1 Based on intra- (97 to 100%) and
interlaboratory (
94 to 95%) agreement for both drugs, th
2 The median
interlaboratory accuracy and precision of the assay for
3 Analysis of 3,420 MICs demonstrated higher
interlaboratory agreement (percentage of MIC pairs withi
4 Interlaboratory agreement among MICs (i.e., mode +/- 1 t
5 Excellent
interlaboratory agreement among the results obtained at
6 High
interlaboratory agreement and precision of CAP/CTM CMV t
7 Interlaboratory agreement based on interpretive category
8 of WHO quantitative standards would improve
interlaboratory agreement for viral load testing; howeve
9 Interlaboratory agreement in determining seropositivity
10 ility study, 9 of 15 clinical strains showed
interlaboratory agreement of >90% at the 80% inhibition
11 the QC study, 4 of the 6 ATCC strains showed
interlaboratory agreement of >90%.
12 The overall
interlaboratory agreement of 24-h visual readings and 48
13 The present study evaluated the
interlaboratory agreement of the results for the microdi
14 We conducted an intralaboratory and
interlaboratory agreement study to assess the accuracy a
15 Both intra- and
interlaboratory agreement was 100%.
16 The overall pairwise
interlaboratory agreement was 97.7%.
17 aluation of growth inhibition) on intra- and
interlaboratory agreement was analyzed.
18 Excellent
interlaboratory agreement was observed with the challeng
19 Good
interlaboratory agreement was observed with the LFD, as
20 ME1111 demonstrated excellent
interlaboratory agreement when tested against dermatophy
21 on and typing assays demonstrating excellent
interlaboratory agreement will allow investigators to be
22 Based on
interlaboratory agreement, the optimal testing condition
23 As part of continuing cooperation to improve
interlaboratory agreement, we are preparing bulk serum c
24 lations and MIC endpoint criteria to improve
interlaboratory agreement.
25 Both intra- and
interlaboratory agreements were >98% for all three drugs
26 Our objective was to evaluate the
interlaboratory and interstudy reproducibility and the e
27 This is the first
interlaboratory assessment of a widely used, targeted me
28 These
interlaboratory challenge data illuminate the relative i
29 The Mixed Stain Study 3 (MSS3)
interlaboratory challenge exercise evaluated the 2001 pe
30 plasma from healthy individuals) the median
interlaboratory coefficient of variation (CV) was 7.6%,
31 ide enrichment program to facilitate uniform
interlaboratory collaboration and exchange of phosphopro
32 d minimizing potential inconsistencies among
interlaboratory comparative studies.
33 An
interlaboratory comparison (ILC) was organized with the
34 nd well characterized, and should facilitate
interlaboratory comparison and standardization.
35 S (GC-qMS), where GC-qMS was validated in an
interlaboratory comparison between Munich and Neuchatel
36 Results from the
interlaboratory comparison demonstrated that most quanti
37 centrations derived from the NIST Lipidomics
Interlaboratory Comparison Exercise.
38 Technology (NIST) has administered nearly 40
interlaboratory comparison exercises devoted to fat-solu
39 articipant measurement performance in single
interlaboratory comparison exercises; we here apply and
40 The related
interlaboratory comparison involved 13 expert laboratori
41 ging concern (CECs) was performed through an
interlaboratory comparison involving 25 research and com
42 An
interlaboratory comparison of a protocol consisting of m
43 ntration, and therefore we also conducted an
interlaboratory comparison of methods for urinary creati
44 chniques utilized may be applicable to other
interlaboratory comparison programs.
45 This paper presents the first post hoc
interlaboratory comparison study of the spICP-MS techniq
46 An
interlaboratory comparison study was also conducted usin
47 e-of-flight mass spectrometry (MALDI-TOF MS)
interlaboratory comparison was conducted on mixtures of
48 The
interlaboratory comparison was designed to see how well
49 mantic and graphical tools developed to help
interlaboratory-
comparison-exercise participants interpr
50 sampling techniques and proposes a model for
interlaboratory comparisons across current cytokine dete
51 While PFGE is state-of-the-art,
interlaboratory comparisons are difficult because the re
52 Interlaboratory comparisons are reported on a dry mass b
53 m, rapid, and reliable, it is well suited to
interlaboratory comparisons during epidemiological inves
54 cal or experimental bias, allowing realistic
interlaboratory comparisons of subtle biomarker informat
55 The performance characteristics and
interlaboratory comparisons of the T-cell flow cytometry
56 s/mL into IU/mL for HDVL standardization and
interlaboratory comparisons.
57 , thus providing greater confidence in these
interlaboratory comparisons.
58 ng isolates of P. marneffei and facilitating
interlaboratory comparisons.
59 or antiretinal antibodies detection and poor
interlaboratory concordance make the diagnosis challengi
60 e median assay precision was 5.4%, with high
interlaboratory correlation (R(2) > 0.96).
61 Interlaboratory correlations, likewise, ranged between 0
62 ay CV 13.21%), and a strong correlation upon
interlaboratory cross validation with an existing immuno
63 with 85% of metabolites exhibiting a median
interlaboratory CV of <20%.
64 ystem, and simplifies method development and
interlaboratory data alignment.
65 It has enabled the direct comparison of
interlaboratory data as well as quality control in clini
66 differences ( P < 0.05) derived from pooled
interlaboratory data varied from 1.5- to 26-fold dependi
67 These
interlaboratory differences (8 of 30 parameters) far out
68 Interlaboratory differences across runs were </=0.10 log
69 Interlaboratory differences were more marked than intral
70 Interlaboratory differences, however, probably due to re
71 mance even for strains with higher levels of
interlaboratory discordance.
72 ommercially prepared antisera and intra- and
interlaboratory discrepancies arising from differences i
73 An
interlaboratory evaluation (two centers) of the Etest me
74 on detection methods participated in a blind
interlaboratory evaluation of a prototype of SRM 2394.
75 An
interlaboratory evaluation of the amplification, sequenc
76 of 465 isolates were examined for intra- and
interlaboratory identification reproducibility and gave
77 tute of Standards and Technology is enhanced
interlaboratory measurement comparability for fat-solubl
78 ave been validated (to within 6% or less) by
interlaboratory measurements at three National Measureme
79 ate the accuracy of intra/intertechnique and
interlaboratory measurements, samples of phosphate buffe
80 Interlaboratory MICs for all isolates were in 92 to 100%
81 An important aspect of this is the
interlaboratory precision (reproducibility) of the analy
82 amples 82% of metabolite measurements had an
interlaboratory precision of <20%, while 83% of averaged
83 ication (LOQ), and measurement of intra- and
interlaboratory precision.
84 An
interlaboratory quality control (QC) program for pneumoc
85 Interlaboratory reliability for HPV DNA positivity and H
86 To date, however, the intra- and
interlaboratory reliability of this procedure has not be
87 However, the
interlaboratory replicability of these assays has not be
88 Interlaboratory reproducibility among MICs was most vari
89 The approach shows
interlaboratory reproducibility and allows for the excha
90 new CGA-specific PCR assay, which exhibited
interlaboratory reproducibility and stability under vari
91 The overall
interlaboratory reproducibility by each method was > or
92 ulticenter study was conducted to assess the
interlaboratory reproducibility of broth microdilution t
93 icenter study was performed to establish the
interlaboratory reproducibility of Etest, to provide an
94 d, 8 independent laboratories determined the
interlaboratory reproducibility of ME1111 susceptibility
95 s prospective multicenter study compares the
interlaboratory reproducibility of PZA susceptibility re
96 ulticenter study was conducted to assess the
interlaboratory reproducibility of susceptibility testin
97 The
interlaboratory reproducibility of the results for two c
98 The
interlaboratory reproducibility of YeastOne and referenc
99 Here we report results of a large
interlaboratory reproducibility study of ultra performan
100 The correlation coefficient for an
interlaboratory reproducibility study was 0.9892.
101 ungin) to 100% (caspofungin, micafungin) and
interlaboratory reproducibility was 99%.
102 In contrast, better
interlaboratory reproducibility was determined between f
103 Excellent overall
interlaboratory reproducibility was observed with the Vi
104 teen laboratories participated in a study of
interlaboratory reproducibility with caspofungin microdi
105 six-center) study evaluated the performance (
interlaboratory reproducibility, compatibility with refe
106 tegy for Aspergillus fumigatus subtyping for
interlaboratory reproducibility.
107 Differences in
interlaboratory research protocols contribute to the con
108 ruments located in independent laboratories (
interlaboratory RSD < 3% for 98% of molecules).
109 This study assessed
interlaboratory sensitivity and reproducibility in the a
110 24 h in RPMI 1640 or AM3 also gave the best
interlaboratory separation of Candida isolates of known
111 Intra- and
interlaboratory spectral reproducibility yielded a diffe
112 The observed
interlaboratory standard deviation (SD) associated with
113 As with any molecular identifier,
interlaboratory standardization must precede broad range
114 method has been validated through intra- and
interlaboratory studies and has shown excellent recoveri
115 Interlaboratory studies in rodents using standardized pr
116 behavior is often presented as a property of
interlaboratory studies, which makes controlled replicat
117 orwitz scaling, which has been reported from
interlaboratory studies.
118 eatments plants (STPs) and the results of an
interlaboratory study (ILS), respectively.
119 Project on Advanced Materials and Standards)
interlaboratory study for desorption electrospray ioniza
120 eed, two immunoassays have been tested in an
interlaboratory study for their capability to detect rum
121 The low RSD and biases observed in this
interlaboratory study illustrate the potential of DTIM-M
122 performance of the assay was evaluated by an
interlaboratory study in which three independent laborat
123 Reanalysis of results from an
interlaboratory study of a selected biochemical process
124 e performance of argon cluster sources in an
interlaboratory study under the auspices of VAMAS (Versa
125 An
interlaboratory study using identical samples shared amo
126 An
interlaboratory study, conducted using blinded NA008 Hig
127 To that end, an
interlaboratory study, involving the original six labora
128 ere shared among the laboratories to measure
interlaboratory test agreement.
129 Accuracy was checked via an EC-sponsored
interlaboratory trial.
130 The intra- and
interlaboratory variabilities of the molecular size meas
131 learance values exhibited a reduced level of
interlaboratory variability (5.3-38% CV).
132 al thyroid samples were normalized to remove
interlaboratory variability and then analyzed by unsuper
133 Unfortunately, the currently observed
interlaboratory variability caused by inconsistent assay
134 Viral loads showed a high degree of
interlaboratory variability for all tested viruses, with
135 This study examines
interlaboratory variability in the measurement of entero
136 Significant
interlaboratory variability is observed in testing the c
137 Overall,
interlaboratory variability levels remained low (<10% co
138 that this feature was likely responsible for
interlaboratory variability observed from in vitro inves
139 r human CMV DNA has raised hopes of reducing
interlaboratory variability of results.
140 We investigated the degree of
interlaboratory variability of several LD serologic test
141 earance values ranged from 4.1 to 30%, while
interlaboratory variability ranged from 27 to 61%.
142 e results on most assays using CDC criteria,
interlaboratory variability was considerable and remains
143 Although
interlaboratory variability was found in the degree of n
144 However, considerable
interlaboratory variability was seen in the results of t
145 ELISA-A showed higher precision and lower
interlaboratory variability, yet ELISA-B exhibited sligh
146 on agars were significant factors leading to
interlaboratory variability.
147 ex and multiplex amplification approaches on
interlaboratory variability.
148 Due to unacceptably high
interlaboratory variation in caspofungin MIC values, we
149 Interlaboratory variation in detecting autoantibodies re
150 strains were detected), and gave the largest
interlaboratory variation in performance.
151 This
interlaboratory variation is in fact smaller than the ma
152 ion platforms optimal for vaginal fluids and
interlaboratory variation limit their use for microbicid
153 lack of standardization, and interassay and
interlaboratory variation makes it difficult to determin
154 dida to caspofungin due to unacceptably high
interlaboratory variation of caspofungin MIC values.
155 Because it is internally standardized,
interlaboratory variation should be minimal.
156 ds limited monoclonal antibody availability,
interlaboratory variation, and the requirement for cultu
157 wever, most were associated with significant
interlaboratory variation.
158 MET exhibited the least
interlaboratory variation.
159 offers greater reproducibility, would reduce
interlaboratory variations and limit discrepancies in re
160 We assessed
interlaboratory variations in editing and their impact o
161 Interlaboratory variations were minimal, as the percenta