Omitted-Variable Bias

Herausgegeben:Surhone, Lambert M.; Tennoe, Mariam T.; Henssonow, Susan F.

• Broschiertes Buch

Produktbeschreibung

Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online. In statistics, omitted-variable bias (OVB) is the bias that appears in estimates of parameters in a regression analysis when the assumed specification is incorrect, in that it omits an independent variable (possibly non-delineated) that should be in the model.In statistics, linear regression includes any approach to modeling the relationship between a scalar variable y and one or more variables denoted X, such that the model depends linearly on the unknown parameters to be estimated from the data. Such a model is called a linear model . Most commonly, linear regression refers to a model in which the conditional mean of y given the value of X is an affine function of X. Less commonly, linear regression could refer to a model in which the median, or some other quantile of the conditional distribution of y given X is expressed as a linear function of X.

Produktdetails

• Verlag: Betascript Publishing
• Seitenzahl: 76
• Englisch
• Abmessung: 220mm
• ISBN-13: 9786131299735
• ISBN-10: 6131299730
• Artikelnr.: 30120513