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Data were evaluated through frequencies, percentages, ratios, chi-square statistics.
Data were evaluated through ANOVA (P < 0.05).
Clinical and access data were systematically entered in a database while acceptance and organisational data were evaluated through ad hoc questionnaires.
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The overall fit of the model to the data was evaluated through Chi square statistics, goodness-of-fit index (GFI), comparative fit index (CFI), normed fit index (NFI), incremental fit index (IFI), standardized root mean square residual (SRMR), and root mean square error of approximation (RMSEA).
Genotype data was evaluated through Stanford University algorithm.
The normal distribution of quantitative data was evaluated through the D'Agostino test.
The data are evaluated through the hypothesis test in which the void hypothesis equals the average and the alternative is the difference between them.
The gravimetric measurement data were evaluated two ways: (1) through eq 1 where N = 200 bursts, which gave 486 ng (RSD = 2.3%) per burst, and (2) through eq 2 where f = 0.858 Hz, which gave 479 ng (RSD = 1.9%) per burst.
Data were evaluated with Statistica (StatSoft, Tulsa, OK), through scatter and frequency distribution plots and K-means cluster analysis with parameters set to maximize initial between-cluster distances.
For sensitivity analyses that required either a one year preview or one year follow-up period after the first IIM service date, patient data were evaluated starting in 2003 and extending through 2009.
These data were evaluated twice a week during a 30-day period through medical charts.
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