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Books on the topic 'Measuring Reliability'

Author: Grafiati

Published: 4 June 2021

Last updated: 16 February 2022

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1

Kałuski, Jan. Metody analizy niezawodności metrologicznej. Politechnika Śląska, 1985.

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2

Różdżyński, Kazimierz. Operational semi-automatic verification of telelimnimetric data under metrological analysis. Institute of Meteorology and Water Management, National Research Institute, 2011.

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3

Measuring computer performance: A practitioner's guide. Cambirdge University Press, 2000.

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4

Lepicovsky, J. Seeding for laser velocimetry in confined supersonic flows with shocks. National Aeronautics and Space Administration, 1996.

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5

Lepicovsky, J. Seeding for laser velocimetry in confined supersonic flows with shocks. National Aeronautics and Space Administration, 1996.

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6

Jackson, Brian A. The problem of measuring emergency preparedness: The need for assessing "response reliability" as part of homeland security planning. RAND Corp., 2008.

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7

Jackson, Brian A. The problem of measuring emergency preparedness: The need for assessing "response reliability" as part of homeland security planning. RAND Corp., 2008.

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8

Jackson, Brian A. The problem of measuring emergency preparedness: The need for assessing "response reliability" as part of homeland security planning. RAND Corp., 2008.

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9

Jackson, Brian A. The problem of measuring emergency preparedness: The need for assessing "response reliability" as part of homeland security planning. RAND Corp., 2008.

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10

Evers, G. C. M. Appraisal of self-care agency A.S.A.-scale: Reliability and validity testing of the Dutch version of the A.S.A.-scale measuring Orem's concept 'Self-care Agency'. Van Gorcum, 1989.

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11

service), SpringerLink (Online, ed. Measurement Uncertainties: Physical Parameters and Calibration of Instruments. Springer Berlin Heidelberg, 2012.

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12

Hollyer, James R. Measuring Governance. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198817062.003.0005.

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Researchers typically construct measures of governance through one of two methods (or some combination thereof): aggregation of the responses of a set of expert respondents to survey questionnaires, or aggregation of some set of factual data. This chapter examines the benefits and drawbacks to each methodology. By relying on expert respondents, researchers are able to ensure that a broad range of varied inputs inform their governance index. This methodology benefits from flexibility. By relying on carefully selected factual data and defined aggregation rules, researchers are able to ensure transparency and reliability, but typically restrict the set of information that influences their index. This chapter argues that, all else being equal, indexes that rely on objective inputs are more appropriate for theory testing, while those that rely on expert perceptions are more appropriate for ranking and assessment exercises.

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13

Streiner, David L., Geoffrey R. Norman, and John Cairney. Measuring change. Oxford University Press, 2015. http://dx.doi.org/10.1093/med/9780199685219.003.0011.

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Although the goal of many clinical assessments and research studies is to measure how much people change between two occasions, the measurement of change is fraught with conceptual and methodological difficulties. One of the difficulties is that there are (at least) two different reasons to measure change: to determine if intervention had any effect, and to identify the correlates of change. These two goals work against each other, because the former requires there to be little difference in the amount of change among people in the same group, while the latter depends on inter-individual differences. The chapter also discusses various biases that exist when people are asked directly how much they think they have changed. This chapter addresses the issues of the relationship of change to the reliability of the scale, difficulties of measuring change in experimental and quasi-experimental studies, and new approaches to measuring change, such as growth curve analysis.

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14

Handel, Michael J. Measuring Job Content. Edited by John Buchanan, David Finegold, Ken Mayhew, and Chris Warhurst. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199655366.013.5.

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Labour market research often relies on assumptions regarding job skill requirements but most information on job content is relatively thin or too general for easy interpretation, requiring new approaches to concepts and measurement. This chapter provides a detailed map of the domains that need to be measured and an approach to measuring them called explicit scaling, involving behaviourally concrete survey questions and response options with relatively fixed meanings across respondents. The measures capture both the diverse kinds of skills used at work and the complexity gradients that are the focus of recent concerns but which have largely eluded objective measurement. This chapter describes the measures first used in the survey of Skills, Technology, and Management Practices (STAMP) and presents empirical evidence on their validity and reliability, including comparisons with other established measures of job skill content.

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15

Lilja, David J. Measuring Computer Performance: A Practitioner's Guide. Cambridge University Press, 2000.

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16

Lilja, David J. Measuring Computer Performance: A Practitioner's Guide. Cambridge University Press, 2005.

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17

Schon, Klaus. High Impulse Voltage and Current Measurement Techniques: Fundamentals - Measuring Instruments - Measuring Methods. Springer, 2013.

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18

Schon, Klaus. High Impulse Voltage and Current Measurement Techniques: Fundamentals – Measuring Instruments – Measuring Methods. 2013.

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19

United States. National Aeronautics and Space Administration., ed. Worst case analysis: Earth sensor assembly for the Tropical Rainfall Measuring Mission observatory. National Aeronautics and Space Administration, 1993.

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20

Toni, Richards, ed. Measuring case mix and quality of care: Rater training and reliability in the graduate medical education study. Rand, 1987.

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21

Measuring scaffolding activity in mother-child interactions: Evidence for the reliability and validity of the system for rating tutor behaviour, SRTB2-R. National Library of Canada = Bibliothèque nationale du Canada, 1995.

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22

Richards, Toni. Measuring Case Mix and Quality of Care: Rater Training and Reliability in the Graduate Medical Education Study/Pbn R-3446-Hhs (Rand Corporation//Rand Report). Rand Corp, 1988.

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23

Evers, G. C. M. Appraisal of Self-care Agency: A.C.A.-Scale: Reliability and Validity Testing of the Dutch Version of the A.S.A.-scale Measuring Orem's Concept "Self-Care Agency". Van Gorcum and Comp BV, 1989.

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24

Otley, Anthony Roger. Validation of the IMPACT questionnaire for measuring health-related quality of life in paediatric inflammatory bowel disease: Sensibility, validity and reliability testing in a paediatric cohort. 2004.

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25

Kaufman, Julia, Elizabeth Steiner, Jonathan Schweig, Sophie Meyers, and Karen Christianson. Evidence on the Validity, Reliability, and Usability of the Measuring and Improving Student-Centered Learning (MISCL) Toolkit: Key Takeaways and Lessons on Developing Tools for School Improvement. RAND Corporation, 2020. http://dx.doi.org/10.7249/rr3235.

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26

Rose, Sage, and Nicole Sieben. Hope Measurement. Edited by Matthew W. Gallagher and Shane J. Lopez. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399314.013.7.

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This chapter covers the multiple measures currently used to assess hope theory. Hope, as theorized by Snyder and colleagues, was originally determined to be a global construct measuring agency and pathways toward goal attainment. Using much of the original theory, hope research has expanded, resulting in multiple measures across different applications and domains. By exploring the context specificity, these scales have been shown to consistently predict outcomes across differing domains, supporting the reliability and validity of new hope measurement. It is anticipated that with more specific hope measurement, the more accurate hope assessment and intervention can become. Concepts covered in this chapter include academic hope, math hope, writing hope, work hope, children’s hope, employment hope, and state hope.

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27

Maestas, Cherie. Expert Surveys as a Measurement Tool. Edited by Lonna Rae Atkeson and R. Michael Alvarez. Oxford University Press, 2016. http://dx.doi.org/10.1093/oxfordhb/9780190213299.013.13.

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Polling political elites, academics, or other types of knowledgeable experts has provided scholars with a trove of information about political institutions, processes, and local context. Expert surveys are an especially useful method for measuring concepts that would be difficult or impossible to measure through alternative strategies and permits scholars to create indicators that are comparable across diverse contextual settings. This chapter provides an overview of the key questions researchers face when using experts as a tool of measurement. It highlights considerations regarding survey design, questionnaire design, and aggregation procedures with an eye toward identifying ways to enhance the validity and reliability of expert-based measures. The chapter also emphasizes the importance of design transparency and systematic reporting of procedures and measures of uncertainty about scores derived from expert surveys.

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28

Gupta, S. V. Measurement Uncertainties: Physical Parameters and Calibration of Instruments. Springer, 2012.

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