This two-article dissertation summarizes the end-of-course survey and formative feedback literatures, as well as proposes actionability as a useful construct in the analysis of feedback from students captured in real-time during their courses. The present inquiry grew out of my work as the founder of DropThought Education, a Division of DropThought. DropThought Education was a student feedback system that helped instructional designers, instructors, and educational systems to use feedback from students to improve learning and student experience. To find out whether the DropThought style of feedback was more effective than other forms of capturing and analyzing student feedback, I needed to (1) examine the formative feedback literature and (2) test DropThought style feedback against traditional feedback forms. The method and theory proposed demonstrates that feedback from students can be specific and actionable when captured in the moment at students' activity level, in their own words. Application of the real-time feedback approach are relevant to practitioners and researchers alike, whether an instructor looking to improve her class activities, or a learning scientist carrying out interventionist, design-based research.

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

This thesis develops and evaluates statistical methods for different types of genetic analyses, including quantitative trait loci (QTL) analysis, genome-wide association study (GWAS), and genomic evaluation. The main contribution of the thesis is to provide novel insights in modeling genetic variance, especially via random effects models. In variance component QTL analysis, a full likelihood model accounting for uncertainty in the identity-by-descent (IBD) matrix was developed. It was found to be able to correctly adjust the bias in genetic variance component estimation and gain power in QTL mapping in terms of precision.  Double hierarchical generalized linear models, and a non-iterative simplified version, were implemented and applied to fit data of an entire genome. These whole genome models were shown to have good performance in both QTL mapping and genomic prediction. A re-analysis of a publicly available GWAS data set identified significant loci in Arabidopsis that control phenotypic variance instead of mean, which validated the idea of variance-controlling genes.  The works in the thesis are accompanied by R packages available online, including a general statistical tool for fitting random effects models (hglm), an efficient generalized ridge regression for high-dimensional data (bigRR), a double-layer mixed model for genomic data analysis (iQTL), a stochastic IBD matrix calculator (MCIBD), a computational interface for QTL mapping (qtl.outbred), and a GWAS analysis tool for mapping variance-controlling loci (vGWAS).

Submitted by ANGEL DE JESUS LAZARO VELASCO null (angelstrauss26@hotmail.com) on 2017-10-25T17:49:03Z No. of bitstreams: 1 DissertacaoAngel.pdf: 1392488 bytes, checksum: 30d16b1c40935e0572a92a6d9c6dc400 (MD5) / Approved for entry into archive by Monique Sasaki (sayumi_sasaki@hotmail.com) on 2017-10-31T17:00:42Z (GMT) No. of bitstreams: 1 velasco_ajl_me_jabo.pdf: 1392488 bytes, checksum: 30d16b1c40935e0572a92a6d9c6dc400 (MD5) / Made available in DSpace on 2017-10-31T17:00:42Z (GMT). No. of bitstreams: 1 velasco_ajl_me_jabo.pdf: 1392488 bytes, checksum: 30d16b1c40935e0572a92a6d9c6dc400 (MD5) Previous issue date: 2017-09-26 / Consejo Nacional de Ciencia y Tecnología (CONACYT) / Há evidências na literatura que a uniformidade das características fenotípicas dos peixes, entre outros animais, pode ser afetada por componentes genéticos, além de fatores ambientais. Maior uniformidade na despesca é desejada, a fim de reduzir a competição entre os animais e, assim, ter uma produção mais homogênea, visando maior retorno financeiro da atividade. O objetivo deste estudo foi estimar se as variâncias residuais do peso e comprimento à despesca de tilápias do Nilo (Oreochromis niloticus) são afetadas por componentes genéticos, para avaliar a possibilidade de seleção para uniformidade de produção. Empregou-se o modelo hierárquico linear generalizado duplo (DHGLM) para calcular os componentes de variância, os parâmetros de herdabilidade, coeficientes de variação e correlações genéticas para peso (não transformado e com transformação Box-Cox) e comprimento à despesca. Foi utilizado um total de 8.725 informações fenotípicas de tilápias provenientes de 271 famílias da linhagem GIFT (Malásia), criados na estação experimental de piscicultura da Universidade Estadual de Maringá. Os resultados apoiaram a hipótese de heterogeneidade genética da variância residual para peso e comprimento à despesca, e a oportunidade de seleção medida através do coeficiente genético de variação da variância residual. Além disso, observou-se a necessidade de um grande número de filhos para a obtenção de estimativas precisas do mérito genético para variação residual, conforme indicado pelas estimativas de baixa herdabilidade. A transformação de Box-Cox foi capaz de diminuir a dependência entre a variância e a média do peso à despesca. A transformação reduziu, mas não eliminou toda a heterogeneidade genética da variância residual, destacando sua presença além do efeito da escala. / There is evidence in the literature that the uniformity of phenotypic traits of fish, among other animals, can be affected by genetic components, as well as environmental factors. Greater uniformity is desired in order to reduce competition among animals and thus have a more uniform production, aiming a greater financial return of the activity. The objective of this study was to assess if the residual variance of the weight and harvest length of the Nile tilapia (Oreochromis niloticus) is affected by a genetic component, to evaluate the possibility of selection for uniformity of production. The double hierarchical generalized linear model was used to estimate the components of variance, heritability, coefficients of variation and genetic correlation for weight (untransformed and with Box-Cox transformation) and harvest length. Phenotypic records of 8,725 individuals from 271 families were analyzed. The results supported the existence of genetic heterogeneity of residual variance on harvest weight and length, and the opportunity to select for increasing uniformity. Moreover, the low heritability estimates showed the necessity of high number of progeny for an accurate estimate of the genetic merit for the residual variance. The Box-Cox transformation of harvest weight reduced the dependency among its mean and variance. The transformation reduced but did not eliminate the genetic heterogeneity of residual variance, highlighting its presence beyond the scale effect. / CONACYT: 579742/410471

<p>Postpartum depression has become a major public health concern for women within a specific time period after delivery. Depression is possibly associated with some risk factors such as socioeconomic status, social support, maternal mental and physical health, and history of anxiety. TOMIS III, funded by the Canadian Institutes of Health Research, is a prospective cohort to study the associations between delivery method and health and health resource utilization.</p> <p>Clinically, we investigated the associations between mode of delivery and outcome of postnatal depression, maternal and infant health, and we implied the risk predictors for outcomes by statistical methodology of marginal model with generalized estimating equations (GEE). Statistically, a variety of regression models, namely, generalized linear mixed effect model (GLMM), hierarchical generalized linear model (HGLM) and Bayesian hierarchical model were applied for this analysis and results were compared with GEEs. Some imputation strategies, namely, mean imputation, last observation carrying forward (LOCF), hot-deck imputation and multiple imputation were employed for handling missing values in this study.</p> <p>Analysis results demonstrated that there was no statistically significant association between mode of delivery and postpartum depression [OR 0.99, 95% CI (0.73, 1.34)]. However, the development of postpartum depression was found to be associated with low income, low mental and physical health functioning, lack of social support, the low number of unmet learning needs in hospital, and English or French spoken at home. Results were consistent for all regression models but GEE provided the best fit and an excellent discriminative ability. GEE models were constructed on different datasets imputed by mean, LOCF, hot-deck and multiple imputation, and LOCF was recommended to handle the missing data in this longitudinal study.</p> <p>Analyses on the outcome of maternal health and infant health stated that method of delivery had a statistically significant influence on maternal health but no significant impact on infant health. Risks of maternal health problems were associated with cesarean delivery, good/fair/poor infant health, low maternal mental and physical health functioning, lack of care for maternal mental health, and good/fair/poor health before pregnancy. Risks of infant health problems were associated with good/fair/poor maternal health before pregnancy and after discharge, inadequate care or help for infant health, fair/poor community services after discharge, low maternal mental health functioning, non-English or non-French spoken at home, and mothers born outside of Canada.</p> / Master of Science (MSc)