Livros sobre o tema "Statistical equivalence"

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1

Wellek, Stefan. Testing statistical hypotheses of equivalence. Boca Raton, FL: Chapman & Hall/CRC, 2003.

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2

Wellek, Stefan. Testing statistical hypotheses of equivalence and noninferiority. 2a ed. Boca Raton: CRC Press, 2010.

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3

Pardo, Scott. Equivalence and noninferiority tests for quality, manufacturing and test engineers. Boca Raton: Chapman and Hall/CRC, 2014.

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4

Giannangelo, Kathy. Transitioning to ICD-10-CM/PCS: The essential guide to general equivalence mappings (GEMs). Chicago: AHIMA Press, 2011.

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5

Berry, Kenneth J., e Janis E. Johnston. Statistical Methods: Connections, Equivalencies, and Relationships. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-41896-9.

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6

Patterson, Scott D. Bioequivalence and statistics in clinical pharmacology. Boca Raton: Chapman & Hall/CRC, 2006.

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7

Patterson, Scott D. Bioequivalence and statistics in clinical pharmacology. Boca Raton, FL: Chapman & Hall/CRC Press, 2005.

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8

Bekker, Paul A. Identification, equivalent models, and computer algebra. Boston: Academic Press, 1994.

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9

Scales, Maharashtra (India) Equivalence Committee for Revision of Pay. Report of the Equivalence Committee for Revision of Pay Scales, Maharashtra State. Bombay: The Committee, 1987.

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10

Florida. State Board of Community Colleges., ed. GED preparatory programs in Florida community colleges: Level III program review report. [Tallahassee, Fla.]: The Board, 1998.

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11

Gerald, Bala, e New York (State). Dept. of Correctional Services. Division of Program Planning, Research, and Evaluation, eds. Follow-up study of a sample of offenders who earned high school equivalency diplomas while incarcerated. Albany, N.Y: State of New York, Dept. of Correctional Services, Division of Program Planning, Research and Evaluation, 1986.

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12

Webb, Alan J. Estimates of producer and consumer subsidy equivalents: Government intervention in agriculture, 1982-87. [Washington, D.C.]: U.S. Dept. of Agriculture, Economic Research Service, 1990.

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13

Kim, Kwang. Participation in basic skills education, 1994-95. Washington, D.C.?]: National Center for Education Statistics, 1997.

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14

Kim, Kwang. Participation in basic skills education, 1994-95. [Washington, D.C.?]: National Center for Education Statistics, 1997.

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15

Chow, Shein-Chung. Design and analysis of bioavailability and bioequivalence studies. 3a ed. Boca Raton: Chapman & Hall/CRC, 2009.

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16

United States. Dept. of Agriculture. Economic Research Service., ed. Estimates of producer and consumer subsidy equivalents: Government intervention in agriculture, 1982-92. Washington, DC: U.S. Dept. of Agriculture, Economic Research Service, 1994.

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17

Dudek, Hanna. Skale ekwiwalentności-- estymacja na podstawie kompletnych modeli popytu: Equivalence scales--estimation on the base of complete demand systems. Warszawa: Wydawnictwo SGGW, 2011.

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18

Chow, Shein-Chung. Design and analysis of bioavailability and bioequivalence studies. 2a ed. New York: M. Dekker, 2000.

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19

Chow, Shein-Chung. Design and analysis of bioavailability and bioequivalence studies. New York: M. Dekker, 1992.

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20

Chow, Shein-Chung. Statistics in drug research: Methodologies and recent developments. New York: M. Dekker, 2002.

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21

li-sṭaṭisṭiḳah, Israel Lishkah ha-merkazit. Talmide kitot 12, mi-shenat ha-limudim 754 she-nivḥanu bi-veḥinot bagrut uvi-veḥinot gemer bi-shenat 1994 ṿe-zakaʼim li-teʻudah, lefi yishuvim. Yerushalayim: ha-Lishkah ha-merkazit li-sṭaṭisṭiḳah, 1997.

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22

li-sṭaṭisṭiḳah, Israel Lishkah ha-merkazit. Nivḥanim bi-veḥinot bagrut uvi-veḥinot gemer ṿe-zakaʼim li-teʻudah 754. Yerushalayim: ha-Lishkah ha-merkazit li-sṭaṭisṭiḳah, 1997.

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23

li-sṭaṭisṭiḳah, Israel Lishkah ha-merkazit. Talmide kitot 12, nivḥanim bi-veḥinot bagrut ṿe-zakaʼim li-teʻudah, lefi yishuv megurim 1996. Yerushalayim: ha-Lishkah ha-merkazit li-sṭaṭisṭiḳah, 1999.

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24

li-sṭaṭisṭiḳah, Israel Lishkah ha-merkazit. Talmide kitot 12, nivḥanim bi-veḥinot bagrut ṿe-zakaʼim li-teʻudah, lefi yishuv megurim 1998. Yerushalayim: ha-Lishkah ha-merkazit li-sṭaṭisṭiḳah, 2002.

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25

li-sṭaṭisṭiḳah, Israel Lishkah ha-merkazit. Nivḥanim bi-veḥinot bagrut uvi-veḥinot gemer ṿe-zakaʼim li-teʻudah 756. Yerushalayim: ha-Lishkah ha-merkazit li-sṭaṭisṭiḳah, 2000.

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26

United States International Trade Commission. Estimated tariff equivalents of U.S. quotas on agricultural imports and analysis of competitive conditions in U.S. and foreign markets for sugar, meat, peanuts, cotton, and dairy products: Report to the president on investigation no. 332-281 under section 332(g) of the Tariff Act of 1930, as amended. Washington, DC: The Commission, 1990.

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27

Wellek, Stefan. Testing Statistical Hypotheses of Equivalence. Taylor & Francis Group, 2003.

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28

Wellek, Stefan. Testing Statistical Hypotheses of Equivalence. Chapman and Hall/CRC, 2002. http://dx.doi.org/10.1201/9781420035964.

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29

Wellek, Stefan. Testing Statistical Hypotheses of Equivalence. Chapman & Hall/CRC, 2002.

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30

Wellek, Stefan. Testing Statistical Hypotheses of Equivalence. Taylor & Francis Group, 2002.

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31

Wellek, Stefan. Testing Statistical Hypotheses of Equivalence and Noninferiority. Taylor & Francis Group, 2010.

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32

Wellek, Stefan. Testing Statistical Hypotheses of Equivalence and Noninferiority. Taylor & Francis Group, 2010.

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33

Wellek, Stefan. Testing Statistical Hypotheses of Equivalence and Noninferiority. Taylor & Francis Group, 2010.

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34

Wellek, Stefan. Testing Statistical Hypotheses of Equivalence and Noninferiority. Chapman and Hall/CRC, 2010. http://dx.doi.org/10.1201/ebk1439808184.

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35

Tran, Thanh V., Tam Nguyen e Keith Chan. Assessing and Testing Cross-Cultural Measurement Equivalence. Oxford University Press, 2018. http://dx.doi.org/10.1093/acprof:oso/9780190496470.003.0004.

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A cross-cultural comparison can be misleading for two reasons: (1) comparison is made using different attributes and (2) comparison is made using different scale units. This chapter illustrates multiple statistical approaches to evaluating the cross-cultural equivalence of the research instruments: data distribution of the items of the research instrument, the patterns of responses of each item, the corrected item–total correlation, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), and reliability analysis using the parallel test and tau-equivalence test. Equivalence is the fundamental issue in cross-cultural research and evaluation.
36

Pardo, Scott. Equivalence and Noninferiority Tests for Quality Manufacturing and Test Engineers. Taylor & Francis Group, 2019.

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37

Pardo, Scott. Equivalence and Noninferiority Tests for Quality, Manufacturing and Test Engineers. Taylor & Francis Group, 2013.

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38

Pardo, Scott. Equivalence and Noninferiority Tests for Quality, Manufacturing and Test Engineers. Taylor & Francis Group, 2013.

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39

Pardo, Scott. Equivalence and Noninferiority Tests for Quality, Manufacturing and Test Engineers. Taylor & Francis Group, 2013.

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40

Horing, Norman J. Morgenstern. Quantum Mechanical Ensemble Averages and Statistical Thermodynamics. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198791942.003.0006.

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Chapter 6 introduces quantum-mechanical ensemble theory by proving the asymptotic equivalence of the quantum-mechanical, microcanonical ensemble average with the quantum grand canonical ensemble average for many-particle systems, based on the method of Darwin and Fowler. The procedures involved identify the grand partition function, entropy and other statistical thermodynamic variables, including the grand potential, Helmholtz free energy, thermodynamic potential, Gibbs free energy, Enthalpy and their relations in accordance with the fundamental laws of thermodynamics. Accompanying saddle-point integrations define temperature (inverse thermal energy) and chemical potential (Fermi energy). The concomitant emergence of quantum statistical mechanics and Bose–Einstein and Fermi–Dirac distribution functions are discussed in detail (including Bose condensation). The magnetic moment is derived from the Helmholtz free energy and is expressed in terms of a one-particle retarded Green’s function with an imaginary time argument related to inverse thermal energy. This is employed in a discussion of diamagnetism and the de Haas-van Alphen effect.
41

Birch, Jonathan. Kin Selection and Group Selection. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198733058.003.0004.

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In group-structured populations in which some other assumptions are satisfied, kin and group selectionist methods provide formally equivalent conditions for change. However, this only shows an equivalence between two statistical methodologies, and this is compatible with there being a real, causal distinction between kin and group selection processes. This chapter pursues a Hamilton-inspired, population-centred approach to drawing that distinction, on which the differences between kin and group selection are differences of degree in the structural properties of populations. The relevant properties are K, the overall degree to which genealogical kin interact differentially, and G, the overall degree to which the population contains stable, internally integrated, and externally isolated social groups. A spatial metaphor (‘K-G space’) provides a useful framework for thinking about these differences.
42

Patterson, Scott D., e Byron Jones. Bioequivalence and Statistics in Clinical Pharmacology. Taylor & Francis Group, 2017.

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43

Patterson, Scott D., e Byron Jones. Bioequivalence and Statistics in Clinical Pharmacology. Taylor & Francis Group, 2017.

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44

Patterson, Scott D., e Byron Jones. Bioequivalence and Statistics in Clinical Pharmacology. Taylor & Francis Group, 2017.

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45

Patterson, Scott D., e Byron Jones. Bioequivalence and Statistics in Clinical Pharmacology. Taylor & Francis Group, 2017.

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46

Patterson, Scott D., e Byron Jones. Bioequivalence and Statistics in Clinical Pharmacology. Taylor & Francis Group, 2021.

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47

Tran, Thanh, Tam Nguyen e Keith Chan. Developing Cross-Cultural Measurement in Social Work Research and Evaluation. Oxford University Press, 2018. http://dx.doi.org/10.1093/acprof:oso/9780190496470.001.0001.

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Given the demographic changes and the reality of cultural diversity in the United States and other parts of the world today, social work researchers are increasingly aware of the need to conduct cross-cultural research and evaluation, whether for hypothesis testing or for outcome evaluation. This book’s aims are twofold: to provide an overview of issues and techniques relevant to the development of cross-cultural measures and to provide readers with a step-by-step approach to the assessment of cross-cultural equivalence of measurement properties. There is no discussion of statistical theory and principles underlying the statistical techniques presented in this book. Rather, this book is concerned with applied theories and principles of cross-cultural research, and draws information from existing work in the social sciences, public domain secondary data, and primary data from the author’s research. In this second edition, several changes have been made throughout the book and a new chapter on item response theory has been added. The chapter on developing new cross-cultural instrument has also been expanded with a concrete example.
48

Weiss, Helen. Design issues in global mental health trials in low-resource settings. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199680467.003.0004.

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In this chapter we outline the key principles in design and analysis of trials for mental health. The chapter focuses on randomized controlled trials as these are the gold-standard trial design, which minimizes confounding due to other factors and enables us to draw conclusions about the effectiveness of the intervention. Other key principles of trial design discussed in the chapter include methods to develop a clearly stated, testable research hypothesis, definition of well-defined outcomes, appropriate choice of the control condition, masking of providers and participants where possible, realistic sample size estimates, and appropriate data monitoring and statistical analysis plans. The chapter also outlines alternatives to the parallel arm superiority trial design, such as equivalence and non-inferiority trials, cross-over, stepped wedge, fixed adaptive, and patient preference trial designs.
49

Patterson, Scott D., e Byron Jones. Bioequivalence and Statistics in Clinical Pharmacology. Taylor & Francis Group, 2017.

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50

Patterson, Scott D., Scott Patterson e Byron Jones. Bioequivalence and Statistics in Clinical Pharmacology. Taylor & Francis Group, 2005.

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