Multimediation Method With Balanced Repeated Replications For Analysis Of Complex Surveys

We propose a method suitable for analysis of cross-sectional studies with complex sampling and continuous variables. The method consists of R + 4 steps, where R denotes the number of replications. In the first R + 1 step, the main and R replicate weights are used (one at a time) to estimate the prod...

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Bibliographic Details
Main Authors: Ha, T. (Author), Mai, Y. (Author), Soulakova, J.N (Author)
Format: Article
Language:English
Published: Routledge 2019
Subjects:
Online Access:View Fulltext in Publisher
LEADER 02052nam a2200325Ia 4500
001 10.1080-10705511.2018.1559065
008 220511s2019 CNT 000 0 und d
020 |a 10705511 (ISSN) 
245 1 0 |a Multimediation Method With Balanced Repeated Replications For Analysis Of Complex Surveys 
260 0 |b Routledge  |c 2019 
856 |z View Fulltext in Publisher  |u https://doi.org/10.1080/10705511.2018.1559065 
520 3 |a We propose a method suitable for analysis of cross-sectional studies with complex sampling and continuous variables. The method consists of R + 4 steps, where R denotes the number of replications. In the first R + 1 step, the main and R replicate weights are used (one at a time) to estimate the product of coefficients for all mediation effects using a structural equation model. In step R + 2, the standard errors of these estimates are computed via balanced repeated replications. In step R + 3, the raw p values corresponding to mediation effects are computed based on the generalized Sobel’s tests. In the final step, R + 4, the p values are adjusted for multiplicity and statistical inferences regarding mediation effects are drawn. To illustrate the approach we examined significance of attitudes toward smoking bans as mediators in the association between smoking restrictions at work and nicotine dependence among male daily smokers. © 2019, © 2019 The Author(s). Published with license by Taylor & Francis Group, LLC. 
650 0 4 |a Complex design 
650 0 4 |a Complex designs 
650 0 4 |a Continuous variables 
650 0 4 |a Cross-sectional study 
650 0 4 |a indirect effects 
650 0 4 |a Indirect effects 
650 0 4 |a Smoke 
650 0 4 |a Standard errors 
650 0 4 |a Statistical inference 
650 0 4 |a structural equation modeling 
650 0 4 |a Structural equation modeling 
650 0 4 |a survey sampling 
650 0 4 |a Survey samplings 
650 0 4 |a Surveys 
700 1 |a Ha, T.  |e author 
700 1 |a Mai, Y.  |e author 
700 1 |a Soulakova, J.N.  |e author 
773 |t Structural Equation Modeling