• No se han encontrado resultados

PROGRAMA 210: ALIMENTACION Y AGRICULTURA

In document CONSEJO ECONOMICO Y SOCIAL (página 59-65)

102 References

58. Train G, Nurock S, Kitchen G, Manela M, Livingston G. A qualitative study of the experiences of long-term care for residents with dementia, their relatives and staff. Aging

Ment Health 2005;9:119–28.

59. Miller E, Cooper S-A, Cook A, Petch A. Outcomes important to people with intellectual disabilities. J Pol Pract Intellect Disabil 2008;5:150–8.

60. Henwood M, Lewis H, Waddington E. Listening to users of domiciliary care services:

developing and monitoring quality standards. Leeds: Nuffield Institute for Health; 1998.

61. Raynes N, Temple B, Glenister C, Coulthard L. Quality at home for older people; involving

service users in defining home care specifications. York: Joseph Rowntree Foundation; 2001.

62. Francis J, Netten A. Raising the quality of home care: a study of service users’ views. Soc Pol

Admin 2004;38:290–305.

63. Willis G, Lessler J. Question appraisal system QAS-99. Rockville, MD: Research Triangle Institute; 1999. URL: http://appliedresearch.cancer.gov/areas/cognitive/

guides.html (accessed 15 May 2008).

64. Suchman L, Jordan B. interactional troubles in face-to-face survey interviews. J Am Stat

Assoc 1990;85:232–41.

65. Willis G. Cognitive interviewing: a tool for improving questionnaire design. London: Sage; 2005.

66. Tourangeau R. Cognitive science and survey methods: a cognitive perspective. In Jabine TB, Straf ML, Tanur JM, Tourangeau R, editors. Cognitive aspects of survey design: building a

bridge between disciplines. Washington, DC: National Academy Press; 1984. pp. 73–100.

67. Campanelli P, Martin E, Rothget J. The use of respondent and interviewer debriefing studies as a way to study the response error in survey data. Statistician 1991;40:253–64.

68. Brazier J, Ratcliffe J, Salomon J, Tsuchiya A. Measuring and valuing health benefits for

economic evaluation. Oxford: Oxford University Press; 2007.

69. Messick S. Validity of test interpretation and use. Research Report No. 90–11. Princetown, NJ: Educational Testing Service; 1990.

70. Brazier J, Deverill M, Green C, Harper R, Booth A. A review of the use of health status measures in economic evaluation. Health Technol Assess 1999;3(9).

71. American Educational Research Association, American Psychological Association, National Council of Measurement in Education. Standards for educational and psychological testing. Washington, DC: American Educational Research Association; 1999.

72. Lenert L, Kaplan RM. Validity and interpretation of preference-based measures of health- related quality of life. Med Care 2000;38:138–50.

73. Coast J, Peters TJ, Natarajan L, Sproston K, Flynn T. Valuing the ICECAP capability index for older people. Soc Sci Med 2008;67:874–82.

74. EuroQol group. EuroQol: a new facility for the measurement of health-related quality of life.

Health Pol 1990;16:199–208.

75. Dolan P, Gudex C, Kind P, Williams A. Valuing health states: a comparison of methods.

J Health Econ 1996;15:209–31.

76. Goldberg D, Hillier V. A scaled version of the General Health Questionnaire. Psychol Med 1979;9:139–45.

77. Goldberg D. Manual of the general health questionnaire. Windsor: National Foundation for Educational Research (NFER); 1978.

78. Goldberg D. The detection of psychiatric illness by questionnaire. London: Oxford University Press; 1972.

79. Hu Y, Stewart-Brown S, Twigg L, Weich S. Can the 12-item General Health Questionaire be used to measure positive mental health? Psychol Med 2007;37:1005–13.

80. Hyde M, Wiggins RD, Higgs P, Blane DB. A measure of quality of life in early old age: the theory, development and properties of a needs satisfaction model (CASP-19). Aging Ment

Health 2003;7:186–94.

81. Wiggins R, Netuveli G, Hyde M, Higgs P, Blane D. The evaluation of a self-enumerated scale of quality of life (CASP-19) in the context of research on ageing: a combination of exploratory and confirmatory approaches. Soc Indicat Res 2008;89:61–77.

82. Wittenberg R, Comas-Herrera A, King D, Malley J, Pickard L, Darton R. Future demand

for long-term care, 2002 to 2041: projections of demand for long-term care for older people in England. Discussion Paper 2330. London: London School of Economics; 2006.

83. Malley J, Towers A-M, Netten A, Brazier J, Forder J, Flynn T, et al. An assessment of the

construct validity of the ASCOT measure of social care-related quality of life. Discussion Paper

2750. Canterbury: PSSRU, University of Kent; 2011.

84. Leyden KM. Social capital and the built environment: the importance of walkable neighbourhoods. Am J Publ Health 2003;93:1546–51.

85. Cohen J. Statistical power analysis for the behavioral sciences. 2nd edn. Hillsdale, NJ: Erlbaum; 1988.

86. Davies B, Fernández J-L, Nomer B. Equity and efficiency policy in community care. Aldershot: Ashgate; 2000.

87. Fernández J-L. Utilisation and service productivities in community social care for older

people: patterns and policy implications. London: London School of Economics and

Political Science; 2005.

88. Bleichrodt H. A new explanation for the difference between time trade-off utilities and standard gamble utilities. Health Econ 2002;11:447–56.

89. Louviere JJ, Street DJ, Burgess L, Wasi N, Islam T, Marley AAJ. Modelling the choices of single individuals by combining efficient choice experiment designs with extra preference information. J Choice Modelling 2008;1:128–63.

90. McFadden D. Conditional logit analysis of qualitative choice behavior. In Zarembka P, editor.

Frontiers in econometrics. New York, NY: Academic Press; 1974. pp. 105–42.

91. Thurnstone L. A law of comparative judgment. Psychol Rev 1927;34:273–86. 92. Louviere JJ, Hensher DA, Swait JD. Stated choice methods: analysis and application.

Cambridge: Cambridge Press; 2000.

93. Fiebig DG, Keane M, Louviere JJ, Wasi N. The generalized multinomial logit model.

Marketing Sci 2010;29:393–421.

94. Yatchew A, Griliches Z. Specification error in probit models. Rev Econ Stat 1985;67:134–9. 95. Herdman M, Badia X, Berra S. EuroQol-5D: a simple alternative for measuring health-related

quality of life in primary care. Barcelona: Agencia d’Avaluacio de Tecnologia i Recerca

104 References

96. Flynn TN, Louviere JJ, Peters TJ, Coast J. Using discrete choice experiments to understand preferences for quality of life. Variance scale heterogeneity matters. Soc Sci Med.

2010;70:1957–65.

97. Burge P, Gallo F, Netten A. Valuing PSS outputs and quality changes. Canterbury: PSSRU, University of Kent; 2006.

98. Ryan M, Netten A, Skatun D, Smith P. Using discrete choice experiments to estimate a preference-based measure of outcome: an application to social care for older people. J Health

Econ 2006;25:927–44.

99. Louviere JJ, Woodworth GG. Best-worst scaling: a model for largest difference judgments.

Working Paper. University of Alberta: Faculty of Business; 1990.

100. Finn A, Louviere JJ. Determining the appropriate response to evidence of public concern: the case of food safety. J Publ Pol Marketing 1992;11:12–25.

101. Marley A, Flynn TN, Louviere JJ. Probabilistic models of set-dependent and attribute-level best-worst choice. J Math Psychol 2008;52:281–96.

102. Flynn TN, Louviere JJ, Peters TJ, Coast J. Best-worst scaling: what it can do for health care research and how to do it. J Health Econ 2007;26:171–89.

103. Flynn TN. Using conjoint analysis and choice experiments to estimate quality adjusted life year values: issues to consider. Pharmacoeconomics 2010;28:711–22.

104. Potoglou D, Burge P, Flynn TN, Netten A, Malley J, Forder J, et al. Best-worst scaling vs. discrete choice experiments: an empirical comparison using social care data. Soc Sci Med 2011;72:1717–27.

105. Swait J, Louviere JJ. The role of the scale parameter in the estimation and comparison of multinomial logit models. J Market Res 1993;30:305–14.

106. Hess S, Daly A. Calculating errors for measures derived from choice modelling estimates. 88th Annual Meeting of the Transportation Research Board, Washington, DC, 2009.

107. Ratcliffe J, Brazier JE, Tsuchiya A, Symonds T, Brown M. Using DCE and ranking data to estimate cardinal values for health states for deriving a preference-based single index from the sexual quality of life questionnaire. Health Econ 2009;18:1261–76.

108. Islam T, Louviere JJ, Burke PF. Modelling the effects of including/excluding attributes in choice experiments on systematic and random components. Int J Res Marketing 2007;24:289–300.

109. Burge P, Potoglou D, Kim CW, Hess S. How do the public value different outcomes of social

care? Cambridge: RAND Europe; 2010.

110. Flynn TN. Valuing citizen and patient preferences in health: recent developments in three types of best-worst scaling. Expert Rev Pharmacoecon Outcomes Res 2010;10:259–67. 111. Ben-Akiva M, Lerman SR. Discrete choice analysis: theory and application to travel demand.

Cambridge: MIT Press; 1985.

112. Dolan P. Modelling valuations for EuroQol health states. Med Care 1997;11:1095–108. 113. Howard GS, Dailey PR. Response shift bias: a source of contamination of self-report

measures. J Appl Psychol 1979;64:144–50.

114. Ring L, Hofer S, Heuston F, Harris D, O’Boyle C. Response shift masks the treatment impact on patient reported outcomes (PROs): the example of individual qu5ality of life in edentulous patients. Health Qual Life Outcomes 2005;3:55.

115. Howard GS, Ralph KM, Gulanick NA, Maxwell SE, Nance SW, Gerber SK. Internal invalidity in pre-test-posttest self-report evaluations and a re-evaluation of retrospective pre-tests. Appl

Psychol Meas 1979;3:1–23.

116. Sprangers M, Hoogstraten J. Pretesting effects in retrospective pretest-posttest designs. J Appl

Psychol 1989;74:265–72.

117. Al-Janabi H, Coast J, Flynn TN. What do people value when they provide unpaid care for an older person? A meta-ethnography with interview follow up. Soc Sci Med 2008;67:111–121. 118. Al-Janabi H, Flynn TN, Coast J. Estimation of a preference-based carer experience scale. Med

Decis Making 2011;31:458–68.

119. Al-Janabi H, Flynn TN, Coast J. QALYs and carers. Pharmacoeconomics 2011;29:1015–23. 120. Fox D, Holder J, Netten A. Personal Social Services survey of adult carers in England: 2009–10:

survey development project. Discussion Paper 2643/2. Canterbury: PSSRU, University

of Kent; 2010.

121. Malley J, Fox D, Netten A. Developing a carers’ experience perfomance indicator. PSSRU Discussion Paper No. 2734. Canterbury: PSSRU, University of Kent; 2010.

122. Malley J, Sandhu B, Netten A. Quality of social care for younger adults with physical and

sensory impairments living in their own homes. Discussion Paper No. 2770. Canterbury:

PSSRU Research Unit, University of Kent; 2011.

123. McHorney CA, Cohen AS. Equating health status measures with item response theory. Illustrations with functional status items. Med Care 2000;38:II43–59.

124. De Vellis R. Scale development: theory and applications. 2nd edn. London: Sage; 2003. 125. Floyd FJ, Widaman KF. Factor analysis in the development and refinement of clinical

assessment instruments. Psychol Assess 1995;7:286–99.

126. Olsson U. On the robustness of factor analysis against crude classification of the observations. Multivariate Behav Res 1979;14:485–500.

127. Holgado-Tello F, Chacón-Moscoso S, Barbero-García I, Vila-Abad E. Polychoric versus Pearson correlations in exploratory and confirmatory factor analysis of ordinal variables.

Qual Quant 2010;44:153–66.

128. Olsson U. Maximum likelihood estimation of the polychoric correlation coefficient.

Psychometrika 1979;44:443–60.

129. Fabrigar LR, Wegener DT, MacCallum RC, Strahan EJ. Evaluating the use of exploratory factor analysis in psychological research. Psychol Meth 1999;4:272–99.

130. Sijtsma K, Emons W, Bouwmeester S, Nyklíček I, Roorda L. Nonparametric IRT analysis of quality-of-life scales and its application to the World Health Organization Quality-of-Life Scale (WHOQOL-Bref). Qual Life Res 2008;17:275–90.

131. Moorer P, Suurmeijer TPBM, Foets M, Molenaar IW. Psychometric properties of the RAND-36 among three chronic disease (multiple sclerosis, rheumatic diseases and COPD) in the Netherlands. Qual Life Res 2001;10:637–45.

132. Sijtsma K, Molenaar IW, editors. Introduction to nonparametric item response theory. London: Sage; 2002.

133. Kaiser HF. An index of factorial simplicity. Psychometrika 1974;39:31–6.

134. Marley AAJ, Louviere JJ. Some probabilistic models of best, worst, and best-worst choices.

106 References

135. Train K. Discrete choice models with simulation. Cambridge, UK: Cambridge University Press; 2003.

136. Ben-Akiva M, Morikawa T. Estimation of switching models from revealed preferences and stated intentions. Transport Res 1990;24:485–96.

137. ALOGIT. HCG Software, London, 2005. URL: http://www.alogit.com.

138. Bierlaire M, editor. BIOGEME: A free package for the estimation of discrete choice models. Proceedings of the 3rd Swiss Transportation Research Conference, Ascona, 2003.

Appendix 1

Development of domains of social

In document CONSEJO ECONOMICO Y SOCIAL (página 59-65)