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Part of the book series: Lecture Notes in Statistics ((LNS,volume 86))

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Abstract

We now assume that we have missing values in the second covariate. The observability of X2 is indicated by a random variable

$$O_{2}:\begin{cases} & \text{1 if}\;\;X_{2} \;\;\textup <Emphasis Type="ItalicSmallcaps"> obervable</Emphasis> \\ & \text{0 if}\;\;X_{2} \;\;\textup<Emphasis Type="ItalicSmallcaps"> unobservable</Emphasis> \end{cases}\;\;\;\;2\dagger)$$

and instead of X2 we observe the random variable

$$Z_{2}:=\begin{cases} X_{2} \;\;\textup{if}\;\;O_{2}=1\\ K+1 \;\;\textup{if}\;\;O_{2}=0 \end{cases}$$

with an additional category for missing values. Instead of K + 1 we also use the symbol “?” for this category in the sequel.

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© 1994 Springer-Verlag New York, Inc.

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Vach, W. (1994). Missing Value Mechanisms. In: Logistic Regression with Missing Values in the Covariates. Lecture Notes in Statistics, vol 86. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-2650-5_3

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  • DOI: https://doi.org/10.1007/978-1-4612-2650-5_3

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-0-387-94263-6

  • Online ISBN: 978-1-4612-2650-5

  • eBook Packages: Springer Book Archive

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