ISO 13528 EZMINUS SCORE
ISO 13528 EZPLUS SCORE
Name:
ISO 13528 EZMINUS SCORE (LET)
ISO 13528 EZPLUS SCORE (LET)
Type:
Purpose:
Generate an Ez- or an Ez+ score based on the ISO 13528 standard.
Description:
The ISO 13528 standard for proficiency testing defines the following
Ez scores
and
with Xref, u(ref), and
u(x) denoting the "assigned value", the
expanded uncertainty of the assigned value, and the laboratory's
estimate of the expanded uncertainty of its result, respectively.
Determing an assigned value and its associated uncertainty is
discussed on pages 5-10 of the standard.
Since there are a mumber of different methods for determining
Xref, u(ref), and
u(x), these values will be defined by the user
rather than being determined from the data.
The ISO 13528 standard recommends comparing these scores to a
critical value of 1.0. Specifically,
- If both Ez- and Ez+ are within the -1 to 1 range, the
laboratory's performance is satisfactory.
- If one of Ez- and Ez+ falls outside the -1 to 1 range, the
laboratory's performance is questionable.
- If both Ez- and Ez+ are outside the -1 to 1 range, the
laboratory's performance is unsatisfactory.
Syntax 1:
Syntax 2:
Examples:
LET Z = ISO 13528 EZMINUS SCORE X ULAB XREF UREF
LET Z = ISO 13528 EZPLUS SCORE X ULAB XREF UREF
Default:
Synonyms:
Related Commands:
Reference:
ISO 13528, First Edition, Statistical Methods for Use
in Proficiency Testing by Interlaboratory Comparisons,
2005, pp. 30.
Applications:
Implementation Date:
Program:
. Note: this example is just meant to demostrate the
. mechanics of the command. This is not in fact
. proficiency data, but it can be used to demonstrate
. how to use the command.
.
skip 25
read gear.dat y x
.
let xref = 1.
let sd = sd y
let uref = 2*sd
let ulab = cross tabulate sd y x
let ulab = 2*ulab
.
let ezm = iso 13528 ezminus score y ulab xref uref
let ezp = iso 13528 ezplus score y ulab xref uref
.
set write decimals 3
print x y ulab ezm ezp
The following output is generated.
---------------------------------------------------------------------------
X Y ULAB EZM EZP
---------------------------------------------------------------------------
1.000 1.006 0.008 2.134 2.134
1.000 0.996 0.008 0.984 0.984
1.000 0.998 0.008 1.214 1.214
1.000 1.000 0.008 1.444 1.444
1.000 0.992 0.008 0.524 0.524
1.000 0.993 0.008 0.639 0.639
1.000 1.002 0.008 1.674 1.674
1.000 0.999 0.008 1.329 1.329
1.000 0.994 0.008 0.754 0.754
1.000 1.000 0.008 1.444 1.444
2.000 0.998 0.010 1.011 1.011
2.000 1.006 0.010 1.778 1.778
2.000 1.000 0.010 1.203 1.203
2.000 1.002 0.010 1.395 1.395
2.000 0.997 0.010 0.916 0.916
2.000 0.998 0.010 1.011 1.011
2.000 0.996 0.010 0.820 0.820
2.000 1.000 0.010 1.203 1.203
2.000 1.006 0.010 1.778 1.778
2.000 0.988 0.010 0.053 0.053
3.000 0.991 0.007 0.447 0.447
3.000 0.987 0.007 -0.055 -0.055
3.000 0.997 0.007 1.201 1.201
3.000 0.999 0.007 1.452 1.452
3.000 0.995 0.007 0.950 0.950
3.000 0.994 0.007 0.824 0.824
3.000 1.000 0.007 1.578 1.578
3.000 0.999 0.007 1.452 1.452
3.000 0.996 0.007 1.075 1.075
3.000 0.996 0.007 1.075 1.075
4.000 1.004 0.007 2.278 2.278
4.000 1.002 0.007 1.889 1.889
4.000 0.994 0.007 0.851 0.851
4.000 1.000 0.007 1.629 1.629
4.000 0.995 0.007 0.980 0.980
4.000 0.994 0.007 0.851 0.851
4.000 0.998 0.007 1.370 1.370
4.000 0.996 0.007 1.110 1.110
4.000 1.002 0.007 1.889 1.889
4.000 0.996 0.007 1.110 1.110
5.000 0.998 0.015 0.696 0.696
5.000 0.998 0.015 0.696 0.696
5.000 0.982 0.015 -0.359 -0.359
5.000 0.990 0.015 0.168 0.168
5.000 1.002 0.015 0.960 0.960
5.000 0.984 0.015 -0.227 -0.227
5.000 0.996 0.015 0.564 0.564
5.000 0.993 0.015 0.366 0.366
5.000 0.980 0.015 -0.491 -0.491
5.000 0.996 0.015 0.564 0.564
6.000 1.008 0.019 1.090 1.090
6.000 1.012 0.019 1.292 1.292
6.000 1.008 0.019 1.090 1.090
6.000 0.997 0.019 0.483 0.483
6.000 0.988 0.019 0.028 0.028
6.000 1.002 0.019 0.736 0.736
6.000 0.995 0.019 0.382 0.382
6.000 0.998 0.019 0.533 0.533
6.000 0.981 0.019 -0.325 -0.325
6.000 0.996 0.019 0.432 0.432
7.000 0.990 0.015 0.162 0.162
7.000 1.004 0.015 1.050 1.050
7.000 0.996 0.015 0.543 0.543
7.000 1.000 0.015 0.860 0.860
7.000 0.998 0.015 0.670 0.670
7.000 1.000 0.015 0.797 0.797
7.000 1.018 0.015 1.939 1.939
7.000 1.010 0.015 1.431 1.431
7.000 0.996 0.015 0.543 0.543
7.000 1.002 0.015 0.924 0.924
8.000 0.998 0.007 1.455 1.455
8.000 1.000 0.007 1.731 1.731
8.000 1.006 0.007 2.558 2.558
8.000 1.000 0.007 1.731 1.731
8.000 1.002 0.007 2.006 2.006
8.000 0.996 0.007 1.179 1.179
8.000 0.998 0.007 1.455 1.455
8.000 0.996 0.007 1.179 1.179
8.000 1.002 0.007 2.006 2.006
8.000 1.006 0.007 2.558 2.558
9.000 1.002 0.008 1.759 1.759
9.000 0.998 0.008 1.275 1.275
9.000 0.996 0.008 1.034 1.034
9.000 0.995 0.008 0.913 0.913
9.000 0.996 0.008 1.034 1.034
9.000 1.004 0.008 2.000 2.000
9.000 1.004 0.008 2.000 2.000
9.000 0.998 0.008 1.275 1.275
9.000 0.999 0.008 1.396 1.396
9.000 0.991 0.008 0.429 0.429
10.000 0.991 0.010 0.333 0.333
10.000 0.995 0.010 0.709 0.709
10.000 0.984 0.010 -0.322 -0.322
10.000 0.994 0.010 0.615 0.615
10.000 0.997 0.010 0.896 0.896
10.000 0.997 0.010 0.896 0.896
10.000 0.991 0.010 0.333 0.333
10.000 0.998 0.010 0.990 0.990
10.000 1.004 0.010 1.553 1.553
10.000 0.997 0.010 0.896 0.896