2020
DOI: 10.22237/jmasm/1556670300
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Using SPSS to Analyze Complex Survey Data: A Primer

Abstract: An introduction to using SPSS to analyze complex survey data is given. Key features of complex survey design are described briefly, including stratification, clustering, multiple stages, and weights. Then, annotated SPSS syntax for complex survey data analysis is presented to demonstrate the step-by-step process using real complex samples data.

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Cited by 57 publications
(43 citation statements)
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“…We attained final SARS-CoV-2 infection prevalence by adding the corrected seroprevalence rate to the rate of current active infection plus the rate of previous documented infection. We also adjusted infection prevalence for DEFF by attributing weights inversely proportional to participants selection probability ( Zou et al, 2020 ).…”
Section: Methodsmentioning
confidence: 99%
“…We attained final SARS-CoV-2 infection prevalence by adding the corrected seroprevalence rate to the rate of current active infection plus the rate of previous documented infection. We also adjusted infection prevalence for DEFF by attributing weights inversely proportional to participants selection probability ( Zou et al, 2020 ).…”
Section: Methodsmentioning
confidence: 99%
“…In order to account for the multi-stage cluster study design, we used SPSS version 25.0 statistical software complex samples package incorporating the following variables in the analysis plan to account for the multistage sample design inherent in the DHS dataset: individual sample weight, sample strata for sampling errors/design, and cluster number [23][24][25]. Analysis was carried out based on the weighted count to account for the unequal probability sampling in different strata and to ensure representativeness of the survey results at the national and regional level.…”
Section: Discussionmentioning
confidence: 99%
“…When running our Complex Samples analyses, McCreary Centre Society supplied us with a plan file containing the complex sampling plan specifications, which was created by Green, Saewyc and Stewart (). For details about this plan file, please see Zou, Lloyd and Baumbusch (in press). Because preliminary analyses showed no substantial design effects, the chi‐square analyses presented for the last objective were performed outside of Complex Samples using weighted and unscaled data, per consultation with McCreary.…”
Section: Methodsmentioning
confidence: 99%