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Introduction to mediation, moderation, and conditional process analysis : a regression-based approach / 2nd ed

Introduction to mediation, moderation, and conditional process analysis : a regression-based approach / 2nd ed (69회 대출)

자료유형
단행본
개인저자
Hayes, Andrew F.
서명 / 저자사항
Introduction to mediation, moderation, and conditional process analysis : a regression-based approach / Andrew F. Hayes.
판사항
2nd ed.
발행사항
New York :   Guilford Press,   c2018.  
형태사항
xx, 692 p. ; 27 cm.
총서사항
Methodology in the social sciences
ISBN
9781462534654 (hardcover)
서지주기
Includes bibliographical references and index.
일반주제명
Social sciences --Statistical methods. Mediation (Statistics). Regression analysis.
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010 ▼a 2017039263
020 ▼a 9781462534654 (hardcover)
035 ▼a (KERIS)REF000018494526
040 ▼a DLC ▼b eng ▼e rda ▼c DLC ▼d 211009
050 0 0 ▼a HA31.3 ▼b .H39 2018
082 0 0 ▼a 001.4/22 ▼2 23
084 ▼a 001.422 ▼2 DDCK
090 ▼a 001.422 ▼b H417i2
100 1 ▼a Hayes, Andrew F. ▼0 AUTH(211009)20100
245 1 0 ▼a Introduction to mediation, moderation, and conditional process analysis : ▼b a regression-based approach / ▼c Andrew F. Hayes.
250 ▼a 2nd ed.
260 ▼a New York : ▼b Guilford Press, ▼c c2018.
300 ▼a xx, 692 p. ; ▼c 27 cm.
490 1 ▼a Methodology in the social sciences
504 ▼a Includes bibliographical references and index.
650 0 ▼a Social sciences ▼x Statistical methods.
650 0 ▼a Mediation (Statistics).
650 0 ▼a Regression analysis.
830 0 ▼a Methodology in the social sciences.
945 ▼a KLPA

No. 소장처 청구기호 등록번호 도서상태 반납예정일 예약 서비스
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No. 1 소장처 세종학술정보원/인문자료실1/ 청구기호 001.422 H417i2 등록번호 151345680 도서상태 대출가능 반납예정일 예약 서비스

컨텐츠정보

목차

Section	Section Description	Page Number
Part I	Fundamental Concepts	
1	    Introduction	p. 3
1.1	        A Scientist in Training	p. 3
1.2	        Questions of Whether, If, How, and When	p. 5
1.3	        Conditional Process Analysis	p. 9
1.4	        Correlation, Causality, and Statistical Modeling	p. 15
1.5	        Statistical Software	p. 18
1.6	        Overview of This Book	p. 20
1.7	        Chapter Summary	p. 21
2	    Simple Linear Regression	p. 23
2.1	        Correlation and Prediction	p. 24
2.2	        The Simple Linear Regression Equation	p. 29
2.3	        Statistical Inference	p. 43
2.4	        Assumptions for Interpretation and Statistical Inference	p. 52
2.5	        Chapter Summary	p. 57
3	    Multiple Linear Regression	p. 59
3.1	        The Multiple Linear Regression Equation	p. 60
3.2	        Partial Association and Statistical Control	p. 66
3.3	        Statistical Inference in Multiple Regression	p. 75
3.4	        Statistical and Conceptual Diagrams	p. 78
3.5	        Chapter Summary	p. 82
Part II	Mediation Analysis	
4	    The Simple Mediation Model	p. 85
4.1	        The Simple Mediation Model	p. 86
4.2	        Estimation of the Direct, Indirect, and Total Effects of X	p. 90
4.3	        Example with Dichotomous X: The Influence of Presumed Media Influence	p. 93
4.4	        Statistical Inference	p. 100
4.5	        An Example with Continuous X: Economic Stress among Small-Business Owners	p. 117
4.6	        Chapter Summary	p. 122
5	    Multiple Mediator Models	p. 123
5.1	        The Parallel Multiple Mediator Model	p. 125
5.2	        Example Using the Presumed Media Influence Study	p. 130
5.3	        Statistical Inference	p. 137
5.4	        The Serial Multiple Mediator Model	p. 143
5.5	        Complementarity and Competition among Mediators	p. 156
5.6	        OLS Regression versus Structural Equation Modeling	p. 159
5.7	        Chapter Summary	p. 162
6	    Miscellaneous Topics in Mediation Analysis	p. 165
6.1	        What about Baron and Kenny?	p. 166
6.2	        Confounding and Causal Order	p. 172
6.3	        Effect Size	p. 184
6.4	        Multiple Xs or Ys: Analyze Separately or Simultaneously?	p. 193
6.5	        Reporting a Mediation Analysis	p. 198
6.6	        Chapter Summary	p. 202
Part III	Moderation Analysis	
7	    Fundamentals of Moderation Analysis	p. 207
7.1	        Conditional and Unconditional Effects	p. 211
7.2	        An Example: Sex Discrimination in the Workplace	p. 219
7.3	        Visualizing Moderation	p. 231
7.4	        Probing an Interaction	p. 234
7.5	        Chapter Summary	p. 244
8	    Extending Moderation Analysis Principles	p. 245
8.1	        Moderation Involving a Dichotomous Moderator	p. 246
8.2	        Interaction between Two Quantitative Variables	p. 254
8.3	        Hierarchical versus Simultaneous Entry	p. 268
8.4	        The Equivalence between Moderated Regression Analysis and a 2 × 2 Factorial Analysis of Variance	p. 271
8.5	        Chapter Summary	p. 280
9	    Miscellaneous Topics in Moderation Analysis	p. 281
9.1	        Truths and Myths about Mean Centering	p. 282
9.2	        The Estimation and Interpretation of Standardized Regression Coefficients in a Moderation Analysis	p. 290
9.3	        Artificial Categorization and Subgroups Analysis	p. 298
9.4	        More Than One Moderator	p. 300
9.5	        Reporting a Moderation Analysis	p. 315
9.6	        Chapter Summary	p. 320
Part IV	Conditional Process Analysis	
10	    Fundamentals of Conditional Process Analysis	p. 325
10.1	        Examples of Conditional Process Models in the Literature	p. 329
10.2	        Conditional Direct and Indirect Effects	p. 333
10.3	        Example: Hiding Your Feelings from Your Work Team	p. 338
10.4	        Statistical Inference	p. 348
10.5	        Conditional Process Analysis in PROCESS	p. 353
10.6	        Chapter Summary	p. 354
11	    Further Examples of Conditional Process Analysis	p. 357
11.1	        Revisiting the Sexual Discrimination Study	p. 358
11.2	        Moderation of the Direct and Indirect Effects in a Conditional Process Model	p. 368
11.3	        Visualizing the Direct and Indirect Effects	p. 378
11.4	        Mediated Moderation	p. 381
11.5	        Chapter Summary	p. 389
12	    Miscellaneous Topics in Conditional Process Analysis	p. 391
12.1	        A Strategy for Approaching Your Analysis	p. 393
12.2	        Can a Variable Simultaneously Mediate and Moderate Another Variable''s Effect?	p. 399
12.3	        Comparing Conditional Indirect Effects and a Formal Test of Moderated Mediation	p. 402
12.4	        The Pitfalls of Subgroups Analysis	p. 407
12.5	        Writing about Conditional Process Modeling	p. 412
12.6	        Chapter Summary	p. 415
Appendices	
A	    Using PROCESS	p. 419
B	    Monte Carlo Confidence Intervals in SPSS and SAS	p. 457
References	p. 461
Author Index	p. 485
Subject Index	p. 495
About the Author	p. 507

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