1 Rating scales 2 Andrich 3 Guilford 4 Accuracy 5 Reliability

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1 92/7/13 : 94/10/16 : - ** *.... :( ) m.mazaheri@um.ac.ir mazaheri@hamoon.usb.ac.ir ** *

2 "" (). : ).(1394.(1393 )...(2002 ). ).(1392

3 147. (1392 ).(1384).( ) (2000 ) (1978) Rating scales 2 Andrich 3 Guilford 4 Accuracy 5 Reliability

4 ( ) (1983 ) 6.(1994 ) :. 8 7 ) (1997 ) 9 (1987 ) ( ( ) 2001 ) ( Bias 2 Invalidity 3 systematic error 4 Berk 5 Osterlind 6 Camilli and Shepard 7 Bruin et al 8 Baumgartner & Steenkamp 9 Schwarz and Hippler 10 Stephenson & Herman, 11 Sangster et al 12 Watkins & Cheung

5 (2012 )..(1388 ). 2 3.(1390 ).. 1 Stojic 2 Zadeh 3 Kasko

6 ) 3 2.( (1394 ).1 : ( ). 1 Buckley 2 Broz 3 Stojic 4 Wang

7 (1392). : 2.(1998 ) (2006) (2) (1) :. 1 Fuzzy inference systems 2 Zetenyi 3 Smithson 4 Vereckling

8 (3).. (4). (5)..(1392).. ) (. 5 4 : 6 :..1 ( ) 1 Inference 2 Center of gravity 3 Defuzzifier 4 Deduction 5 Inference 6 Fuzzifier

9 153 : : :.. : (1392 ) 1 Defuzzifier

10 (92-93 ). :.1. %60 ) ( %40 ). ( : ) (.

11 155. matlab SPSS-20 t ) ( ) ( ).(1

13 (1389 ).... ( 50 10).(1393). 1 1.Fuzzy membership

14 :1 * 4/47 12/5 10/5 12/5 4/47 11/ /58 4/47 15/3 4/47 8/65 14/2 9/05 13/7 7 13/05 17/6 18/8 5/55 3/65 17/05 8/85 10/ /25 10/5 4/5 11/ /75 4/25 15/25 10/75 5/5 19 2/75 18/5 10/ /5 20 9/75 2/75 19/75 14/5 16/05 18/ /5 15/95 19/ /47 4/95 6/75 2/ / / /5 11/5 17 3/ /5 9/ /7 5/45 2/75 9/ /7 18/ / /5 15/ / *

15 159 () (1992 ) - 4.( ) Wang 2 Mandel 3 () ( ) ( ) 4 Defuzzification

16 : :2 (1) (2) (3) (5) (4) (6) (10) (7) (8) (9) (13) (14) (15) (11) (12) (16) (17) (18) (19) (20) (21) (22) (23) (24) (25) 25 :(1). 1 Rule base

17 161 :(6). :(11). :(16). :(21). :. MIN. MIN.. (α ). :. MAX. SUM MAX SUM..

18 : (1995 ) SUM product. 10/75 5/5 1 0 y 9 fuzzy ( y) = ( y 10) 9 y 10 0 otherwise 9 10 Area = f ( y) dy = dy ( y 10) dy= Moment = yf ( y) dy = ydy ( y 10 y) dy = /47 : 1 Center of gravity Defuzzifier 2 Maximum Defuzzifier 3 Klir

19 163 Moment yf ( y) dy Cetroid = 4.57 Area = f( y) dy = 9.5 =. 3 : 3 4/ / 2 2 () 5/ / 2 2 () 3 : ( ). t. 4 t : 4 0/ t 2/357

20 t(21) = 2.357, p <.05 %95 3 (12/125) (11/219)... ( ).. "" (). 2

21 165 () :2...

22 :(labmat )

23 167 ( )..(1369 ).١.(1982 )..(1392 ).٢ (1393)..٣ (14)7..(1392 )..۴ (1388).۵. : :..(1389).۶... :(1391).٧. )..(1389)..٨.(2006 ). :.(.. (1392).٩. ::..(1390).١٠. (1384)..١١.

24 :. : matlab (1389).١٢. :. (1393).١٣.(1394 )..١۴ (2)8 : (1394).١۵. ). (1384 ).١۶.(.(1390).١٧. :. 18. Andrich, D. A. (1978). A rating formulation for ordered response categories. Psychometrika, 43, Baumgartner, H. and Steenkamp, J-B. E.M. (2001) Response Styles in Marketing Research: A Cross-National Investigation, Journal of Marketing Research, 38 (2), pp Berk, A.B.: (1982), Handbook of methods for detecting test bias (The John Hopkins Press Ltd, London). 21. Broz, Z. (2012). Fuzzy Logic Decision Support for Long-term Investing in the Financial Markets. Advances in Intelligent System and Computing,1(1), Bruin, L.P., Diederiks, J.P.M., Witte, L.P., Stevens, F.C.J., & Philipsen, H.(1997). Assessing the Responsiveness of a Functional Status Measure: The Sickness Impact Profile Versus the SIP68, Journal Clinical Epidemiology, 50, Buckley. J., Eslami, E., & Feruing, T. (2002). Fuzzy Mathematics in Economics and Engineering. Physica Verlag Heidelberg.

25 Calman KC(1984) Quality of life in Cancer Patients -An Hypothesis Med Ethics 25. Camilli, G. and L. Shepard: 1994, MMSS: Methods for identifying biases test items, Vol.4 (SAGE Publications, Inc, California). 26. Clifford W. (2000): Measurement tools and the quality of life, San Francisco. Cobb, Redefining Progress; Ferrance C :Powers M. (1985) Quality of Life Index : Development and Propertied.Adv Nursci. 28. klir, g, yuan, b.(1995). fuzzy sets and fuzzy logic: theory and applications. new jersey: prentice hall p t r. 29. Korotz, D.M (2002). Limitations in the Use of Achievement Tests as Measures of Educators Productivity, 37 (4), Nel E ;Uys HH (1993) The Effect Of Preparative Teaching on the Emothional Attitude of Patients Undergoing Coronary Bypass Surgery Curations 31. Osterlind S.J.: 1983, Test item bias. Series: Quantitative Applications in the Social Sciences (SAGE University Papers 30, Sage Publications, Inc). 32. Sangster, RL. Willits, FK. Saltiel, J. Lorenze, FO., & Rockwood, T.H. (2001). The effects of numerical labels on response scales. Paper presented at the Annual Meeting of the American Statistical Association, Atlanta, GA. 33. Schwarz, N., & Hippler, H.J. (1987). What response scales may tell your respondents. In H. J. Hippler, N. Schwarz, & S. Sudman (Eds.), Social information processing and survey methodology. New York: Springer Verlag. 34. Stephenson, N.L., & Herman, J. (2000). Pain measurement: A comparison using horizontal and vertical visual analogue scales. Applied Nursing Research, 13,

26 Stojic, G. (2012). Using Fuzzy Logic for Evaluating the Level of Countries (Regions ) Economic Development. Panoconomics, 3, Wang Li-Xin,(1997)A Course in Fuzzy Systems & Control ;Prentics-Hall International,Inc. 37. Wang Li-Xin,Mandel Jerry M,(1992),Generating Fuzzy Rules by learning form Examples;IEEE Transactions on Systema,and Cybernetics. 38. Zetenyi, T. (1998). fuzzy sets in psychology. (G. stelmach,, & P. vroon, Eds.) bz Amsterdam: elsevier science publishers B.V.

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