Multilevel modeling represents a potentially viable method for meta-analyzing single-subject research, but questions remain concerning its methodological properties with regard to characteristics of single-subject data. For this dissertation, Monte Carlo methods were used to investigate the properties of a 3 level model (i.e., with a quadratic equation at level 1), and three different level 1 error specifications (i.e., different variance components and covariances of 0, lag-1 autoregressive covariance structures, and separate error terms for each phase, with different variance components and covariances of 0). Data for simulated subjects were generated to have characteristics typical of published single-subject data (e.g., typical variances and magnitudes of effect). Samples were simulated for conditions which varied in number of data points per phase, number of subjects per study, number of studies meta-analyzed, level of autocorrelation in residuals, and continuity of variance across phases. Outcome variables examined included rates of convergence of analyses, power for statistical tests of fixed effects, and relative parameter bias of estimates of fixed effects, random effects’ variance components, and autocorrelation estimates. Convergence rates were found to be 100% for all level 1 error specifications and data conditions. Power for statistical tests of fixed effects was observed to be adequate when 10 or more data points were generated per phase and 60 or more total subjects were included in meta-analyses. The relative biases of estimates of fixed effects were found to have limited associations with numbers of data points per phase, levels of autocorrelation, and the continuity/discontinuity of variance across phases. Random effects’ variance components were observed to be frequently biased. Associations between relative bias and data conditions were found to vary by random effect. Finally, autocorrelation estimates were found to be biased in all conditions for which autocorrelation was generated. Results are discussed with regard to study strengths and limitations, and their implications for the meta-analysis of single subject data and primary single subject research. / text

Incorporating the best findings from current, high-quality research into routine clinical practice is the basis of evidence-based care. Chapter 1: "Systematic Review and Meta-Analysis in Evidence-Based Care" is a review of the systematic review process, including meta-analysis, aimed at clinical professionals with limited statistical training. It advocates the use of the systematic review process, outlines some general techniques, and provides selected resources where individuals can acquire additional assistance. The typical steps involved include: formulating a clear research question, defining inclusion and exclusion criteria, extracting the data and assessing the study quality, summarizing and synthesizing the evidence, and then interpreting the findings. When effort is made to minimize bias and locate as many articles on a particular topic as possible, systematic reviews and meta-analyses can produce invaluable findings for evidence-based care. Chapter 2: "The Effect of Macronutrient Distribution on the Lipid Profile in Adults: A Systematic Review and Meta-Analysis" describes a systematic review and meta-analysis that examined the impact total macronutrients had on blood lipid levels. This chapter builds upon the concepts introduced in chapter one, and assesses the effect of manipulating macronutrient distribution on the lipid profile of adults, and compares these effects to recommendations regarding macronutrients, such as the Acceptable Macronutrient Distribution Ranges (AMDRs). Suggestions related to improving the quality of meta-analyses are also outlined, and supplemental analyses are provided at the end of the dissertation.

A variety of psychotherapies have been demonstrated to be efficacious and effective treatments for depression. The cost of psychotherapy, however, and its low availability in some contexts pose significant treatment barriers for many depressed individuals. Based on the idea that peers (i.e., individuals who have successfully recovered from similar problems) may be uniquely able to provide empathy and support to those currently receiving treatment, some community mental health centers have implemented peer treatment models that employ recovered former clients as cost-effective adjunct providers. The effectiveness of these and other peer-administered interventions (PAIs) has not been well-established. The current study is a meta-analysis of the existing outcome research on PAIs for depression. Twenty-six studies were identified as eligible for inclusion and yielded 30 between-groups effect sizes and 29 pre-post PAI effect sizes. Study characteristics and methodological quality were coded and random-effects models were used to calculate and compare mean effect sizes. PAIs produced significant pre-to-post treatment reductions in depression symptoms that were comparable to those found in well-established professionally-administered interventions (.4554). In direct comparisons, PAIs performed as well as professionally-administered treatments (.0848). but not significantly better than treatment-as-usual (e.g., periodic physician check-ins or availability of community mental health services) and wait-list control conditions (.0978). These findings did not change after adjusting for the moderate degree of publication bias in the data. Moderation models revealed that professionally-co-administered PAIs produced significantly worse outcomes than those that were purely peer-administered, and that educational/skills-based PAIs (but not supportive PAIs) produced better outcomes compared with professional treatments. Limitations of this analysis included the heterogeneity of the included interventions and the lack of data on mediators and moderators. Still, these findings suggest that PAIs have promise as effective depression treatments and are worthy of further study.

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Contexte : Les répercussions de l’alcool au niveau des fonctions cognitives sont bien documentées. Certaines hypothèses suggèrent que l’alcool affecte des fonctions cognitives spécifiques alors que d’autres avancent l’hypothèse de déficits diffus. Cependant, une ambigüité persiste concernant quelles fonctions cognitives sont le plus touchées par l’alcool, et à quel point la durée d’abstinence affecte la récupération cognitive. Nous avons procédé à une des premières méta-analyses qui s’intéresse aux différentes fonctions cognitives touchées par la consommation problématique d’alcool et à la durée d’abstinence requise pour une récupération au niveau des cognitions. Méthodes : Une recherche de la littérature a permis d’identifier 62 études évaluant les cognitions chez les personnes présentant des troubles liés à l’utilisation d’alcool. Les estimations de la taille d’effet ont été calculées avec la Comprehensive Meta Analysis –V2 pour les 12 domaines cognitifs suivants : quotient intellectuel, fluidité verbale/langage, vitesse de traitement de l’information, mémoire de travail, attention, résolution de problème/fonctions exécutives, inhibition/impulsivité, apprentissage verbal, mémoire verbale, apprentissage visuel, mémoire visuelle, habiletés visuo-spatiales. Parmi ces 12 domaines cognitifs, 3 estimations de la taille d’effet ont été calculées selon les durées d’abstinences suivantes : court- (<1 mois), moyen- (2 à 12 mois) et long- (>1 an) termes. Résultats : Les résultats ont révélé la présence de dysfonctions modérées dans 11 domaines cognitifs durant l’abstinence à court terme, et dans 10 domaines cognitifs pour le moyen-terme. Des dysfonctions cognitives minimales furent notées durant l’abstinence à long-terme. Conclusions : Ces résultats révèlent des déficits cognitifs significatifs et diffus durant la première année d’abstinence. Déficits qui se normalisent après un an. Ces résultats soutiennent l’hypothèse de déficits cognitifs diffus reliés à l’alcoolisme et suggèrent que la cognition devrait faire partie intégrante du traitement d’alcoolisme. / Background: The cognitive repercussions of alcoholism are well documented. However, the literature remains somewhat ambiguous with which distinct cognitive functions are more susceptible to impairment in alcoholism and to how duration of abstinence affects cognitive recovery. Some theories claim alcohol negatively affects specific cognitive functions while others assert that deficits are more diffuse in nature. We performed the first meta-analysis to examine cognition in alcoholism and how duration of abstinence affects cognitive recovery. Methods: A literature search yielded 62 studies assessing cognitive dysfunction among alcoholics. Effect size estimates were calculated using the Comprehensive Meta-Analysis V2, for the following 12 cognitive domains: intelligence quotient, verbal fluency/language, speed of processing, working memory, attention, problem solving/executive functions, inhibition/impulsivity, verbal learning, verbal memory, visual learning, visual memory, and visuo-spatial abilities. Within these 12 domains, 3 effect size estimates were calculated based on abstinence duration and partitioned into short- (<1 month), intermediate- (2 to 12 months) and long- (>1 year) term abstinence. Results: Findings revealed moderate impairment across 11 cognitive domains during short term abstinence with moderate impairment across 10 domains during intermediate term abstinence, and overall small effect size estimates during long term abstinence. Conclusions: Results suggest significant cognitive dysfunction during the first year following abstinence from alcohol and that long term abstinence yields near normalisation of cognitive function. These findings support the diffuse brain deficits hypothesis. Clinical implications suggest that cognition may need to be considered an integral part of the treatment of alcoholism.

Genetic improvement of indigenous pig populations in tropical developing countries can make a significant contribution to the conservation and utilization of local genetic resources. Designing a swine breeding program requires knowledge of genetic parameters for economically important traits. A meta-analysis of genetic parameters determined under tropical conditions and published from 1974 to 2009 was carried out to provide consensus estimates of genetic parameters. Given that the data recording and analysis infrastructure for implementing the conventional best linear unbiased prediction (BLUP) methods is generally lacking in developing countries, Genome-wide selection (GS) provides an approach for achieving faster genetic progress without developing a pedigree recording system. A simulation study was carried out to evaluate the option of using available 60 K single nucleotide polymorphism marker panel. The observed levels of linkage disequilibrium (LD) in the tropical pig populations were simulated and utilized. Genomic predictions were from ridge regression analysis. The results showed that expected accuracies of genomic breeding values (GBV) were in the range of 0.31 - 0.86 for the validation set. Genome-wide selection improved accuracy of GBVs over conventional BLUP method for traits with low heritability and in young animals with no performance data. Crossbred training populations had higher accuracy than purebred training populations. An assessment of the opportunities for GS in tropical pig breeding was conducted. Genome-wide selection performed better than conventional methods by increasing genetic gain and maintaining genetic variation while lowering inbreeding especially for traits with low heritability, by exploiting LD and the Mendelian sampling effects. Combining GS with repeated backcrossing of crossbreds to the selected exotic population in moderate LD promises faster improvements of the commercial population. A two-step selection strategy that involves the use of GS to pre-select candidates that entered the performance test station and for selecting replacement candidates in a nucleus swine breeding program was evaluated and compared to other conventional approaches. Genome-wide selection generated an increase of about 38% to 172% in annual returns compared to other conventional approaches for previously selected population in moderate LD and about 2% to 50% increases in return for unselected population in low LD. / Canadian Commonwealth Scholarship and Fellowship Program, University of Guelph

Outlets for students to develop mathematical ideas and skills to solve real-life problems and applicable situations have been neglected in secondary classrooms (Gainsburg, 2008). Designing curricula that applies real-life situations has been promoted by the National Council of Teachers of Mathematics (2000), the National Research Council (1998), and the Commission on Behavioral and Social Sciences and Education (2000) and also is an expectation of state standards for student learning (Texas Education Agency, 2009). Contrary, evidence has shown low benefits to classroom real-life examples perceived by students. This study served dual purposes: 1) Determine the relationship between place-based education and mathematics learning, and 2) Investigate teacher conceptions of place-based education opportunities in high school, mathematics curriculum. This study employed two methodologies. A mixed-methods approach was employed for the meta-analysis of place-based programs and the second employed qualitative methods of structured interviewing to determine teachers’ conceptions of place-based pedagogy. Upon completion of the study, I concluded: 1) Place-based pedagogies align toward more foundational mathematic skills (e.g. measurement, number sense) when implemented, and 2) Teachers’ conceive place-based as a general effective tool for student engagement and real-world context of how mathematics functions in society.

After almost two decades of research on direct repression by p53, I provide evidence that the transcription factor p53 solely acts as an activator of transcription. I evaluate the prominent models of transcriptional regulation by p53 based on a computational meta-analysis of genome-wide data. With this tool at hand, the major contradiction how p53 binding can result in activation of one target gene and repression of another is resolved. In contrast to most current models, solely genes activated by p53 are found to be enriched for p53 binding. Meta-analysis of large-scale data is unable to confirm reports on directly repressed p53 target genes and does not support models of direct repression. Consequently, as supported by experimental data, p53 is not a direct repressor of transcription, but solely activates its target genes. Moreover, models based on interference of p53 with activating transcription factors are also not supported by the meta-analysis. As an alternative to these models, the meta-analysis leads to the conclusion that p53 represses transcription indirectly by activation of the p53-p21- DREAM/RB pathway. Thus, results of the meta-analysis support only two models, namely activation by direct binding of p53 to target genes and repression through activating the p53-p21-DREAM/RB pathway.

Differential item functioning (DIF) occurs when individuals from different groups who have equal levels of a latent trait fail to earn commensurate scores on a testing instrument. Type I error occurs when DIF-detection methods result in unbiased items being excluded from the test while a Type II error occurs when biased items remain on the test after DIF-detection methods have been employed. Both errors create potential issues of injustice amongst examinees and can result in costly and protracted legal action. The purpose of this research was to evaluate two methods for detecting DIF: logistic regression (LR) and Mantel-Haenszel (MH). To accomplish this, meta-analysis was employed to summarize Monte Carlo quantitative studies that used these methods in published and unpublished literature. The criteria employed for comparing these two methods were Type I error rates, the Type I error proportion, which was also the Type I error effect size measure, deviation scores, and power rates. Monte Carlo simulation studies meeting inclusion criteria, with typically 15 Type I error effect sizes per study, were compared to assess how the LR and MH statistical methods function to detect DIF. Studied variables included DIF magnitude, nature of DIF (uniform or non-uniform), number of DIF items, and test length. I found that MH was better at Type I error control while LR was better at controlling Type II error. This study also provides a valuable summary of existing DIF methods and a summary of the types of variables that have been manipulated in DIF simulation studies with LR and MH. Consequently, this meta-analysis can serve as a resource for practitioners to help them choose between LR and MH for DIF detection with regard to Type I and Type II error control, and can provide insight for parameter selection in the design of future Monte Carlo DIF studies.

Background: Cancer and diabetes are the second and twelfth leading global causes of death, respectively. Cancer incidence is increased in diabetics compared to non-diabetics. Common pathobiological pathways are shared by the two diseases: hyperglycaemia, hyperinsulinaemia, chronic inflammation and altered concentrations of endogenous hormones. These pathways can all directly or indirectly be linked to chronic hyperglycaemia. Lifestyle factors also affect cancer, diabetes and hyperglycaemia. Hypothesis: Chronic hyperglycaemia is the common biological pathway linking cancer, diabetes and lifestyle factors. Chronic hyperglycaemia can be assessed by monitoring glycated haemoglobin (HbA1c) levels. Aim: The first aim is to investigate whether the link between diabetes and increased cancer risk can be explained by increasing HbA1c levels. Secondly, glycaemic and overall models of lifestyle factors should be developed and compared to determine the relative influence of lifestyle factors on blood glucose level and, subsequently, cancer risk. This could clarify whether improved glycaemic control via lifestyle factors is sufficient to significantly reduce cancer risk. Method: Dose-response meta-analyses on cancer risk and HbA1c levels were performed and the results communicated via a research article. Statistical glycaemic and overall models were developed from published studies on colorectal cancer (CRC), lifestyle factors and HbA1c, via meta-analysis. Log-linear and restricted cubic spline models were considered for studies relating CRC risk to lifestyle factors or HbA1c. Linear models were considered for studies relating HbA1c to lifestyle factors. Only statistically significant models were compared. Results: Increased cancer risk with increasing HbA1c levels was present for a number of cancers, with some cancer types also showing increased risk in the pre-diabetic and normal HbA1c ranges. Comparison of the glycaemic and overall models revealed that HbA1c significantly affected cancer risk and was significantly affected by lifestyle factors. However, the overall effects of lifestyle factors were much stronger than their glycaemic effects (between 9% and 25% difference in risk between overall effects and glycaemic effects at the exposure levels analysed). Glycaemic and overall models for cigarette smoking and chronic stress revealed increased cancer risk with increasing exposure, but decreased cancer risk for increased dietary fibre intake. The glycaemic model for alcohol consumption displayed decreased cancer risk, while the overall model revealed increased cancer risk, emphasising the strong effect of carcinogenic substances in alcohol. Conclusions: Risk for a number of cancers increased with HbA1c levels in diabetic and non-diabetic persons. Cancer prevention by improved blood glucose control seems plausible. The overall effects of lifestyle factors on cancer risk are much stronger than their glycaemic effects. Lifestyle factors alone do not provide enough reduction in blood glucose levels. Other therapeutic strategies for reducing blood glucose levels, such as pharmacotherapeutics or fasting, should be investigated. The possible harmful effects of reducing blood glucose levels, such as neuroglycopaenia, should be considered before implementation of therapeutic strategies. Although there seems to be a strong association between HbA1c and cancer risk, this does not imply causality. The possibility of residual confounding cannot be ignored, even though the most adjusted estimates were used to develop the models, where possible. / MIng (Electrical and Electronic Engineering), North-West University, Potchefstroom Campus, 2014