AbstractThis study aims at analyzing the relationship between team characteristic and innovation performance. The mediating effect of creative climate on the team characteristic and innovation performance is also measured. Based upon literature review, individual creative characteristics, team diversity, team cohesion, task characteristics are presented as antecedents of team characteristic. Creative climate affects the creative behavior and innovative performance. Creative climate is measured as the Team Climate Inventory (TCI) proposed by Anderson & West (1998) including goal, participative-autonomy and innovative-support. Data were collected from 186 survey responses (54 Teams) out of total 462 (69 teams) from the R&D department of a major ICT firm in Korea. Empirical results show the diversity, cohesion, job characteristic, individual creative characteristic have a positive effect on the creative climate and innovation performance. The participative-autonomy climate factor appears to mediate the relationship between team characteristic (diversity, cohesion, job and individual characteristics) and innovation performance. However, the mediating effects of goals and innovative-support factors were not significant statistically. It was confirmed that the organization can contribute to improve the team innovation performance by facilitating a autonomy and participative climate as well as fostering the team characteristic. 1충북대학교 2질병관리본부 3충북대학교 4질병관리본부 5충북대학교 본 연구에서는 질병관리본부에서 매년 조사하고 있는 지역사회 건강 조사자료를 이용하여 충청북도 지역을 대상으로 국민의 삶의 질에 미치는 영향을 다수준 분석의 절차와 방법을 이용하여 분석하였다. 종속 변수인 삶의 질에 영향을 미치는 변수로는 주관적 건강상태, 구강건강, 스트레스를 이용하였으며 지역사회 건강조사자료의 다수준 분석의 활용성을 확인하고 적합한 분석의 수준을 결정하기
위해 다수준 분석에서 많이 사용되고 있는 집단내 일치도 지수(r_wg), 급내상관계수(ICC(1)과 ICC(2)), WABA(within and between analysis) 등을 평가 측도로 사용하였다. 분석의 수준을 결정하기 위해 평가 측도를 사용한 결과 다수준 모형보다는 단일수준 모형이 적합함을 보였으며 다수준 분석 결과 또한 집단 수준의 영향력이 통계적으로 유의하지 않아 분석 수준 결정에 사용된 평가 측도가 적절함을 알 수 있었다. In this study, we propose the procedure and methods of multilevel analysis using the Community Health Survey data from Korea Centers for Disease Control and Prevention and analyze the effect of various health status on the quality
of life. The variables that affect the quality of life as the dependent variable are subjective health status, oral health and stress. In order to determine the appropriate level of analysis, r_wg (within group agreement), ICC(1), ICC(2), WABA (within and between analysis) etc. widely used in multilevel analysis was used as the evaluation measure. As a result of using evaluation measures to determine the level of analysis, single level model is more appropriate than multilevel model. Also, the
result of multilevel analysis is that the influence of group level are not statistically significant. Therefore, we conclude that the evaluation measure used to determine the level of analysis is appropriate. 키워드열기/닫기 버튼, , , multilevel analysis, the Community Health Survey, WABA, multilevel model. 피인용 횟수
인용현황.x �ټ��غм��� ������ ���: WABA�� �߽����� �� �� ��** �� �� ��** �� ������ �ټ��غм�(multilevel analysis) �������� �ֱٿ� ���� ���ǰ� �ִ� WABA(within and between analysis)�� ����� ��ü���� �м������ �Ұ��ϴ� ���� �� ������ �ִ�. �ټ��غм� ������� �� �м����� �� (x) �ջ�ô���� Ÿ�缺 ����(������ �ڷ�κ����� ����)�� (x) �ټ��ؿ��������� ���ռ� (model fit) ����� ũ�� ������ �� �� �ִ�. ���ڿ� ���ϴ� ����� �м�������δ� rwg`` �� x`` ICC(x)`` ICC(x)`` WABA�� �ַ� ���°�`` ���� ... �����ڷ� ���� �� �̿�ȳ� ��ó : http://s-space.snu.ac.kr/bitstream/10371/36885/1/03%eb%b0%95%ec%9b%90%ec%9a%b0_%ec%82%bc.pdf
������ �Ű��ּ���. ����ı� ��� : �ſ� ��õ ��Ÿ���� �������� �������� ��� : �ִ� 10,000�� ����(�̺�Ʈ �Ⱓ �ִ� 20,000��) 학술논문다수준분석의 절차와 방법 : WABA를 중심으로저자박원우, 고수경학술지정보
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다수준 분석의 절차와 방법 waba를 중심으로
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