Precision Estimates for AASHTO Test Method T308 and the Test Methods for Performance-Graded Asphalt Binder in AASHTO Specification M320 (2005) / Chapter Skim
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4 CHAPTER 2: ANALYSIS TECHNIQUE 2.1 TECHNIQUE OVERVIEW The analysis method used to determine precision estimates for this study is designed to determine robust estimates of precision representative, as much as possible, of testing performed in accordance with the test standards. The desire is to obtain estimates that will compare favorably to those that might be obtained from a strictly controlled inter-laboratory study.
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5 As shown in Figure 1, the analysis technique employs a four step process. First, null responses and unpaired data (i.e.
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6 ORIGINAL PROFICIENCY DATA PAIRED DATA r paired data set x paired data set y paired data set x valid data set y valid data set VALID DATA CORE DATA x core data set y core data set r valid data set r core data set SRx Sr SRy Unpaired Data Unpaired Data Invalid Data Unpaired Data Invalid Data Outliers Unpaired and null data are identified. Laboratories submitting unpaired or null data are removed.
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7 2.2.2 DETERMINE INVALID DATA (STEP 2) Invalid data are defined as data falling above and below the values IU and IL, respectively; using Equations 2 and 3 based on Hoaglin et al [11,12]
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8 2.2.3 DETERMINE OUTLIERS (STEP 3) Outliers are defined as data falling above and below the values OU and OL, respectively; using Equations 4 and 5 based on Hoaglin et al [11,12]
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9 2.2.4 ANALYSIS OF CORE DATA (STEP 4) Once laboratories submitting either invalid or outlying data are eliminated, traditional standard deviation-type analyses are performed on the remaining data to determine repeatability and reproducibility precision estimates.
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10 2.3 Check for Normality According to ASTM E 177, the multiplier for determining the difference two-sigma (d2s) limits assumes an underlying normal distribution.
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