Latent variable modelling with non‐ignorable item non‐response: multigroup response propensity models for cross‐national analysis
نویسندگان
چکیده
منابع مشابه
Correcting for Survey Nonresponse Using Variable Response Propensity
All surveys with less than full response potentially suffer from nonresponse bias. Poststratification weights can only correct for selection into the sample based on observables whose distribution is known in the population. Variables such as gender, race, income, and region satisfy this requirement because they are available from the U.S. Census Bureau, but poststratification based on these va...
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Traditional weight adjustments for survey sampling error are often constructed through multiple stages, where design weights are based on the inverse of the probability of selection, and in a separate stage nonresponse adjustments are derived from weighting cells or classes, or based on model-deduced response propensities. More recent efforts by Little and Vartivarian (2003) have advocated the ...
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Missing data usually present special problems for statistical analyses, especially when the data are not missing at random, that is, when the ignorability principle defined by Rubin (1976) does not hold. Recently, a substantial number of articles have been published on model-based procedures to handle nonignorable missing data due to item nonresponse (Holman & Glas, 2005; Glas & Pimentel, 2008;...
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Log-linear models have been shown to be useful for smoothing contingency tables when categorical outcomes are subject to nonignorable nonresponse. A log-linear model can be fit to an augmented data table that includes an indicator variable designating whether subjects are respondents or nonrespondents. Maximum likelihood estimates calculated from the augmented data table are known to suffer fro...
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ژورنال
عنوان ژورنال: Journal of the Royal Statistical Society: Series A (Statistics in Society)
سال: 2018
ISSN: 0964-1998,1467-985X
DOI: 10.1111/rssa.12350