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The multi-subject maps were obtained using a random effect procedure [64] and projected on a single flattened Talairach normalized brain.
Data were analysed using a random effect procedure (Friston et al., 1999).
Therefore, a mixed models design was used in the analyses, with participant ID included as random effect (procedure GENLINMIXED in spss™).
Preceding this analysis, the mean frequency of hand washing in different healthcare sectors was assessed with linear mixed models with healthcare sector as fixed effect and subject identification as random effect (procedure MIXED in spss™).
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The minimization of the error function in each iteration of the "random effects" procedure was performed using the genetic algorithm method.
A random effects procedure was adopted for data analysis.
The fMRI data were analyzed in a two-stage, random effects procedure.
The random effects procedure used (Stata v 9) assumes normal error for the random component.
Imaging data were analysed using Statistical Parametric Mapping (SPM99) employing an event-related model with a two stage random effects procedure.
A drawback of the random effects procedure is that it is performed in two steps: first, the interviewer random effects are estimated from a probit model, and then the interviewer random effects are included in the selection model as the selection variable.
It may also indicate that despite the random-effect procedure, the within- and between-event variabilities are not completely independent.
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