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| 001 | EBC4975368 | ||
| 003 | MiAaPQ | ||
| 005 | 20191009123143.0 | ||
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| 007 | cr cnu|||||||| | ||
| 008 | 191009s2010 xx o ||||0 eng d | ||
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_a9780826137975 _q(electronic bk.) |
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| 035 | _a(MiAaPQ)EBC4975368 | ||
| 035 | _a(Au-PeEL)EBL4975368 | ||
| 035 | _a(CaONFJC)MIL256619 | ||
| 035 | _a(OCoLC)608691522 | ||
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_aMiAaPQ _beng _erda _epn _cMiAaPQ _dMiAaPQ |
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| 050 | 4 | _aBF176.5.Y63 2009 | |
| 082 | 0 | _a150.287 | |
| 100 | 1 | _aYoder, Paul. | |
| 245 | 1 | 0 | _aObservational Measurement of Behavior. |
| 250 | _a1st ed. | ||
| 264 | 1 |
_aNew York : _bSpringer Publishing Company, _c2010. |
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| 264 | 4 | _c�2010. | |
| 300 | _a1 online resource (249 pages) | ||
| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 505 | 0 | _aCover -- Contents -- List of Figures -- List of Tables -- Foreword -- Preface -- Acknowledgments -- 1 Introduction and Measurement Contexts -- Overview -- Systematic Observation -- Count Coding Systems -- Importance of Falsifiable Research Questions or Hypotheses -- Behavior as "Behavior" Versus Behavior as a Sign or Indicant of a Construct -- Two Interpretations of Operationalism -- Distinction Between Context-Dependent Behavior and Generalized Tendencies to Behave -- Rationale for Identifying How We Are Conceptualizing Our Object of Measurement -- Influential Variables of a Measurement Context -- Structuredness -- Ecological Validity -- Tension Between Structuredness and Ecological Validity -- Recommendations for Measuring Generalized Characteristics From Observations -- Potential Disadvantages of Systematic Observational Count Measurement -- Recommendations -- References -- 2 Improving Measurement of Generalized Characteristics Through Direct Observation and Generalizability Theory -- Overview -- Two Concepts of Measurement -- Generalizability Theory as a Measurement Theory for Vaganotic Measures -- Example: Generalizability (G) Study With Multiple Sessions as a Single Facet -- Consequences of a Low G Coefficient -- Decision Studies -- McWilliam and Ware as an Example of a Two-Faceted Decision Study -- Practice Using a G Calculator on Data From a Two-Faceted G and D Study -- Accuracy of D Study Projections -- Implications of the Lessons of G and D Studies for Single-Subject Research -- A Dilemma -- Recommendations -- References -- 3 Designing or Adapting Coding Manuals -- Overview -- Selecting, Adapting, or Creating a Coding Manual -- Definition of a Coding Manual -- Relation of the Coding Manual to the Research Questions and Predictions -- Recommended Steps for Modifying or Designing Coding Manuals -- The Potential Value of Flowcharts. | |
| 505 | 8 | _aDo Coding Manuals Need to Be Sufficiently Short to Be Included in Methods Sections? -- Recommendations -- References -- 4 Sampling Methods -- Overview -- The Elements of a Measurement System -- Behavior Sampling -- Continuous Behavior Sampling -- Intermittent Behavior Sampling -- Interval Sampling -- Participant Sampling -- Focal Sampling -- Multiple Pass Sampling -- Conspicuous Sampling -- Reactivity -- Live Coding Versus Recording the Observation for Later Coding -- Recording Coding Decisions -- Practice Recording Session -- Recommendations -- References -- 5 Common Metrics of Observational Variables -- Overview -- Definition of Metric -- Quantifiable Dimensions of Behavior -- Proportion Metrics -- Proportion Metrics Change the Meaning of Observational Variables -- Scrutinizing Proportions -- An Implicit Assumption of Proportion Metrics -- Testing Whether the Data Fit the Assumption of Proportion Metrics -- Consequences of Using a Proportion When the Data Do Not Fit the Assumption -- Alternative Methods to Control Nuisance Variables -- Statistical Control -- Procedural Control -- Transforming Metrics of Observational Variables in Group Statistical Analyses -- Scales of Measurement for Observational Variables -- Observational Variables in Parametric Analyses -- Recommendations -- References -- 6 Introduction to Sequential Analysis -- Overview -- Definitions of Terms Used in This Chapter -- Sequential Versus Nonsequential Variables -- Sequential Associations Are Not Sufficient Evidence for Causal Inferences -- Coded Units and Exhaustiveness -- Three Major Types of Sequential Analysis -- Event-Lag Sequential Analysis -- Time-Lag Sequential Analysis -- Time-Window Sequential Analysis -- The Need to "Control for Chance" -- How Sequential Data Are Represented Prior to Contingency Table Organization -- Contingency Tables. | |
| 505 | 8 | _aProper 2 × 2 Contingency Table Construction of Two Streams of Data for Concurrent Analysis -- Proper 2 × 2 Contingency Table Construction From One Stream of Data for Event-Lag Sequential Analysis -- Simulation Study to Compare Results From Two Ways to Construct Contingency Tables -- Contingency Tables for Time-Window Lag Sequential Analysis -- Transitional Probability -- Transitional Probabilities in Backward Sequential Analysis -- Summary of Transitional Probabilities -- Recommendations -- References -- 7 Analyzing Research Questions Involving Sequential Associations -- Overview -- Computer Software to Aid Sequential Analysis -- Practice Exercise Using MOOSES Software to Conduct Time-Window Analysis -- Yule's Q -- What Is "Enough Data" and How Do We Attain It? -- Proposed Solutions for Insufficient Data -- Sequential Association Indices as Dependent Variables in Group Designs -- Testing the Significance of a Mean Sequential Association -- Testing the Between-Group Difference in Mean Sequential Associations -- Testing the Within-Subject Difference in Sequential Associations -- Testing the Significance of the Summary-Level Association Between a Participant Characteristic and a Sequential Association Between Behaviors -- Statistical Significance Testing of Sequential Associations in Single Cases -- A Caveat Regarding the Use of Yule's Q -- Recommendations -- References -- 8 Observer Training, Observer Drift Checks, and Discrepancy Discussions -- Overview -- Three Purposes of Point-by-Point Agreement on Coding Decisions -- Two Definitions of Agreement -- Agreement Matrices -- Discrepancy Discussions -- Criterion Coding Standards -- Observer Training -- Method of Selecting and Conducting Agreement Checks -- Retraining When Observer Drift Is Identified -- Recommendations -- References -- 9 Interobserver Agreement and Reliability of Observational Variables. | |
| 505 | 8 | _aOverview -- Additional Purposes of Point-by-Point Agreement -- Added Principles When Agreement Checks Are Used to Estimate Interobserver "Reliability" of Observational Variable Scores -- Exhaustive Coding Spaces Revisited -- The Effect of Chance on Agreement -- Common Indices of Point-by-Point Agreement -- Occurrence Percentage Agreement -- Nonoccurrence Percentage Agreement -- Total Percentage Agreement -- Kappa -- Base Rate and Chance Agreement Revisited -- Intraclass Correlation Coefficient as an Index of Interobserver Reliability from the Vaganotic Concept of Measurement -- Options for Running ICC With SPSS -- Between-Participant Variance on the Variable of Interest Affects ICC -- Using ICC as a Measure of Interobserver Reliability for Predictors and Dependent Variables in Group Designs -- The Interpretation of SPSS Output for ICC -- The Conceptual Relation Between Interobserver Agreement and ICC -- Consequences of Low or Unknown Interobserver Reliability -- Recommendations -- References -- 10 Validation of Observational Variables -- Overview -- The Changing Concept of Validation -- Understanding Which Types of Validation Evidence Are Most Relevant for Different Research Designs, Objects of Measurement, and Research Purposes -- Content Validation -- Definition of Content Validation -- Different Traditions Vary on the Levels of Importance Placed on Content Validation -- Weaknesses of Content Validation -- Sensitivity to Change -- Definition of Sensitivity to Change -- Influences on Sensitivity to Change -- Weakness of Sensitivity to Change -- Treatment Utility -- Definition of Treatment Utility -- Weaknesses of Treatment Utility -- Criterion-Related Validation -- Definition of Criterion-Related Validation -- Primary Appeal of Criterion-Related Validation -- Weaknesses of Criterion-Related Validation -- Construct Validation. | |
| 505 | 8 | _aDefinition of Construct Validation -- Discriminative Validation -- Nomological Validation -- Multitrait, Multimethod Validation -- An Implicit "Weakness" of Science? -- Recommendations -- References -- Glossary -- A -- B -- C -- D -- E -- F -- G -- H -- I -- K -- L -- M -- N -- O -- P -- R -- S -- T -- U -- V -- W -- Y -- Index -- A -- B -- C -- D -- E -- F -- G -- I -- K -- L -- M -- N -- O -- P -- R -- S -- T -- U -- V -- W -- Y -- Z. | |
| 520 | _a"Yoder and Symons bring decades of work to bear and it shows....[The book is] presented with broad scholarship and conceptual depth." -Roger Bakeman, PhD Professor. | ||
| 588 | _aDescription based on publisher supplied metadata and other sources. | ||
| 590 | _aElectronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2019. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries. | ||
| 650 | 0 | _aObservation - methods. | |
| 655 | 4 | _aElectronic books. | |
| 700 | 1 | _aSymons, Frank. | |
| 700 | 1 | _aSymons, Frank. | |
| 776 | 0 | 8 |
_iPrint version: _aYoder, Paul _tObservational Measurement of Behavior _dNew York : Springer Publishing Company,c2010 |
| 797 | 2 | _aProQuest (Firm) | |
| 856 | 4 | 0 |
_uhttp://ezproxy01.ny.edu.hk:2048/login?url=https://ebookcentral.proquest.com/lib/ircp3g4/detail.action?docID=4975368 _zClick to View |
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