7 December 2000 **) and forthcoming in Keywords: Conjoint Analysis 6-1 fax:06-6878-2766 tel:06-6879-8566 e-mail:ohkusa@iser.osaka-u.ac.jp Cost-Effective 798/799 '99/'00 Conjoint Analysis 799/700 0.8% 3.5% 1.0 47% 31 10% 2.5% Conjoint ) ( Analysis 6000 43.5% 11%,16% 33% 21% 8% 799/700 Conjoint Analysis 11 1),2),3) 4),5) 6) '97' 2 12405 798 2 6,569 799 1 22,503 Cost-Effective Cost-Effective 7),8),9),10) 11) linear probability 798/'99 '99/'00 11 Conjoint Analysis Conjoint Analysis Conjoint Analysis 2 ’98/’99 '99/'00 798/'99 Conjoint Analysis Conjoint Analysis 33 3.1
10% y% x% x + y% 60 60
60 10
1.9%
'99/'00 0.8% 3.5% 30% 2 10% 2.5% 33 ( ) 3.2 Ii It E i 0 Oi Ji,t   =    76 + YAAi,t + YAA ,t + YGGi,t + YHHHi,t + YNNNi +   YcCi + Ym1Mi + Ym2Mi + YdDt + YmI i + YjI i + YeEi + YoOi + Ei,t | 1  if  J*,t > 0 (3)
(2) J i   =    ηo + η A i + η α A i + η G G i + η H i + η N N i 5 +  η C i + η M i + η M i + η M i + η F i + η W i + η I i + η Ï i + η E E i
60
1.0% 47% 44 Conjoint  Analysis 4.1 Conjoint Analysis Conjoint Analysis . . ● Willingness to Pay 12) Standard gamble Time trade off Rating Scale Willingness to Pay Standard gamble Time trade off Rating Scale Conjoint Analysis Willingness to Pay Conjoint Analysis 13) Conjoint Analysis Conjoint Analysis 16) 17) 14) 15) MRI 18) Conjoint Analysis 19),20),21),22),23),24) Conjoint Analysis 13),25) random effect probit Conjoint Analysis Conjoint Analysis probit individual effect random effect Conjoint Analysis random effect individual effect random effect individual effect Conjoint Analysis 26) Hausman random effect random effect Conjoint Analysis 0 Conjoint Analysis random effect random effect Conjoint Analysis 6000 3000 6000 3000 6000 3000 0 6000 3000 6000 3000 6000 3000
4.2
Conjoint Analysis

P,
individual effect random
effect 18 18 6000 43.5% 11%,16% 33% 6000 11% 11 0 2.1% 6000 8.7% 2.1%,3.2% 6.6% 21% 8% 4.2%,1.6% 60 10 6 10 Conjoint Analysis 3.7% 5 Conjoint Analysis 2 '99/'00 0.8% 1.0 3.5% 47% 10% 2.5% ( ) Conjoint Analysis 6000 8.7% 2.1%,3.2% 6.6% Conjoint Analysis 31 Analysis Conjoint 1999 -015 H11- 0 [1] Serfling RE. Methods for Current Statistical Analysis of Excess Pneumonia-Influenza Deaths. Public Health Rep 1963; 78: 494-506. [2] Assad F, Cockburn WC, Sundaresan TK. Use of excess mortality from respiratory diseases in the study of influenza. Bulltein of WHO.1973; 49: 219-233. [3] Choi K and Thacker SB. An Ealuation of Influenza Mortality Surveillance, 1962-1979 .I. Am J Epidemiology.1981; 113: 215-226. [4] .1999; 46-4: 263-273. [5] . Journal of National Institution of Public Health.1999; 48-4: 291-297. [6] Shindo,N, M.Ii,Y.Ohkusa and K.Taniguchi.A Newly Developed Japanese Pneumonia and Influence Mortality Model and Statistical Analysis Influenza Excess Mortality by Stochastic Frontier Estimation.ISER DP. 2000; 501. [7] Nichol,K.L., K.L.Margolis, J.Wuorena and T.V.Sternberg.The Efficiency and Cost Ef- fectiveness of Vaccination Against Influenza among Elderly Persons Living in the Com- munity.The New England Journal of Medicine.1994; 778-784. [8] Gross,P.A., A.W.Hermogenes, H.S.Sacks, J.Lau and R.A.Levandowski.The Efficiency of Influenza Vaccine in Elderly Persons :A Meta-analysis and Review of Literature. Annals of Internal Medicine.1995 ; 123: 519-527. [9] Levy,E. French Economic Evaluations of Influenza and Influenza Vaccination. Phar- macoEconomics 1996;IX,Supple.III: 62-66. [10] Scott,G.W.and H.M.Scott.Economic Evaluation of Vaccination Against Influenza in New Zealand.PharmacoEconomics.1996; IX: 51-60. [11] Mullahy,J. It'll Only Hurt a Second? Microeconomic Determinants of Who Gets Flue Shots. Health Economics.1999; 8: 9-24. [12] Tolley,G.,D.Kenkel and R.Fabian.Valuing Health Policy :  An Economic Ap- proach University of Chicago Press.1994. [13] Conjoint Analysis. .2000; 10-1:125-144. [14] Ryan,M. Using Conjoint Analysis to Take Account of Patient Preferences and Go Beyond Health Outcomes. An Application to In-Vitro Fertilization. Social Science and Medicine.1999 ; 48  535-546. [15] Ryan,M. and S.Farrar.A Pilot Study Using Conjoint Analysis to Establish the Views of Users in the Provision of Orthodontic Services in Grampian. Health Economics Reserch Unit Discussion Paper. Aberdeen,University of Aberdeen .1994; 07/94. [16] Ryan,M and J.Hughes.Using Conjoint Analysis to Assess Women's Preference for Mis- carriage Management. Health Economics. 1997; 6: 261-274. [17] Van der Pol,M. and J.Cairns.Establishing Patient's Prefernces for Blood Transfusion Support: An Application of Conjoint Analysis.Journal of Health Services Research and Policy. 1997; 3: 70-76. [18] Bryan,S., M.Buxton, R.Sheldon, A.Grant.The Use of Magnetic Resonance Imaging for The Investigation of Knee Injuries: A Discrete Choice Conjoint Analysis Exercise. Health Economics 1998; 7: 595-604. [19] Bryan,S. Structural Reliability of Conjoint Analysis Applied to Health Care :  an Empirical Investigation, presented in IHEA 2nd World Conference, 1999. [20] Johnson,F , W.Desvousges and M.Ruby.Willingness to Pay to Avoid Cardiovascular and Respiratory Conditions : Consensus Estimates of Task-Specific Stated Prefer- ences, presented in IHEA 2nd World Conference.1999. [21] Ratcliffe.J.Patients Prefrences Regarding the Process and Outcomes of Life Saving Technology：An Application of Conjoint Analysis to Liver Transplantation. presented in IHEA 2nd World Conference. 1999. [22] San Miguel,A and M.Ryan.Testing the Assumptions of Completeness and Stability of Preferences in Health Care Using Discrete Choice Models, presented in IHEA 2nd World Conference.1999. [23] Telser,H and P.Zweifel.Conjoint Analysis as a Method for Measuring Wilingness to Pay for Risk Reductions. presented in IHEA 2nd World Conference.1999. [24] Van der Pol,M. and J.Cairns.Using Conjoint Analysis to Estimate Time Preference for Other’s Health, presented in IHEA 2nd World Conference.1999. [25]ン
[26] Hausman,J. Specifiction Test in Econometrics. Econometrica.1978; 46:1251-1271.
Conjoint :
139.7 1% 0 -435.18 2 0.1545
: :
0 -87.459 2 0.2869
0
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