Detecting a change in the structure of a time series is a classical statistical problem. Here we consider a short memory causal linear process $X_i=\sum_{j=0}^\infty a_j\xi_{i-j}$, $i=1,\cdots,n$, where the innovations $\xi_i$ are independent and identically distributed and the coefficients $a_j$ are summable. The goal is to detect the existence of an unobserved time at which there is a change in the marginal distribution of the $X_i$'s. Our model allows us to simultaneously detect changes in the coefficients and changes in location and/or scale of the innovations. Under very simple moment and summability conditions, we investigate the asymptotic behaviour of the sequential empirical process based on the $X_i$'s both with and without a change-point, and show that two proposed test statistics are consistent. In order to find appropriate critical values for the test statistics, we then prove the validity of the moving block bootstrap for the sequential empirical process under both the hypothesis and the alternative, again under simple conditions. Finally, the performance of the proposed test statistics is demonstrated through Monte Carlo simulations.

Change is an organizational inevitability. There are few fields that undergo change more rapidly than information technology. Keeping up with the pace of change in a field so inclined toward change may take a unique toll on workers in information technology. Yet, little has been done to investigate workers' orientations towards change in this turbulent field. Accordingly, this research explores attitudes toward change and some possible related characteristics among individuals who work in the field of information technology. The primary purpose of this study is to explore the nature of resistance to change in information technology. The secondary purpose of this study was to discover potential relationships between resistance to change and several well known motivational variables; specifically empowerment, engagement, and workaholism. Trust was included in this model as well because it has been shown to relate to both motivation and resistance to change and because trust is generally understood to be a characteristic that eases interaction and reduces transaction costs. This study used a web-based survey to collect responses from individuals employed in two medium-sized information technology organizations. Responses were analyzed using correlational, regression, path, and factor analyses to analyze participants' responses. Results indicated that resistance to change is a factor in information technology. Also, two of three motivational characteristics related negatively to resistance to change. Trust related negatively to resistance to change and positively to the same two motivational characteristics, but did not mediate the relationship between these variables. These findings are discussed in terms of their relevance to the study of information technology as they suggest possible implications for organizational functioning, individual well-being, technology adoption, and coping, and innovation.

Magister Artium (Psychology) - MA(Psych) / While research into children’s subjective well-being (SWB) has advanced over the past decade, there is a paucity of cross-cultural research, particularly in South Africa. Moreover, while the adaptation and validation of instruments in English and Afrikaans are evident, other language groups have not received much attention. This study aimed to provide structural validation of the Students’ Life Satisfaction Scale across a sample of children in South Africa using multi-group analysis across three language groups (Setswana, Xitsonga, and Tshivenda). Within this process, the study aimed to use multi-group confirmatory factor analysis (MGCFA) to compare the structural validity and measurement invariance of the three language groups. Finally, the study aimed to determine the convergent validity of the three language groups of the SLSS by regressing them onto the single-item Overall Life Satisfaction Scale (OLS). The study uses data from Wave 3 of the South African Children’s Worlds Study and included a sample of 625 children across the language groups (Setswana: n = 187; Sesotho: n = 170; and Tshivenda: n = 268). For the overall pooled sample an excellent fit was obtained for a single-factor model, including one error-covariance. Standardised regression weights of the items ranged between .43 and .73. MGCFA revealed an acceptable fit for the configural model (unconstrained loadings); however, metric (constrained loadings) and scalar invariance (constrained loadings and intercepts) was not tenable. However, through the application of partial constraints metric invariance was tenable when Item 5 (I like my life) was freely estimated, while scalar invariance was tenable when Item 1 (I enjoy my life) and Item 5 (I like my life) were freely estimated. The results suggest that the Items: My life is going well; I have a good life; The things in my life are excellent; and I am happy with my life, are comparable by correlations, regression coefficients, and latent mean scores across the three language groups. Convergent validity using the OLS was obtained for the pooled sample and across the language groups. The key contribution of the study is establishing that the Setswana, Sesotho, and Tshivenda translated and adapted versions of the SLSS are valid for use within the South African context to measure children’s SWB, and that they can be grouped together in an overall pooled sample.

Integration in the European Union (EU) in terms of the legal as well as economic spheres has grown in depth, scope and speed since its establishment. The EU has significantly affected various fields of policies within its member states, including the environment. This is understood as the 'Europeanisation process'. The Netherlands, considered one of the pioneering countries to establish environmental measures, has approximately 80% of its legislation in the environmental field derived from European legislation. The thesis seeks to answer how Dutch environmental policy has been affected by the EU over the past twenty years. The implementation process of three environmental directives is analysed concerning water, biodiversity and air, to understand this process. The concept of Europeanisation and the related theory of goodness of fit is applied to argue that the implementation process of European environmental directives in the Netherlands is effective if there are no major adjustments necessary in the national setting, i.e. there is no policy or institutional misfit between domestic and European legislation, and no veto players impede the process. On the other hand, the implementation process is significantly more complicated if the directive needs extensive transformations. It is concluded that...

In many hypothesis testing problems such as one-sample and two-sample test problems, the test statistics are degenerate U-statistics. One of the challenges in practice is the computation of U-statistics for a large sample size. Besides, for degenerate U-statistics, the limiting distribution is a mixture of weighted chi-squares, involving the eigenvalues of the kernel of the U-statistics. As a result, it’s not straightforward to construct the rejection region based on this asymptotic distribution. In this research, we aim to reduce the computation complexity of degenerate U-statistics and propose an easy-to-calibrate test statistic by using the divide-and-conquer method. Specifically, we randomly partition the full n data points into kn even disjoint groups, and compute U-statistics on each group and combine them by averaging to get a statistic Tn. We proved that the statistic Tn has the standard normal distribution as the limiting distribution. In this way, the running time is reduced from O(n^m) to O( n^m/km_n), where m is the order of the one sample U-statistics. Besides, for a given significance level , it’s easy to construct the rejection region. We apply our method to the goodness of fit test and two-sample test. The simulation and real data analysis show that the proposed test can achieve high power and fast running time for both one and two-sample tests.

This dissertation compares the parameter estimates obtained from two item response theory (IRT) models: the 1-PL IRT model and the MC1-PL IRT model. Several scenarios were explored in which both unidimensional and multidimensional item-level and personal-level data were used to generate the item responses. The Monte Carlo simulations mirrored the real-life application of the two correlated dimensions of Necessary Operations and Calculations in the basic mathematics domain. In all scenarios, the MC1-PL IRT model showed greater precision in the recovery of the true underlying item difficulty values and person theta values along each primary dimension as well as along a second general order factor. The fit statistics that are generally applied to the 1-PL IRT model were not sensitive to the multidimensional item-level structure, reinforcing the requisite assumption of unidimensionality when applying the 1-PL IRT model.

Fit indices and fit measures commonly used to determine the accuracy and desirability of structural equation models are expected to be insensitive to nonlinearity in the data. This includes measures as ubiquitous as the CFI, TLI, RMSEA, SRMR, AIC, and BIC. Despite this, some software will report these measures when certain models are used. Consequently, some researchers may be led to use these fit measures without realizing the impropriety of the act. Alternative fit measures have been proposed, but these measures require further testing. As part of this thesis, a large simulation study was carried out to investigate alternative fit measures and to confirm whether the traditional measures are practically blind to nonlinearity in the data. The results of the simulation provide conclusive evidence that fit statistics and fit indices based on the chi-square distribution or the residual covariance matrix are entirely insensitive to nonlinearity. The posterior predictive p-value was also insensitive to nonlinearity. Only fit measures based on the structural residuals (i.e., HFI and R-squared) showed any sensitivity to nonlinearity. Of these, the R-squared was the only reliable measure of nonlinear model misspecification. This thesis shows that an effective strategy for determining whether a nonlinear model is preferable to a linear one involves using the R-squared to compare models that have been fit to the same data. An R-squared that is much larger for the nonlinear model than the linear model suggests that the linear model may be less desirable than the nonlinear model. The proposed method is intended to be supplementary to substantive theory. It is argued that any dependence on fit indices or fit statistics that places these measures on a higher pedestal than substantive theory will invariably lead to blindness on the part of the researcher. In other words, unwavering adherence to goodness-of-fit measures limits the researchers vision to what the measures themselves can detect.

<p> The Kolmogorov-Smirnov tests of homogeneity or goodness-of-fit and the binomial group tests for eliminating defectives are of different nature. But they are both popular in applications. The former are widely used in nonparametric comparison, while the later are usually adopted in the group screening problems. When the experimenter has k populations, k-sample statistics should be considered for the testing of homogeneity or goodness-of-fit. On the other hand, when there are k experimenters available for performing group testing on a given population, a k-sample group testing procedure should be used.</p> <p> In this thesis, the distribution functions of k-sample analogues of the Kolmogorov-Smirnov statistics have been found under certain conditions and a k-sample group testing procedure has been defined. This procedure has also been shown to be optimal in the sense that it requires a minimum expected number of k-sample group tests for finding a single defective from a binomial population.</p> <p> Our methods are mainly combinatorial: matrix enumeration, tree counting and construction algorithms are explored as a foundation of our study.</p> / Thesis / Doctor of Philosophy (PhD)

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