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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.
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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.
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).
An association analysis was conducted in the German Holstein-Friesian population to test the association between the single nucleotide polymorphism (SNP) at position +777 within the CXCR1 gene and the SNP at position −1768 in the 5′ upstream region of this gene (rs41255711) and the indicator trait SCS by using a granddaughter design.
In summary, visualized ratiometric pH indicator was fabricated by using a fluorescent dye (FITC) and a phosphorescent dye (Ru phen 3 2+).
Assessment of the initial 84 potential quality indicators was done by using a RAND-modified Delphi method.
Lactate dehydrogenase (LDH) was measured as an indicator of cell death by using a cytotoxicity detection kit (Roche; Applied Science, Barcelona, Spain).
The selection of the organic rankine cycle design is based on techno-economic indicators and is done by using a qualification utility function for the population of solutions on the Pareto curve.
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