Definition Specification Error
Contents |
Law Sports and Everyday Life Additional References Home Social sciences Applied and social sciences magazines Specification Error Print this article Print all entries for this topic definition functional specification Cite this article Tools Specification Error International Encyclopedia of the Social definition job specification Sciences COPYRIGHT 2008 Thomson Gale Specification Error BIBLIOGRAPHY In the context of a statistical model, specification error means definition design specification that at least one of the key features or assumptions of the model is incorrect. In consequence, estimation of the model may yield results that are incorrect or
Definition Of Specification In Biology
misleading. Specification error can occur with any sort of statistical model, although some models and estimation methods are much less affected by it than others. Estimation methods that are unaffected by certain types of specification error are often said to be robust. For example, the sample median is a much more robust measure of central tendency than the definition of specification in construction sample mean because it is unaffected by the presence of extreme observations in the sample. For concreteness, consider the case of the linear regression model. The simplest such model is where Y is the regressand, X is a single regressor, U is an error term, and β 0 and β 1 are parameters to be estimated. This model, which is usually estimated by ordinary least squares, could be misspecified in a great many ways. Some forms of misspecification will result in misleading estimates of the parameters, and other forms will result in misleading confidence intervals and test statistics. One common form of misspecification is caused by nonlinearity. According to the linear regression model (1), increasing the value of the regressor X by one unit always increases the expected value of the regressand Y by β 1units. But perhaps the effect of X on Y depends on the level of X. If so, the model (1) is misspecified. A more general model is which includes the square of X as an additional regres
Law Sports and Everyday Life Additional References Home Social sciences Applied and social sciences magazines Specification Error Print this article Print all entries for this topic Cite this article Tools Specification Error International Encyclopedia of the Social Sciences data definition specification COPYRIGHT 2008 Thomson Gale Specification Error BIBLIOGRAPHY In the context of a statistical model,
Algorithm Definition And Specification
specification error means that at least one of the key features or assumptions of the model is incorrect. In consequence, estimation
Fda Definition Of Specification
of the model may yield results that are incorrect or misleading. Specification error can occur with any sort of statistical model, although some models and estimation methods are much less affected by it than others. http://www.encyclopedia.com/doc/1G2-3045302564.html Estimation methods that are unaffected by certain types of specification error are often said to be robust. For example, the sample median is a much more robust measure of central tendency than the sample mean because it is unaffected by the presence of extreme observations in the sample. For concreteness, consider the case of the linear regression model. The simplest such model is where Y is the regressand, X is a http://www.encyclopedia.com/doc/1G2-3045302564.html single regressor, U is an error term, and β 0 and β 1 are parameters to be estimated. This model, which is usually estimated by ordinary least squares, could be misspecified in a great many ways. Some forms of misspecification will result in misleading estimates of the parameters, and other forms will result in misleading confidence intervals and test statistics. One common form of misspecification is caused by nonlinearity. According to the linear regression model (1), increasing the value of the regressor X by one unit always increases the expected value of the regressand Y by β 1units. But perhaps the effect of X on Y depends on the level of X. If so, the model (1) is misspecified. A more general model is which includes the square of X as an additional regressor. In many cases, a model like (2) is much less likely to be misspecified than a model like (1). A classic example in economics is the relationship between years of experience in the labor market (X ) and wages (Y ). Whenever economists estimate such a relationship, they find that β 1 is positive and β 2 is negative. If the relationship between X and Y really is nonlinear, and the sample contains a reasonable
findings, especially studies that use predictive (multiple regression, causal modeling). So, below is a definition with an analogy from a 2005 publication. This is one of the most series problem with http://www.iqscorner.com/2011/09/what-is-specification-error-in-research.html many research studies that claim to have identified THE important predictors of some http://www.ni.com/white-paper/4439/en/ dependent variable (e.g, reading disability research)Double click on images to enlarge- iPost using BlogPress from Kevin McGrew's iPad Posted by Kevin McGrew at 10:53 AM Email ThisBlogThis!Share to TwitterShare to FacebookShare to Pinterest Labels: Specification error No comments: Post a Comment Newer Post Older Post Home Subscribe to: Post Comments (Atom) About Me definition of Kevin McGrew Dr. Kevin McGrew is Director of the Institute for Applied Psychometrics (llc). Additional information, including potential conflicts of interest resulting from commercial test development or other consultation, can be found at The MindHub(TM; http://www.themindhub.com ). General email contact is iap@earthlink.net. View my complete profile This is an IAP blog Click for IAP home page Purpose,Passion & Serendipity Click on image to visit Google definition of specification Page Rank IQs Corner fun stuff Time for some fluid intelligence (Gf) Classic White Coffee Mug by IQsCorner More Intelligence Mugs CHC IQ related t-shirts designed by Dr. Kevin "IQ" McGrew CHC Periodic Table T-shirt @ Skreened store Click on shirt to see large version of image and learn more About this blog and blogger Why IQ's Corner blog? The MindHub K. McGrew LinkedIn profile K. McGrew Bio K. McGrew CV K. McGrew Conflict of Interest Disclosure IQMobile @ Twitter Institute for Applied Psychometrics (IAP) Brain Clock blog Atkins MR/ID Intellectual Competence & Death Penalty blog Twitter Updates Twitter Updates follow me on Twitter Subscribe to IQ's Corner Daily Newspaper Follow by Email Save Page to PDF File IQs Corner Recognized Psychology Today Interview Scientific American-Mind Top 101 brain blog 2008 Top 50 Blog by Psychology Professionals Key projects, features and articles WJ IV Evolving Web of Knowledge (EWOK) "Intelligent" intelligence testing with the WJ IV COG Beyond CHC and the WJ III: Pushing the edge of the envelope Beyond IQ project CHC COG-ACH correlates res. synthesis CHC Intelligence Theory Ability Model and Definitions: CHC v2.0 (June 2011) CHC Timeline Project CHC theory ability definitions-brief
Федерация 中国 (China) 日本 (Japan) 대한민국 (Korea) 台灣 (Taiwan) See All Countries Toggle navigation INNOVATIES WEBSHOP ONDERSTEUNING COMMUNITY Nederland Understanding Instrument Specifications -- How to Make Sense Out of the Jargon Publish Date: jun 21, 2007 | 99 Ratings | 3,80 out of 5 | Print Overview This tutorial is part of the National Instruments Measurement Fundamentals series. Each tutorial in this series will teach you a specific topic of common measurement applications by explaining theoretical concepts and providing practical examples. For more information, return to the NI Measurement Fundamentals Main page. For many years, multifunction data acquisition boards have given engineers and scientists an interface between transducers and computers. These boards, which are designed for a wide range of applications, are used in a variety of applications from dynamometer control to CD player testing. Because of developments in component and computer technologies, it is now possible to build computer-based measurement systems that rival -- and at times exceed -- the performance of systems based on traditional boxed instruments. Traditionally, data acquisition boards and stand-alone instruments have been specified by using either different terminology or similar terminology with different meanings. This application note resolves this issue by providing clear definitions for specification parameters such as NMRR, CMRR, and ECMRR (just to name a few) and illustrates how these specifications directly influence your measurements. We begin by providing a strictly technical definition for each of the key parameters that you are likely to come across when specifying your measurement system. We then cover some common mistakes and conclude with a suggested error budget template. Table of Contents Definitions Resolution, Precision, Accuracy Error Calculation or Accuracy Determination Conclusion Relevant NI Products 1. Definitions Resolution -- the smallest amount of input signal change that the instrument can detect reliably. This term is determined by the instrument noise (either circuit or quantization noise). For example, if you have a noiseless voltmeter that has 5 1/2 digits displayed and is set to the 20 V input range, the resolution of this voltmeter is 100 µV. This can be determined by looking at the change associated with the least significant digit. Now, if this same voltmeter had 10 counts of peak-to-peak noise, the effective resolution would be decreased because of the presence of the noise. Because of the Gaussian distribu