The analysis of longitudinal binary data can be undertaken using any of the three families of models namely, marginal, random effects and conditional models. Each family of models has its own respective merits and demerits. The models are applied in the analysis of binary longitudinal data for childhood disease data namely the Respiratory Syncytial Virus (RSV) data collected from a study in Kilifi, coastal Kenya. The marginal model was fitted using generalized estimating equations (GEE). The random effects models were fitted using ‘Proc GLIMMIX’ and ‘NLMIXED’ in SAS and then again in Genstat. Because the data is a state transition type of data with the Markovian property the conditional model was used to capture the dependence of the current response to the previous response which is known as the history. The data set has two main complicating issues. Firstly, there is the question of developing a stochastically based probability model for the disease process. In the current work we use direct likelihood and generalized linear modelling (GLM) approaches to estimate important disease parameters. The force of infection and the recovery rate are the key parameters of interest. The findings of the current work are consistent and in agreement with those in White et al. (2003). The aspect of time dependence on the RSV disease is also highlighted in the thesis by fitting monthly piecewise models for both parameters. Secondly, there is the issue of incomplete data in the analysis of longitudinal data. Commonly used methods to analyze incomplete longitudinal data include the well known available case analysis (AC) and last observation carried forward (LOCF). However, these methods rely on strong assumptions such as missing completely at random (MCAR) for AC analysis and unchanging profile after dropout for LOCF analysis. Such assumptions are too strong to generally hold. In recent years, methods of analyzing incomplete longitudinal data have become available with weaker assumptions, such as missing at random (MAR). Thus we make use of multiple imputation via chained equations that require the MAR assumption and maximum likelihood methods that result in the missing data mechanism becoming ignorable as soon as it is MAR. Thus we are faced with the problem of incomplete repeated non–normal data suggesting the use of at least the Generalized Linear Mixed Model (GLMM) to account for natural individual heterogeneity. The comparison of the parameter estimates using the different methods to handle the dropout is strongly emphasized in order to evaluate the advantages of the different methods and approaches. The survival analysis approach was also utilized to model the data due to the presence of multiple events per subject and the time between these events. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermarizburg, 2008.

National cultures play a critical role in effective leadership and organisational success in international businesses. Contemporary organisations are therefore challenged by cross-cultural leadership needs to address increasing diversity. In the past decades, there has been a growing interest in studies of non-Western leadership. Recent papers have focused particularly on leadership in the Asia-Pacific region. This paper compares leadership in China and New Zealand, based on the data collected by using the GLOBE (Global Leadership and Organisational Behaviour Effectiveness) project leadership questionnaire. In addition, the paper reviews the main findings of previous research in order to investigate the similarities and differences in preferred leadership behaviours/characteristics in both cultures, while attempting to examine the consistency of current findings against the previous GLOBE studies. Significant differences of leadership behaviours between China and New Zealand have been identified. This paper generally supports the findings of previous GLOBE studies that charismatic/value-based leadership is the universally contributing factor towards outstanding leadership and self-protective leadership is the universally negative factor against leadership excellence. Findings in this paper may contribute to further understanding of leadership practice in these two countries. Future research should be undertaken to examine the effects of cultural differences on organisational practice by a more comprehensive research method.

Thesis (Ph.D.)--McMaster University (Canada), 1995. / Source: Dissertation Abstracts International, Volume: 56-12, Section: B, page: 6848. Adviser: M. L. Tiku.

Thesis (M.Ed.)--Texas State University-San Marcos, 2007. / Vita. Appendices: leaves 126-137. Includes bibliographical references (leaves 138-145).

Thesis (M.A.)--Carleton University, 2004. / Includes bibliographical references (p. 207-271). Also available in electronic format on the Internet.

Thesis (M.A.)--Carleton University, 2004. / Includes bibliographical references (p. 73-77). Also available in electronic format on the Internet.

Thesis (Ph. D.)--University of Alabama at Birmingham, 2008. / Title from first page of PDF file (viewed Feb. 10, 2009). Includes bibliographical references (p. 71-78).

Thesis (M.S.)--University of Alabama at Birmingham, 2008. / Title from first page of PDF file (viewed Feb. 16, 2009). Includes bibliographical references.

Thesis (M.S.)--University of Alabama at Birmingham, 2008. / Title from first page of PDF file (viewed May 30, 2008). Includes bibliographical references.

Thesis (M.S.)--University of Alabama at Birmingham, 2007. / Title from first page of PDF file (viewed on June 26, 2009). Includes bibliographical references.