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https://doi.org/10.18148/srm/2012.v6i2.5033

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How few countries will do? Comparative survey analysis from a Bayesian perspective

Wie wenige Länder werden es machen? Eine vergleichende Studie
[journal article]

Hox, Joop
Schoot, Rens van de
Matthijsse, Suzette

Abstract

"Meuleman and Billiet (2009) have carried out a simulation study aimed at the question how many countries are needed for accurate multilevel SEM estimation in comparative studies. The authors concluded that a sample of 50 to 100 countries is needed for accurate estimation. Recently, Bayesian estimat... view more

"Meuleman and Billiet (2009) have carried out a simulation study aimed at the question how many countries are needed for accurate multilevel SEM estimation in comparative studies. The authors concluded that a sample of 50 to 100 countries is needed for accurate estimation. Recently, Bayesian estimation methods have been introduced in structural equation modeling which should work well with much lower sample sizes. The current study reanalyzes the simulation of Meuleman and Billiet using Bayesian estimation to find the lowest number of countries needed when conducting multilevel SEM. The main result of our simulations is that a sample of about 20 countries is sufficient for accurate Bayesian estimation, which makes multilevel SEM practicable for the number of countries commonly available in large scale comparative surveys." (author's abstract)... view less

Keywords
data organization; data; data collection method; method; comparative research; estimation; data documentation

Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods

Document language
English

Publication Year
2012

Page/Pages
p. 87-93

Journal
Survey Research Methods, 6 (2012) 2

Issue topic
Theory of human values

ISSN
1864-3361

Status
Published Version; peer reviewed

Licence
Deposit Licence - No Redistribution, No Modifications


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© 2007 - 2025 Social Science Open Access Repository (SSOAR).
Based on DSpace, Copyright (c) 2002-2022, DuraSpace. All rights reserved.