구조방정식 모형 연구의 실전 > 교육통계.교육측정

이 책은 구조방정식 모형을 활용하여 연구를 시작하려는 이들을 위해, 저자들이 그동안 읽어온 많은 자료들 중 꼭 필요하고 중요한 내용들을 중심으로 연구자의 관점에서 종합하여 정리한 것이다. 우리는 내용 연구자로서 연구방법론이나 통계학을 익히고, 적용하여 우리의 학문 분야를 발전시키기 위해 구조방정식 모형을 사용해왔다. 하지만 각자의 구조방정식 모형 연구의 경력은 동일하지 않으며 서로 간에 차이가 있다. 이러한 차이 덕분에 우리는 통계적 개념을 학습하며 겪는 어려움을 공감하고, 질문하고, 답변하는 과정을 거치며 최대한 쉽게 이 책을 집필하는 특별하고, 멋진 경험을 하였다. 저자들은 연구방법론 연구자와 내용 연구자 사이에서 가교 역할을 할 수 있는 세련된 내용 연구자로서 실제 연구에 도움이 되는 내용들을 최대한 효과적으로 전달하고자 하였다. 

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제1장 모형지정 ························································································11

1.1 구조방정식의 기본 개념 ·····································································12

1.2 모형의 유형 ·······················································································26

1.3 모형지정 ····························································································43

제2장 재미있는 기초 통계 ········································································53

2.1 변량, 공변량, 피어슨 적률상관계수, 회귀계수 ····································55

2.2 공변량 특성 ·······················································································68

2.3 피어슨 적률 상관계수, 편상관계수, 부분상관계수 ······························76

2.4 상관계수에 영향을 미치는 요인 ··························································87

2.5 상관과 인과의 차이 ············································································90

2.6 기타 상관계수의 유형 ·········································································91

제3장 즐거운 연구의 기초 개념 ·································································93

3.1 모집단과 표본 ·····················································································94

3.2 측정의 척도 ·······················································································106

3.3 측정의 신뢰도와 타당도 ·····································································112

제4장 모형식별 ························································································137

4.1 모형식별 ····························································································138

4.2 모수들의 유형과 표기 ·········································································142

4.3 자유 모수와 고정 모수 ········································································150

4.4 잠재변인의 측정 단위 ·········································································152

4.5 연구모형을 리즈렐식 모형으로 표기해 보기 ········································154

4.6 모형식별의 지침 ·················································································159

제5장 자료의 점검과 준비 ·········································································187

5.1 자료 입력의 정확성 ·············································································188

5.2 결측 자료 ····························································································189

5.3 극단값(outliers) ·················································································205

5.4 정상성(normality), 선형성(linearity), 동분산성(Homoscedacity) ···214

5.5 모형 분석을 위한 자료의 준비 ·····························································226

제6장 모형 추정 ························································································237

6.1 모형 추정의 기본 원리 ········································································238

6.2 표본 변량-공변량 행렬(S)을 사용한 모형 추정 ····································244

6.3 표본 변량-공변량 행렬(S)을 사용한 과잉식별 모형 추정 ·····················255

6.4 모형 합치 함수 ····················································································259

제7장 모형 평가 ························································································261

7.1 모형  통계 ···················································································263

7.2 상대적 적합도 지수(CFI ) ···································································264

7.3 RMSEA ······························································································267

7.4 Tucker Lewis index(TLI ) 또는 non-normed fit index(NNFI ) ······268

7.5 모형 비교 ···························································································269

제8장 jamovi와 친해지기 ········································································271

8.1 jamovi 소개와 설치 ···········································································271

8.2 jamovi 프로그램 기초 ·······································································274

8.3 분석자료 입력 및 편집 ·······································································288

8.4 자료 입력하기 ····················································································292

8.5 jamovi에서 엑셀파일 불러오기 ·························································294

8.6 저장 및 출력하기 ···············································································294

8.7 자료 처리의 실제 ···············································································296

8.8 자료 연산하기 ····················································································301

8.9 자료 변환하기 ····················································································312

8.10 결측치가 있는 경우 합산 ··································································316

8.11 jamovi library를 활용한 모듈 설치 ·················································319

제9장 중다회귀분석과 결과 기술 ······························································327

9.1 통계 프로그램 활용하기 ·····································································327

9.2 통계 결과 작성하기 ············································································335

9.3 통계 결과 해석하기 ············································································339

9.4 학술연구 원고작성의 예 ·····································································343

제10장 중다매개모형의 분석과 결과 기술 ················································347

10.1 통계 프로그램 활용하기 ···································································348

10.2 통계 결과 작성하기 ··········································································373

10.3 통계 결과 해석하기 ··········································································376

10.4 학술연구 원고작성의 예 ···································································381

제11장 측정모형의 분석과 결과 기술 ·······················································387

11.1 분석 절차 ·························································································388

11.2 확인적 요인분석을 활용한 측정모형 검증 ·········································414

11.3 학술연구 원고작성의 예 ···································································420

제12장 구조모형의 분석과 결과 기술 ·······················································425

12.1 SEM 모듈 설치와 SEM 분석 ····························································426

12.2 구조모형의 통계결과 작성 및 해석하기 ············································466

12.3 학술연구 원고작성의 예 ···································································473

참고문헌 ··································································································475

찾아보기 ··································································································481

저자소개

최희철(HeeCheol Choi)

대구교육대학교를 졸업하고, 단국대학교 대학원 교육학과에서 상담심리전공으로 석사학위와 박사학위를 취득하였다. 현재 광주여자대학교 상담심리학과 교수로 재직 중이다. 평소 구조방정식 모형을 활용하여 상담심리학 관련 횡단연구 및 종단연구 결과를 다양한 학회지에 출판하고 있다. 상담이론, 심리통계, 연구방법론을 지속해서 학부와 대학원에서 강의해 왔다. 

김영미(YoungMi Kim)

대구효성가톨릭대학교를 졸업하고, 부산대학교 대학원 특수교육학과에서 특수교육을 전공으로 석사학위와 박사학위를 취득하였다. 현재 광주여자대학교 초등특수교육과 교수로 재직 중이다. 구조방정식 모형을 활용하여 장애인 관련 연구 결과를 다양한 학회지에 출판하고 있다. 

이우진(WooJin Lee)

초당대학교를 졸업하고, 대구대학교 일반대학원 언어치료학과에서 석사학위와 조선대학교 특수교육학과 언어·청각전공으로 박사학위를 취득하였다. 현재 광주여자대학교 언어치료학과 교수로 재직 중이다. 구조방정식 모형을 활용하여 연구 결과를 다양한 학회지에 출판하고 있다. 

강혜진(HyeJin Kang)

부산대학교 대학원 특수교육학과에서 특수교육을 전공으로 석사학위와 박사학위를 취득하였다. 현재 광주여자대학교 중등특수교육과 교수로 재직 중이다. 구조방정식 모형을 활용하여 특수교사와 장애인 관련 연구 결과를 다양한 학회지에 출판하고 있다. 특수교육 관련 이론과 실제, 특수교육대상자 진단 및 평가 등의 교과목을 학부와 대학원에서 강의해 왔다. 

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