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Whether single or multiple measures are finally agreed on, the data they provide should eventually merge with other health records, such as the proposed mental health minimum dataset and electronic patient records.
In these settings, multiple measures are usually introduced with apparently successful results.
Specifically, four image quality approaches and a biometric quality approach (that may each contain multiple measures) are considered for the evaluation.
As Black and Smith (2006) note, the high degree of correlation between different measures of peer ability make it difficult to interpret individual coefficient estimates for specific measures when multiple measures are included in the empirical model.
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.
The patterns of concurrency they display – defined across multiple measures – are distinct, and consistent with the epidemics that unfolded in each population.
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Multiple measures were taken to ensure quality qPCR data.
Given the complex nature of dating and dating relationships, multiple measures were utilized in these analyses.
Multiple measures were adopted to prevent and control rockbursts, including the prediction and early warning measures, stress relief by blasting in advance, optimized blasting design and optimized tunnel support in the tunnel sections prone to strong rockbursts.
Although we focus on the analysis of multichannel spike train data the metrics we describe are applicable to any stationary time series in which causal relationships among multiple measures is desired.
Multiple measures were undertaken to exclude contamination and potential artifactual DNA changes (including post-mortem damage).
More suggestions(15)
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