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1

Popovich, JoAnn M. "Multidimensional Performance Measurement." Journal of Nursing Care Quality 12, no. 4 (1998): 14–21. http://dx.doi.org/10.1097/00001786-199804000-00006.

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2

Sarwar Awan, Masood, Muhammad Waqas, and Muhammad Amir Aslam. "Multidimensional measurement of poverty in Pakistan: Provincial analysis." Nóesis. Revista de Ciencias Sociales y Humanidades 24, no. 48 (2015): 55–72. http://dx.doi.org/10.20983/noesis.2015.2.2.

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3

Williams, Marie T., and Kylie N. Johnston. "Multidimensional measurement of breathlessness." Current Opinion in Supportive and Palliative Care 13, no. 3 (2019): 184–92. http://dx.doi.org/10.1097/spc.0000000000000436.

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4

Núñez Medina, Gerardo. "Medición Multidimensional de la Concentración de Población." Revista Espacio I+D Innovación más Desarrollo 3, no. 5 (2014): 20–49. http://dx.doi.org/10.31644/imasd.5.2014.a02.

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5

Sharma, Lalit, and Kavita Chakravarty. "Multidimensional Poverty Measurement in Haryana." Indian Journal of Human Development 9, no. 1 (2015): 89–101. http://dx.doi.org/10.1177/0973703020150106.

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6

Alkire, Sabina, and James Foster. "Counting and multidimensional poverty measurement." Journal of Public Economics 95, no. 7-8 (2011): 476–87. http://dx.doi.org/10.1016/j.jpubeco.2010.11.006.

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7

Bastos, Amélia, and Carla Machado. "Child poverty: a multidimensional measurement." International Journal of Social Economics 36, no. 3 (2009): 237–51. http://dx.doi.org/10.1108/03068290910932738.

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8

TITIEV, ROBERT J. "Multidimensional measurement and universal axiomatizability." Theoria 38, no. 1-2 (2008): 82–88. http://dx.doi.org/10.1111/j.1755-2567.1972.tb00925.x.

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9

Bennett, Christopher J., and Shabana Mitra. "Multidimensional Poverty: Measurement, Estimation, and Inference." Econometric Reviews 32, no. 1 (2013): 57–83. http://dx.doi.org/10.1080/07474938.2012.690331.

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10

Weinrich, James D. "Multidimensional Measurement of Sexual Orientation: Past." Journal of Bisexuality 14, no. 3-4 (2014): 314–32. http://dx.doi.org/10.1080/15299716.2014.946198.

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11

Weinrich, James D. "Multidimensional Measurement of Sexual Orientation: Present." Journal of Bisexuality 14, no. 3-4 (2014): 373–90. http://dx.doi.org/10.1080/15299716.2014.951138.

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12

Weinrich, James D. "Multidimensional Measurement of Sexual Orientation: Ideal." Journal of Bisexuality 14, no. 3-4 (2014): 544–56. http://dx.doi.org/10.1080/15299716.2014.960958.

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13

Thimmaiah, Navitha. "Multidimensional Measurement of Poverty in Mysore." Indian Economic Journal 62, no. 4 (2015): 1265–88. http://dx.doi.org/10.1177/0019466220150406.

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14

Decancq, Koen, Marc Fleurbaey, and François Maniquet. "Multidimensional poverty measurement with individual preferences." Journal of Economic Inequality 17, no. 1 (2019): 29–49. http://dx.doi.org/10.1007/s10888-019-09407-9.

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15

Busemeyer, J. R., and Z. Wang. "Hilbert space multidimensional modelling of continuous measurements." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 377, no. 2157 (2019): 20190142. http://dx.doi.org/10.1098/rsta.2019.0142.

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Data fusion problems arise when a researcher needs to analyse results obtained by measuring empirical variables under different measurement contexts. A context is defined by a subset of variables taken from a complete set of variables under investigation. Multiple contexts can be formed from different subsets, which produce a separate distribution of measurements associated with each context. A context effect occurs when the distributions produced by the different contexts cannot be reproduced by marginalizing over a complete joint distribution formed by all the variables. We propose a Hilbert
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16

Dirksen, Jakob, and Sabina Alkire. "Children and Multidimensional Poverty: Four Measurement Strategies." Sustainability 13, no. 16 (2021): 9108. http://dx.doi.org/10.3390/su13169108.

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Empirically, official multidimensional measures of poverty often show children to be the poorest age group. Such poverty measures and their analysis can be used to directly inform policies to reduce children’s multiple deprivations. This paper introduces methods to produce official national statistics on multidimensional poverty that inform child-focused anti-poverty policies. In doing so, it recognises the importance of parsimonious, consistent measures, given practical constraints such as policy makers’ time. The paper does not recommend constructing several disjoint poverty measures which c
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17

Heshmati, Almas. "Measurement of a Multidimensional Index of Globalization." Global Economy Journal 6, no. 2 (2006): 1850087. http://dx.doi.org/10.2202/1524-5861.1117.

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In this article we present two composite indices of globalization. The first is based on the Kearney/Foreign Policy magazine and the second is obtained from principal component analysis. They indicate which countries have become most global and show how globalization has developed over time. The indices are composed of four components: economic integration, personal contact, technology and political engagement, each generated from a number of variables. A breakdown of the index into major components provides possibilities to identify sources of globalization and associate it with economic poli
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18

Choi Gyun, 권종희, and 서병수. "Measurement of Multidimensional Poverty by Counting Approach." Korean Journal of Social Welfare 63, no. 1 (2011): 85–111. http://dx.doi.org/10.20970/kasw.2011.63.1.004.

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19

Slapničar, Sergeja, and Adriana Rejc Buhovac. "IDENTIFYING TEMPORAL RELATIONSHIPS WITHIN MULTIDIMENSIONAL PERFORMANCE MEASUREMENT." Journal of Business Economics and Management 15, no. 5 (2014): 978–93. http://dx.doi.org/10.3846/16111699.2013.789450.

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The paper investigates temporal relationships between leading drivers of success, non-financial outputs, and financial outcomes as suggested by the Balanced Scorecard. Based on a sample of 42 companies with a four-year survey data, we find partial confirmation of temporal causality between selected actions and performance. The effects of the leading variables on the non-financial outputs are the strongest in the same year. Also, the influence of innovation and HR policies via the number of patented innovations and new products (services) on profit growth is the strongest within one year. These
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20

Heneman, Herbert G., and Donald P. Schwab. "Pay Satisfaction: Its Multidimensional Nature and Measurement." International Journal of Psychology 20, no. 1 (1985): 129–41. http://dx.doi.org/10.1080/00207598508246743.

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21

Heneman, Herbert G., and Donald P. Schwab. "PAY SATISFACTION: ITS MULTIDIMENSIONAL NATURE AND MEASUREMENT*." International Journal of Psychology 20, no. 1 (1985): 129–41. http://dx.doi.org/10.1080/00207598508247727.

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22

Drasgow, Fritz, Michael V. Levine, and Mary E. McLaughlin. "Appropriateness Measurement for Some Multidimensional Test Batteries." Applied Psychological Measurement 15, no. 2 (1991): 171–91. http://dx.doi.org/10.1177/014662169101500207.

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23

Tsaur, Sheng-Hshiung, Ying-Wen Liang, and Huei-Ju Hsu. "A Multidimensional Measurement of Work-Leisure Conflict." Leisure Sciences 34, no. 5 (2012): 395–416. http://dx.doi.org/10.1080/01490400.2012.714701.

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24

Alkire, Sabina, and Maria Emma Santos. "A Multidimensional Approach: Poverty Measurement & Beyond." Social Indicators Research 112, no. 2 (2013): 239–57. http://dx.doi.org/10.1007/s11205-013-0257-3.

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25

Hizgilov, Albert, and Jacques Silber. "On Multidimensional Approaches to Financial Literacy Measurement." Social Indicators Research 148, no. 3 (2019): 787–830. http://dx.doi.org/10.1007/s11205-019-02227-4.

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26

Alkire, Sabina, and James Foster. "Understandings and misunderstandings of multidimensional poverty measurement." Journal of Economic Inequality 9, no. 2 (2011): 289–314. http://dx.doi.org/10.1007/s10888-011-9181-4.

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27

Sumi, Chikayoshi, and Tomonori Ebisawa. "Phantom experiments of axial strain measurements using multidimensional autocorrelation method, multidimensional Doppler method and direct strain measurement method." Acoustical Science and Technology 30, no. 2 (2009): 117–23. http://dx.doi.org/10.1250/ast.30.117.

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28

Valliere, Dave. "Multidimensional entrepreneurial intent: an internationally validated measurement approach." International Journal of Entrepreneurial Behavior & Research 23, no. 1 (2017): 59–77. http://dx.doi.org/10.1108/ijebr-08-2015-0182.

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Purpose Entrepreneurial intent (EI) is a foundational construct in theories of entrepreneurship. But three challenges currently threaten the author’s ability to accurately measure EI. First, previous measurement approaches have confounded EI with closely related but theoretically distinct constructs such as attitudes and beliefs about entrepreneurship. Second, they have treated EI as an “all-or-nothing” decision, without reflecting the step-wise commitment of the entrepreneuring process. And finally, much of past EI research has been done in Western developed countries without validation in a
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29

Bergener, M., and E. U. Kranzhoff. "Measurement in Psychogeriatrics." International Psychogeriatrics 4, no. 3 (1992): 101–15. http://dx.doi.org/10.1017/s1041610292001194.

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Stake's concept of Responsive Evaluation is applied in evaluating the chain of psychogeriatric services of a general psychiatric hospital. Central to the approach presented are methodological considerations in describing individual treatment courses in their objective and subjective features. This can only be accomplished by establishing multidimensional strategies, incorporating biological, mental, psychological, and sociocultural aspects.
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30

Brown, Giorgina, and Federica Pintaldi. "A multidimensional approach in the measurement of underemployment." Statistical Journal of the United Nations Economic Commission for Europe 23, no. 1 (2006): 43–56. http://dx.doi.org/10.3233/sju-2006-23105.

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31

Ringbeck, T., T. Möller, and B. Hagebeuker. "Multidimensional measurement by using 3-D PMD sensors." Advances in Radio Science 5 (June 12, 2007): 135–46. http://dx.doi.org/10.5194/ars-5-135-2007.

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Abstract. Optical Time-of-Flight measurement gives the possibility to enhance 2-D sensors by adding a third dimension using the PMD principle. Various applications in the automotive (e.g. pedestrian safety), industrial, robotics and multimedia fields require robust three-dimensional data (Schwarte et al., 2000). These applications, however, all have different requirements in terms of resolution, speed, distance and target characteristics. PMDTechnologies has developed 3-D sensors based on standard CMOS processes that can provide an optimized solution for a wide field of applications combined w
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32

de Boer, Noortje. "Street-level Enforcement Style: A Multidimensional Measurement Instrument." International Journal of Public Administration 42, no. 5 (2018): 380–91. http://dx.doi.org/10.1080/01900692.2018.1465954.

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33

Thimmaiah, Navitha. "Multidimensional Measurement of Poverty: A Study in Mysore." Indian Journal of Human Development 9, no. 2 (2015): 235–59. http://dx.doi.org/10.1177/0973703020150205.

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34

Chattier, Priya. "Multidimensional, Gender-Sensitive Poverty Measurement: Perspectives from Fiji." Contemporary Pacific 28, no. 1 (2016): 31–57. http://dx.doi.org/10.1353/cp.2016.0012.

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35

Jaquet, Vincent, Chieh Hsu, and Attila Becskei. "Measurement of bistability in a multidimensional parameter space." Integrative Biology 9, no. 2 (2017): 167–77. http://dx.doi.org/10.1039/c6ib00242k.

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36

Wineman, Ayala. "Multidimensional Household Food Security Measurement in Rural Zambia." Agrekon 55, no. 3 (2016): 278–301. http://dx.doi.org/10.1080/03031853.2016.1211019.

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37

Liu, Xiang Dong, Yu Xuan Wu, Na Liu, and Wen Li Cai. "Multidimensional portfolio risk measurement: a mixed copula approach." International Journal of Computing Science and Mathematics 12, no. 3 (2020): 228. http://dx.doi.org/10.1504/ijcsm.2020.10033976.

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38

Cai, Wen Li, Na Liu, Yu Xuan Wu, and Xiang Dong Liu. "Multidimensional portfolio risk measurement: a mixed copula approach." International Journal of Computing Science and Mathematics 12, no. 3 (2020): 228. http://dx.doi.org/10.1504/ijcsm.2020.111708.

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39

FUKAWA, Yuko. "Multidimensional approach to measurement of interest in reading." Proceedings of the Annual Convention of the Japanese Psychological Association 75 (September 15, 2011): 3AM129. http://dx.doi.org/10.4992/pacjpa.75.0_3am129.

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40

Rutherford, Brian N., James S. Boles, and Scott C. Ambrose. "Reconceptualizing the measurement of multidimensional salesperson job satisfaction." Journal of Personal Selling & Sales Management 39, no. 3 (2019): 287–98. http://dx.doi.org/10.1080/08853134.2019.1601018.

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41

McGuire, Deborah B. "Comprehensive and multidimensional assessment and measurement of pain." Journal of Pain and Symptom Management 7, no. 5 (1992): 312–19. http://dx.doi.org/10.1016/0885-3924(92)90064-o.

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42

Puputti, Sari, Heikki Aisala, Ulla Hoppu, and Mari Sandell. "Multidimensional measurement of individual differences in taste perception." Food Quality and Preference 65 (April 2018): 10–17. http://dx.doi.org/10.1016/j.foodqual.2017.12.006.

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43

Permanyer, Iñaki. "Book review of Multidimensional Poverty Measurement and Analysis." Journal of Economic Inequality 14, no. 3 (2016): 353–56. http://dx.doi.org/10.1007/s10888-016-9331-9.

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44

Pietro, Cipresso, Serino Silvia, and Riva Giuseppe. "The Pursuit of Happiness Measurement: A Psychometric Model Based on Psychophysiological Correlates." Scientific World Journal 2014 (2014): 1–15. http://dx.doi.org/10.1155/2014/139128.

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Everyone is interested in the pursuit of happiness, but the real problem for the researchers is how to measure it. Our aim was to deeply investigate happiness measurement through biomedical signals, using psychophysiological methods to objectify the happiness experiences measurements. The classic valence-arousal model of affective states to study happiness has been extensively used in psychophysiology. However, really few studies considered a real combination of these two dimensions and no study further investigated multidimensional models. More, most studies focused mainly on self-report to m
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45

Vitko, Aleksandr Viktorovich. "Bulk properties of multidimensional objects." Interactive science, no. 9 (43) (September 19, 2019): 30–33. http://dx.doi.org/10.21661/r-498027.

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For the purpose of learning multidimensional models, difficult for perception, representations and technology (device) of the description and measurement of volume and amount of the substance filling the volume of multidimensional objects are considered. Alternative options of multidimensional set of one-dimensional models and unified multidimensional model of three-dimensional objects are compared. The technology of measurement of multidimensional volume and amount of the substance that fills volume is shown. The authors came to the conclusion when transferring from a set of coordinate vector
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46

Paap, Muirne C. S., Sebastian Born, and Johan Braeken. "Measurement Efficiency for Fixed-Precision Multidimensional Computerized Adaptive Tests: Comparing Health Measurement and Educational Testing Using Example Banks." Applied Psychological Measurement 43, no. 1 (2018): 68–83. http://dx.doi.org/10.1177/0146621618765719.

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It is currently not entirely clear to what degree the research on multidimensional computerized adaptive testing (CAT) conducted in the field of educational testing can be generalized to fields such as health assessment, where CAT design factors differ considerably from those typically used in educational testing. In this study, the impact of a number of important design factors on CAT performance is systematically evaluated, using realistic example item banks for two main scenarios: health assessment (polytomous items, small to medium item bank sizes, high discrimination parameters) and educa
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47

Ambel, Alemayehu Azeze, Harriet Kasidi Mugera, and Robert E. S. Bain. "Accounting for drinking water quality in measuring multidimensional poverty in Ethiopia." PLOS ONE 15, no. 12 (2020): e0243921. http://dx.doi.org/10.1371/journal.pone.0243921.

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The Multidimensional Poverty Index is used increasingly to measure poverty in developing countries. The index is constructed using selected indicators that cover health, education, and living standards dimensions. The accuracy of this tool, however, depends on how each indicator is measured. This study explores the effect of accounting for water quality in multidimensional poverty measurement. Access to drinking water is traditionally measured by water source types. The study uses a more comprehensive measure, access to safely managed drinking water services, which are free from E. coli contam
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48

Gallardo, Mauricio. "Measuring Vulnerability to Multidimensional Poverty." Social Indicators Research 148, no. 1 (2019): 67–103. http://dx.doi.org/10.1007/s11205-019-02192-y.

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Abstract A method to measure vulnerability to multidimensional poverty is proposed under a mean–risk behaviour approach. We extend the unidimensional downside mean–semideviation measurement of vulnerability to poverty towards the multidimensional space by incorporating this approach into Alkire and Foster’s multidimensional counting framework. The new approach is called the vulnerability to multidimensional poverty index (VMPI), alluding to the fact that it can be used to assess vulnerability to poverty measured by the multidimensional poverty index (MPI). The proposed family of vulnerability
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49

Lekobane, Khaufelo Raymond, and Keetie Roelen. "Leaving No One Behind: Multidimensional Child Poverty in Botswana." Child Indicators Research 13, no. 6 (2020): 2003–30. http://dx.doi.org/10.1007/s12187-020-09744-6.

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Abstract Child poverty measurement is vital for informing policies and for improving children’s lives. Nevertheless, efforts to measure (child) poverty remain dominated mainly by monetary approaches, and many countries fail to monitor multidimensional child poverty. Using the 2015/2016 Botswana multi-topic household survey, this study developed a child-centred, individual-level and composite measure that offers nationally relevant and context-specific insights into the magnitude and depth of multidimensional child poverty in Botswana. In particular, it did so through the lens of Leave No One B
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50

Jak, Suzanne, Frans J. Oort, and Conor V. Dolan. "Measurement bias and multidimensionality; an illustration of bias detection in multidimensional measurement models." AStA Advances in Statistical Analysis 94, no. 2 (2010): 129–37. http://dx.doi.org/10.1007/s10182-010-0128-z.

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