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PROCESS macro를 이용한 조절된 매개효과분석
이형권 저
신영사 2020.12.15.
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제 1장 PROCESS macro의 사용법
1.1 PROCESS macro를 설치하는 방법 ····························································· 17
1.1.1 dialog box의 설치방법(process.spd) / 17
1.1.2 command syntax의 설치와 사용 / 18
1.2 PROCESS macro의 사용 ·············································································· 18
1.2.1 dialog box의 사용 / 19
1.2.2 command syntax의 사용 / 19
1.2.3 PROCESS macro의 사용예제 / 20
1.2.4 dialog box의 메뉴와 syntax 명령문의 비교 / 24
1.2.5 dialog box에서 사용 불가능한 옵션들 / 30
1.2.6 PROCESS version 2에 비하여 version 3에서 달라진 중요한 변화들 / 30
1.2.7 PROCESS 사용시 유의사항 / 32
제 2장 단순매개모형
2.1 단순매개모형 ··································································································· 38
2.2 독립변수()의 직접효과와 간접효과 및 총효과의 추정 ···························· 41
2.2.1 의 에 대한 직접효과 / 42
2.2.2 의 에 대한 간접효과 / 43
2.2.3 의 에 대한 총효과 / 44
2.3 매개모형 1:미디어영향력 연구(가 이분형 변수) ··································· 46
2.3.1 회귀계수의 해석 / 48
2.3.2 PROCESS를 이용한 모형추정 / 50
차 례6 차 례
2.4 통계적 추론 ····································································································· 53
2.4.1 직접효과의 추론 / 53
2.4.2 간접효과의 추론 / 54
2.4.3 총효과의 추론 / 67
2.5 매개모형 2:경제적 스트레스 연구(가 연속형 변수) ····························· 68
제 3장 다중매개모형
3.1 병렬다중매개모형 ···························································································· 76
3.2 병렬다중매개모형의 예제:미디어영향력 연구 ··········································· 81
3.3 통계적 추론 ····································································································· 89
3.3.1 직접효과의 추론 / 89
3.3.2 특정간접효과의 추론 / 89
3.3.3 특정간접효과들의 대응별 비교 / 91
3.3.4 총간접효과의 추론 / 94
3.3.5 총효과의 추론 / 94
3.4 직렬다중매개모형 ···························································································· 95
3.4.1 직렬다중매개모형의 직접효과와 간접효과 / 98
3.4.2 통계적 추론 / 99
3.4.3 직렬다중매개모형예제(미디어영향력 연구) / 100
3.5 병렬다중매개모형과 직렬다중매개모형이 결합된 모형 ···························· 107
3.6 다중매개모형의 보충내용과 매개변수들 간의 경쟁 ·································· 109
제 4장 매개분석의 기타주제
4.1 Baron and Kenny(1986) 방법은 어떠한가? ··········································· 115
4.2 혼동효과와 인과순서 ···················································································· 123
4.2.1 혼동과 부수현상적 관계의 설명 / 124
4.2.2 인과순서 / 132차 례 7
4.3 효과크기 ········································································································ 134
4.3.1 부분표준화효과 / 136
4.3.2 완전표준화효과 / 137
4.3.3 간접효과의 측정시에 문제가 되는 측정치들 / 139
4.4 복수의  또는 복수의 :개별분석인가 아니면 동시분석인가? ········ 144
4.4.1 가 여러 개인 경우 / 144
4.4.2 가 여러 개인 경우 / 147
제 5장 다항범주형 선행변수가 포함된 매개분석
5.1 상대적 총효과와 직접효과 및 간접효과 ···················································· 151
5.1.1 상대적 간접효과 / 153
5.1.2 상대적 직접효과 / 154
5.1.3 상대적 총효과 / 155
5.1.4 의 효과의 전반적 검정 / 156
5.2 예제:관광목적지 이미지연구 ····································································· 157
5.3 지표코딩방법이 아닌 헬머트 코딩방법의 사용 ········································· 166
5.4 기타주제 ········································································································ 174
5.4.1 매개변수가 두 개 이상인 경우 / 174
5.4.2 코딩방법 선택의 중요성 / 175
제 6장 조절분석의 기초
6.1 조건부효과와 비조건부효과 ········································································· 180
6.1.1 비조건부제약의 철회 / 181
6.1.2 조절작용의 대칭성 / 182
6.1.3 회귀계수의 해석 / 183
6.1.4 조절분석에서 ?의 중요성 / 1858 차 례
6.2 예제:성차별연구 ························································································· 186
6.2.1 PROCESS를 이용한 추정 / 191
6.2.2 회귀계수의 해석 / 194
6.2.3 변수의 척도 및 ?과 ?의 해석 / 195
6.3 조절작용의 그래프 그리기 ·········································································· 198
6.4 상호작용의 탐색 ··························································································· 201
6.4.1 특정값 선택방법 / 202
6.4.2 존슨-네이만 방법 / 206
6.5 조절효과검정과 탐색작업의 차이점 ···························································· 211
6.6 인위적 범주화와 하위집단분석 ··································································· 214
제 7장 조절분석 원리의 확장
7.1 조절변수가 이분형 변수인 경우의 조절분석 ············································· 219
7.2 독립변수와 조절변수가 모두 계량변수인 경우의 조절분석 ····················· 228
7.2.1 회귀계수의 해석 / 234
7.2.2 그래프를 이용한 시각화 / 236
7.2.3 조절효과의 탐색 / 239
7.3 위계적 회귀분석과 동시분석 ······································································· 240
7.4 조절회귀분석과 2×2 factorial ANOVA의 동질성 ··································· 243
7.4.1 단순효과 모수화 / 247
7.4.2 주효과 모수화 / 249
7.4.3 PROCESS를 이용한 2×2 집단 간 factorial ANOVA 분석 / 250
제 8장 조절분석의 기타주제와 조절분석의 추가확장
8.1 평균중심화에 대한 진실과 신화 ································································· 255
8.1.1 평균중심화가 다중공선성과 ?의 표준오차에 미치는 영향 / 258
8.1.2 평균중심화가 ?과 ? 및 이들의 표준오차에 미치는 영향 / 261차 례 9
8.1.3 PROCESS에서의 평균중심화 옵션 / 263
8.2 조절분석에서 표준화회귀계수의 추정과 해석 ··········································· 264
8.2.1 제1표준화방법(Variant 1) / 264
8.2.2 제2표준화방법(Variant 2) / 266
8.2.3 표준화는 조절효과의 탐색을 용이하게 하는가? / 269
8.3 조절변수가 두 개인 경우의 조절분석 ························································ 270
8.3.1 가산다중조절모형 / 270
8.3.2 조절된 조절모형 / 280
8.4 조건부효과들의 비교 ···················································································· 291
8.4.1 가산다중조절모형에서 조건부효과의 비교 / 293
8.4.2 조절된 조절모형에서 조건부효과의 비교 / 294
8.4.3 PROCESS를 이용한 분석 / 295
8.5 조절변수가 모두 계량변수인 경우의 조절된 조절모형 ···························· 296
제 9장 다항범주형 선행변수와 조절변수
9.1 다항범주형 선행변수의 조절효과 ······························································· 305
9.2 예제:관광목적지 이미지연구 ····································································· 310
9.2.1 PROCESS를 이용한 분석 / 312
9.2.2 회귀계수들의 해석 / 315
9.3 그래프 그리기 ······························································································· 317
9.4 상호효과의 탐색작업 ···················································································· 321
9.4.1 특정값 선택방법 / 322
9.4.2 존슨-네이만 방법 / 329
9.5 조절변수가 다항범주형 변수인 경우 ·························································· 332
9.5.1 예제:관광목적지 이미지연구 / 335
9.5.2 상호효과의 탐색과 회귀계수의 해석 / 336
9.5.3 PROCESS를 이용한 분석 / 33810 차 례
제10장 조건부과정분석의 기초
10.1 조건부직접효과와 조건부간접효과 ··························································· 345
10.1.1 직접효과만 조절되는 모형 / 347
10.1.2 간접효과만 조절되는 모형 / 348
10.1.3 직접효과와 간접효과가 모두 조절되는 모형 / 349
10.1.4 병렬다중매개모형에서 특정간접효과가 조절되는 모형 / 350
10.2 예제:역기능행동연구 ················································································ 351
10.3 조건부 간접효과와 직접효과의 수량화 ···················································· 360
10.3.1 의 조건부간접효과 / 361
10.3.2 의 직접효과 / 363
10.4 통계적 추론 ································································································ 363
10.4.1 직접효과의 추론 / 363
10.4.2 간접효과의 추론 / 364
10.4.3 조절된 매개의 탐색 / 367
제11장 조건부과정분석의 추가예제
11.1 예제:성차별연구 ······················································································· 373
11.1.1 단순조절분석 / 374
11.1.2 단순매개분석 / 378
11.2 조건부과정모형에서 직접효과와 간접효과의 조절 ································· 381
11.2.1 PROCESS를 이용한 추정 / 385
11.2.2 직접효과와 간접효과의 수량화 / 388
11.2.3 직접효과와 간접효과의 그래프 / 391
11.3 통계적 추론 ································································································ 394
11.3.1 직접효과의 추론 / 394
11.3.2 간접효과의 추론 / 395
11.3.3 모형의 간소화 / 398차 례 11
11.4 매개된 조절 ································································································ 399
11.4.1 적항()의 간접효과로서의 매개된 조절 / 399
11.4.2 매개된 조절이 관심과 의미가 없는 이유 / 405
제12장 다항범주형 변수가 포함된 조건부과정분석
12.1 예제:관광목적지 이미지연구 ··································································· 410
12.2 의 간접효과 ····························································································· 420
12.2.1 매개과정의 첫 번째 단계 / 420
12.2.2 매개과정의 두 번째 단계 / 425
12.3 상대적 조건부간접효과 ·············································································· 426
12.4 조절된 매개의 검정과 탐색 ······································································ 429
12.4.1 상대적 간접효과의 조절에 관한 검정 / 429
12.4.2 조절된 매개의 탐색 / 431
12.5 상대적 조건부직접효과 ·············································································· 433
12.6 모형의 추가확장과 복잡성 ········································································ 436
제13장 조절변수가 한 개인 다른 조절된 매개모형
13.1 PROCESS model 7 ·················································································· 441
13.1.1 조절된 매개의 탐색 및 비조건부간접효과 / 443
13.1.2 model 7의 예제 / 444
13.1.3 조절된 매개의 탐색 / 448
13.2 PROCESS model 59 ················································································ 449
13.2.1 비선형함수의 조절된 매개검정 / 451
13.2.2 model 59의 예제 / 452
13.3 PROCESS model 15 ················································································ 458
13.3.1 model 15의 예제(주도적 성격연구) / 460
13.3.2 조절된 매개의 검정과 탐색 / 46312 차 례
제14장 조절변수가 두 개인 조절된 매개모형
14.1 PROCESS model 9(부분 조절된 매개) ·················································· 467
14.1.1 model 9의 예제 / 470
14.1.2 부분 조절된 매개의 탐색 / 474
14.2 PROCESS model 16(부분 조절된 매개) ················································ 476
14.2.1 model 16의 예제 / 477
14.2.2 부분 조절된 매개의 탐색 / 481
14.3 PROCESS model 11(조절된 조절된 매개) ············································ 482
14.3.1 조절된 조절된 매개모형의 검정과 탐색 / 485
14.3.2 조절된 조절된 매개의 대칭성 / 486
14.3.3 model 11의 예제 / 487
14.3.4 조절된 조절된 매개효과의 탐색 / 492
14.4 PROCESS model 18(조절된 조절된 매개) ············································ 495
14.4.1 model 18의 예제 / 497
14.4.2 조절된 조절된 매개의 탐색 / 502
14.5 PROCESS model 21(조절된 조절된 매개) ············································ 504
14.5.1 model 21의 예제 / 506
14.5.2 조절된 조절된 매개의 탐색 / 511
14.6 PROCESS model 12(조절된 조절된 매개) ············································ 513
14.6.1 model 12의 예제 / 515
14.6.2 조절된 조절된 매개의 탐색과 조건부직접효과의 탐색 / 519
제15장 다중매개모형이 포함된 조절된 매개모형
15.1 PROCESS model 84 ················································································ 523
15.1.1 model 84의 예제 / 525
15.1.2 조절된 매개지수와 조절된 매개의 탐색 / 531
15.2 PROCESS model 88 ················································································ 533
15.2.1 model 88의 예제 / 535
15.2.2 조절된 매개지수와 조절된 매개의 탐색 / 541차 례 13
15.3 병렬다중매개모형과 조절모형의 결합 ······················································ 543
15.3.1 병렬다중매개모형과 조절모형의 결합 예제 / 545
15.3.2 조절된 매개지수와 조절된 매개의 탐색 / 550
제16장 PROCESS의 사용자정의모형
16.1 매개과정의 행렬표현 ·················································································· 556
16.2 조절효과의 표기법 ····················································································· 561
16.2.1 WMATRIX와 ZMATRIX 표기법 / 562
16.2.2 WZMATRIX 표기법 / 565
16.3 사용자정의를 이용한 공변량의 지정방법 ················································ 570
16.4 숫자모형의 편집 ························································································· 572
16.5 사용자정의모형의 추가예제 ······································································· 582
16.5.1 모형의 수정방법 이용 / 582
16.5.2 모형을 처음부터 구축하는 방법 / 583
부록 ························································································································· 585
참고문헌 ·················································································································· 617
찾아보기 ·················································································································· 631

저자 소개 1

연세대학교 상경대학 응용통계학과(경제학사) 연세대학교 대학원 경영학과(경영학 석사/박사) 현, 세명대학교 글로벌경영학부 교수 [저서] PROCESS macro를 이용한 매개분석?조절분석 및 조절된 매개분석(신영사, 2015) Mplus를 이용한 매개효과와 조절효과 및 조절된 매개효과 분석(신영사, 2018) [주요 논문] 종업원들의 우호성이 심층행동과 직무만족에 미치는 영향: 감성지능과 사회적 지원의 조절된 조절된 매개효과(관광연구) Challenge Stressors, Work Engagement, and Affective Commitment among Chine
연세대학교 상경대학 응용통계학과(경제학사)
연세대학교 대학원 경영학과(경영학 석사/박사)
현, 세명대학교 글로벌경영학부 교수
[저서]
PROCESS macro를 이용한 매개분석?조절분석 및 조절된 매개분석(신영사, 2015)
Mplus를 이용한 매개효과와 조절효과 및 조절된 매개효과 분석(신영사, 2018)
[주요 논문]
종업원들의 우호성이 심층행동과 직무만족에 미치는 영향: 감성지능과 사회적 지원의 조절된 조절된 매개효과(관광연구)
Challenge Stressors, Work Engagement, and Affective Commitment among Chinese Public Servants(Public Personnel Management) 외 다수

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품목정보

발행일
2020년 12월 15일
쪽수, 무게, 크기
638쪽 | 188*257*35mm
ISBN13
9788955017427

출판사 리뷰

복잡한 사회현상을 분석하기 위해 통계분석기법은 꾸준히 진화하고 있습니다. 그 중 매개효과분석과 조절효과분석을 통합한 '조절된 매개분석'(moderated mediation analysis)은 고급통계분석방법으로서 그 앞자리를 차지하고 있습니다.

조절된 매개분석 분야의 세계 최고 권위자는 Andrew F. Hayes 교수로, Ohio 주립대학교의 심리학과에 재직하고 있습니다. Hayes 교수는 ‘매개분석·조절분석 및 조절된 매개분석’을 다룬 저서를 2013년에 출간하였고(필자에 의해 완역 및 해설한 편역서 2015년 신영사 출간), 2018년에는 그 개정판이 나왔습니다. 주요 개정내용으로 △독립변수가 다항범주형 변수인 경우의 매개분석, △독립변수 또는 조절변수가 다항범주형 변수인 경우의 조절분석, △독립변수가 다항범주형 변수인 경우의 조절된 매개분석입니다. 본서는 2018년 원서의 개정 사항을 반영하여 해당 분석내용을 상세하게 설명하였습니다.

본서는 매개분석(제2장부터 제5장)과 조절분석(제6장부터 제9장) 및 조절된 매개분석(제10장부터 제15장)으로 구성되어 있습니다. 여기서 제10장(PROCESS macro model 14)과 제11장(PROCESS macro model 8)은 조절변수가 하나인 비교적 단순한 조절된 매개모형을 소개합니다. 제12장에서는 독립변수가 다항범주형 변수인 경우의 model 8을 설명합니다.

Hayes(2013, 2018)의 저서는 조절된 매개모형인 model 8과 model 14을 다루고 있습니다. 하지만 연구자들이 연구를 진행할 때 이들 두 가지 모형 이외의 다른 연구모형을 분석해야 하는 상황이 생길 수 있습니다. 이러한 다른 모형들은 본서의 제13장부터 제15장에서 설명합니다. 특히 본서의 3원 상호작용(조절된 조절효과)과 매개모형을 결합한 ‘조절된 조절된 매개모형(moderated moderated mediation model)’은 가장 복잡한 조절된 매개모형에 해당합니다. 이러한 ‘조절된 조절된 매개모형’을 분석한 국내 및 해외 연구는 거의 발표되지 않았으며 이는 미개척 분야라고 할 수 있습니다.

이 책에서 사용하는 자료파일은 도서출판 ㈜신영사의 홈페이지(http://www.shinyoungsa.co.kr)나 블로그(https://blog.naver.com/sys28945)에 방문하여 ‘자료실’에 업로드된 자료파일을 내려받아 사용할 수 있습니다. 본서에서 설명하는 내용을 숙지한 후 자료파일을 이용하여 해당 분석을 실행하면 연구에 많은 도움이 될 것입니다.

Hayes 교수는 조절된 매개효과를 분석하기 위한 PROCESS macro를 개발하여 무료로 보급하고 있는데, Hayes 교수의 홈페이지(https://www.afhayes.com)에서 내려받을 수 있습니다. 이 소프트웨어를 PC에 설치하는 방법과 사용법은 본서의 제1장에 상세하게 설명되어 있습니다. PROCESS macro는 계속 업그레이드되기 때문에 수시로 Hayes 교수의 홈페이지를 방문하여 최신 버전을 받는 것이 좋습니다.

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