898713473 Year: 1995 Volume: 11 Publisher: Philadelphia (Pa.): SIAM

Real computing made real : preventing errors in scientific and engineering calculations
Author:
ISBN: 0691036632 9780691036632 Year: 1996 Publisher: Princeton (N.J.): Princeton university press


Book
Latent class analysis of survey error
Author:
ISBN: 9780470289075 9780470891155 9780470891148 0470289074 0470891157 0470891149 Year: 2011 Publisher: Hoboken, N.J Wiley

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Abstract

"This book concerns the error in data collected using sample surveys, the nature and magnitudes of the errors, their effects on survey estimates, how to model and estimate the errors using a variety of modeling methods, and, finally, how to interpret the estimates and make use of the results in reducing the error for future surveys. The book focuses on models that are appropriate for categorical data, although there are references to the differences and special problems that arise in the analysis and modeling of error for continuous data. Though the primary modeling method that is described is latent class analysis (LCA), a wide range of related models and applications are also discussed"

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