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If standard multilevel modelling is used without incorporating such a sampling design, the estimators of parameters may be biased.
In the second stage, multilevel modelling is used to analyse the relationship between privatisation, several measures of individual socioeconomic status and individual income.
Multilevel modelling is especially suitable for the purpose of this paper because it accounts for the hierarchical structure of students within schools while avoiding aggregation bias and the mis-estimation of standard errors (Bryk and Raudenbush 1992; Ferrão 2003; Goldstein 2003).
In this context, our data can be seen as hierarchical data, with repeated measures nested within persons (Hox 2002; Heck and Thomas 2009; Twisk 2006; Scollon et al. 2003) points out that multilevel modelling is useful when analysing panel data because multiple measures are nested in a single individual.
Multilevel modelling is a statistical technique that can be used to correct for this clustering.
The use of multilevel modelling is necessary as it controls for a number of design elements within the study.
Similar(45)
Multilevel modelling was adjusted for cluster (centre) and individual effects.
Multilevel modelling was used to predict decision satisfaction.
Multilevel modelling was used to analyze the data.
The results of multilevel modelling are summarized in Table 4.
Poisson multilevel modelling was conducted of deaths as standardised mortality ratios.
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