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In the identification stage, we determined the need for differencing the monthly BFV incidences by checking stationarity (i.e., trends in the mean and variance) and the order of both the seasonal and non-seasonal autoregressive and moving-average indicators by using an autocorrelation function and a partial autocorrelation function (Hipel et al. 1977).
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To investigate the effect of the withdrawal of the incentive on practices' performance, we reconstructed the relevant indicators by using a large primary care database, the Clinical Practice Research Datalink CPRDD).
This external and independent testing would also demonstrate whether we may have missed any relevant indicators by using a pre-existing framework or by being closely involved in the case studies.
The goal of the analysis was to assess the effect of each independent variable on each of the HRQOL indicators by using a multivariable logistic regression (MLR) modelling procedure.
Spectrum estimates the uncertainty around the estimate of each indicator by using a Monte Carlo approach.
With variable model estimation, we drew a trend line for each health-related indicator by using a logarithmic or linear approximation with six time points referencing 1996, 1999, 2002, 2005, 2008, and 2011.
The Li-thermal method performed very poorly because of the overestimation of mean indicator transit time by using an external lithium ion electrode.
These indicators were quantified and integrated by using an exploratory factor analysis (Costello and Osborne, 2005; Child, 2006; Preacher et al., 2013).10.
In the AP selection phase, the MN evaluates all nearby APs, by using an indicator such as signal strength.
During the repeated process, the external pushing force was monitored by using an indicator with load cell (BONGSHIN, Inc. Seoul, South Korea).
In this setting, better results might be achieved by using an indicator independent from thermal signals.
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