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003			OSt
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008			200729s2021 flu b 001 0 eng
010			_a 2020030224
020			_a9780367630713 (hbk.)
040			_aDLC _beng _erda _cJKRC
082	0	0	_a006.312 _223 _bKRI.K
100	1		_aKrippendorff, Klaus. _eauthor. _930037
245	1	4	_aReliability of generating data / _cby Klaus Krippendorff.
250			_a1 st ed.
260			_aBoca Raton : _bChapman & Hall, CRC Press, _c2021.
300			_aix, 315 p. _c26 cm.
336			_atext _btxt _2rdacontent
337			_aunmediated _bn _2rdamedia
338			_avolume _bnc _2rdacarrier
504			_aIncludes bibliographical references and index.
520			_a"All data are the result of human actions whether by experimentations, observations, or declarations. As such, the presumption of knowing what data are about is subject of imperfections that can affect the validity of research efforts. With calls for data-based research comes the need to assure the reliability of generated data. Especially the reliability of converting texts into analyzable data has become a burning issue in several areas. However, this issue has been met by only a few limited, and sometimes misleading measures of the extent to which data can be trusted as surrogates of the phenomena of analytical interests. The statistic proposed by the author - "Krippendorff's Alpha" - is widely used in the social sciences, not only where human judgements are involved but also where measurements are compared. This book expands on the author's seminal work in content analysis and develops methods for assessing the reliability of the kind of data that previously defied evaluations for this purpose. It opens with a discussion of the epistemology of reliable data, then presents the most basic alpha coefficient for the single-valued coding of predefined units. This largely familiar way of measuring reliability provides the platform for the succeeding chapters which start with an overview of alternative coefficients and then expand alpha one quality after another, including to cope with the reliabilities of multi-valued coding, segmenting texts into meaningful units, big data, and information retrievals. It also includes a chapter on how to diagnose and remedy imperfections and one on applicable standards, all converging on the statistical issues of the reliability of generating data. Features: Provides an overview of methods for assessing the reliability of generating data Expands a statistic proposed by the author, already widely used in the social sciences Includes many easy to follow numerical examples to illustrate the measures Written to be useful to beginning and advanced researchers from many disciplines, notably linguistics, sociology, psychometric and educational research, and medical science"-- _cProvided by publisher.
650		0	_aQuantitative research _xReliability. _930038
650		0	_aData mining _xReliability. _930039
653			_aReliability of Generating Data
710			_aTaylor and Francis Group _ePublisher _930040
776	0	8	_iOnline version: _aKrippendorff, Klaus, _tThe reliability of generating data _b1. _dBoca Raton : Chapman & Hall, CRC Press, 2021. _z9781003112020 _w(DLC) 2020030225
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _c1 _e23 _n0
999			_c428569 _d428569