Master of Science / Department of Statistics / Shie-Shien Yang / In fitting linear models, R[superscript]2 statistic has been wildly used as one of the measures to assess the goodness-of-fit and prediction power of the model. Unlike fixed linear models, at this time there is no single universally accepted measure for assessing goodness-of-fit and prediction power of a linear mixed model. In this report, we reviewed seven different approaches proposed to define a measure analogous to the usual R[superscript]2 statistic for assessing mixed models. One of seven statistics,Rc, has both conditional and marginal versions. Association mapping is an efficient way to link the genotype data with the phenotype diversity. When applying the R[superscript]2 statistic to the association mapping application, it can determine how well genetic polymorphisms, which are the explanatory variables in the mixed models, explain the phenotypic variation, which is the dependent variation. A linear mixed model method recently has been developed to control the spurious associations due to population structure and relative kinship among individuals of an association mapping. We assess seven definitions of R[superscript]2 statistic for the linear mixed model using data from two empirical association mapping samples: a sample with 277 diverse maize inbred lines and a global sample of 95 Arabidopsis thaliana accessions using the new method. R[superscript]2[subscript]LR statistic derived from the log-likelihood principle follows all the criterions of R[superscript]2 statistic and can be used to understand the overlap between population structure and relative kinship in controlling for sample relatedness. From our results,R[superscript]2[subscript]LR statistic is an appropriate R[superscript]2 statistic for comparing models with different fixed and random variables. Therefore, we recommend using RLR statistic for linear mixed models in association mapping.

This thesis was aimed to evaluate if sentiment related to stocks expressed on the subforum “Wallstreetbets” also reflects the traded volume in the stock market. For this purpose, a collection of comment data from posts filtered under the “Hot” section was issued between the 6th of April 2021 and the 20th of April 2021 on daily basis at 22.00 (GMT+2). The comments were preprocessed to filter out noise, and thereafter comments that contained mentions of stocks were analyzed using VADER, an algorithm for grading sentiment. In total sentiment regarding 13 different stocks were fitted into a mixed effect model with random slopes and intercepts. The results showed a positive correlation between sentiment expressed and the traded volume. This indicates that by studying the forum we can better understand how people invested in stocks make investment decisions, which potentially could lead to a competitive advantage over time.

Spatiotemporal dynamics of resource availability can produce markedly different patterns of landscape utilization which necessitates studying habitat selection across biologically relevant extents. Feral pigs (Sus scrofa) are a prolifically expanding, generalist species and researchers have yet to understand fundamental drivers of space use in agricultural landscapes within the United States. To study multi-scale habitat selection patterns, I deployed 13 GPS collars on feral pigs within the Mississippi Alluvial Valley. I estimated resource selection using mixed-effects models to determine how feral pigs responded to changes in forage availability and incorporated those results with autocorrelated kernel density home range estimates. My results indicated season-specific habitat functional responses to changes in agricultural phenology and illustrated the interdependencies of landscape composition, hierarchical habitat selection, and habitat functional responses. These results indicate fundamental drivers of feral pig spatial distributions in an agricultural landscape which I used to predict habitat use to direct feral pig management.

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A “Value-Added” definition of school effectiveness calls for the evaluation of schools based on the unique contribution of schools to individual student academic growth. The estimates of value-added school effectiveness are usually used for ranking and classifying schools. The current simulation study examined and compared the validity of school effectiveness estimates in four statistical models for school ranking and classification. The simulation study was conducted under two sample size conditions and the situations typical in school effectiveness research. The Conditional Cross-Classified Model (CCCM) was used to simulate data. The findings indicated that the gain score model adjusting for students’ test scores at the end of kindergarten (i. e., prior entering to an elementary school) (Gain_kindergarten) could validly rank and classify schools. Other models, including the gain score model adjusting for students’ test scores at the end of Grade 4 (i. e., one year before estimating the school effectiveness in Grade 5) (Gain_grade4), the Unconditional Cross-Classified Model (UCCM), and the Layered Mixed Effect Model (LMEM), could not validly rank or classify schools. The failure of the UCCM model in school ranking and classification indicated that ignoring covariates would distort school rankings and classifications if no other analytical remedies were applied. The failure of the LMEM model in school ranking and classification indicated that estimation of correlations among repeated measures could not alleviate the damage caused by the omitted covariates. The failure of the Gain_grade4 model cautioned against adjustment using the test scores of the previous year. The success of the Gain_kindergarten model indicated that under some circumstances, it was possible to achieve valid school rankings and classifications with only two time points of data.

A “Value-Added” definition of school effectiveness calls for the evaluation of schools based on the unique contribution of schools to individual student academic growth. The estimates of value-added school effectiveness are usually used for ranking and classifying schools. The current simulation study examined and compared the validity of school effectiveness estimates in four statistical models for school ranking and classification. The simulation study was conducted under two sample size conditions and the situations typical in school effectiveness research. The Conditional Cross-Classified Model (CCCM) was used to simulate data. The findings indicated that the gain score model adjusting for students’ test scores at the end of kindergarten (i. e., prior entering to an elementary school) (Gain_kindergarten) could validly rank and classify schools. Other models, including the gain score model adjusting for students’ test scores at the end of Grade 4 (i. e., one year before estimating the school effectiveness in Grade 5) (Gain_grade4), the Unconditional Cross-Classified Model (UCCM), and the Layered Mixed Effect Model (LMEM), could not validly rank or classify schools. The failure of the UCCM model in school ranking and classification indicated that ignoring covariates would distort school rankings and classifications if no other analytical remedies were applied. The failure of the LMEM model in school ranking and classification indicated that estimation of correlations among repeated measures could not alleviate the damage caused by the omitted covariates. The failure of the Gain_grade4 model cautioned against adjustment using the test scores of the previous year. The success of the Gain_kindergarten model indicated that under some circumstances, it was possible to achieve valid school rankings and classifications with only two time points of data.

Le traitement par éfavirenz, un médicament antirétroviral, a été associé avec des changements de profil lipidique potentiellement défavorables. Ce travail a abordé la question de savoir si ces effets dépendent des concentrations plasmatiques d’éfavirenz et, dans ce cas, si sa posologie pourrait être optimisée sans perte d'efficacité.Un modèle de pharmacocinétique de population a été développé à partir de données d’enfants infectés par le VIH. La simulation d’une population normalisée sous éfavirenz aux posologies recommandées montre que 15 % des enfants auraient des concentrations insuffisantes 12 heures après la prise, ce qui serait associé à un risque de la réplication virale de 23 %.Pour décrire la relation entre taux plasmatiques d'éfavirenz et changements de taux de cholestérol, des modèles de pharmacocinétique-pharmacodynamique (PK-PD) de réponse indirecte ont été développés. Le modèle sélectionné prédit que les taux d’éfavirenz individuels sont associés à une augmentation des lipoprotéines de haute densité sur 5 ans, et des lipoprotéines de basse densité durant 4 mois avec un retour progressif aux valeurs de base.Pour évaluer l’impact des concentrations d'éfavirenz sur l'efficacité, un modèle dynamique PK-PD a décrit la relation entre ces concentrations et l’évolution de la charge virale VIH et du taux de CD4. Un score d’efficacité a été développé sur la base d’hypothèses pharmacodynamiques pour prédire le risque de la réplication virale.L’utilisation de l’éfavirenz aux posologiques recommandées par la Food and Drug Administration aux Etats-Unis semble assurer une efficacité optimale et des changements potentiellement favorables dans les fractions de cholestérol. / As other antiretroviral drugs, treatment with efavirenz has been associated with potentially unfavorable lipid profile changes in adults and in children. The thesis addressed the question of whether these changes depend on efavirenz plasma concentrations and if dose adjustments could be envisioned without loss of efficacy.To estimate individual efavirenz exposure over 24 hours, a population pharmacokinetic model was developed using data from HIV infected children. Simulations for a normalized population receiving efavirenz dosed according recommendations predicted that 15% of children would have insufficient mid dose concentrations, associated with a 23% risk of viral replication.To describe the relationship between efavirenz concentrations and cholesterol changes, population pharmacokinetic-pharmacodynamic (PK-PD) indirect response models were developed. The selected model predicted that individual efavirenz concentrations were associated with an increase in high-density lipoprotein concentrations over 5 years but with an increase in low-density lipoprotein concentrations only during the first 4 months of treatment followed by a gradual return to baseline.To study the importance of efavirenz concentrations with regard to efficacy, a PK-PD dynamics model was developed to describe the relationship between concentrations and HIV RNA load and CD4 cell count evolutions. A score was defined based on a pharmacodynamic hypothesis to predict the risk of viral replication.Using US Food and Drug Administration dosing recommendations in children ensure optimal efficacy and potentially favorable changes in cholesterol fractions.

Indiana University-Purdue University Indianapolis (IUPUI) / Introduction: Increasing obesity in children leads to an increase in the risk of Type 2 diabetes (T2D). Therefore, it is important to promote healthier lifestyles in youths and encourage their caregivers(s) to provide a healthy lifestyle environment. The PowerHouse program focuses on improving food choices, increasing physical activity, and adopting behavior changes for the reduction of obesity and the prevention of T2D. Method: The aim of this study was to assess the effects of implementing the PowerHouse program on both clinical and quality of life outcomes in high-risk, low-income youth and their caregivers. Primary outcomes were BMI standard deviation and BMI percentile in youths. Secondary outcomes included physical activity of youths and quality of life for both youths and their caregivers. Attendance rates were also calculated. Linear effect mixed models were used to test for time effects for all outcomes. Results: Clinical outcomes did not improve over time, except for youth HbA1c (p-value = 0.0447). Some improvements in youth quality-of-life outcomes were noted: specifically, the Sports Index score of the Fels Physical Activity Questionnaire for Children (adjusted p-value = 0.0213) and the Physical Summary (p-value = 0.0407), Psychosocial Summary (p-value = 0.0167), and Total score (p-value = 0.0094) for the youth-reported Pediatric Quality of Life Inventory. Quality of life did not change over time for caregivers. For attendance, there was an improvement after the intervention was modified to improve access to fresh produce (p-value = 0.0002). Conclusion: HbA1c and quality of life improved over time for youth; however, there was not an improvement in caregiver outcomes over time. The data suggest that more time may be needed to see the full effects of the intervention, and/or that a booster intervention may be needed.

<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)

The construction industry's two main certifications are Leadership in Energy and Environmental Design (LEED) and Energy Star. To achieve the triple bottom line of sustainability for these certifications, both certifications should make a positive impact individually as well as mutually, with their impact extending to the surrounding neighborhood. This research examined the spillover effect of LEED and/or Energy Star certified office buildings on the property values of other buildings in their neighborhood in Manhattan, New York City from an economic standpoint. The spatial analysis approach using the Geographic Information System and the statistical analysis approach based on the Hedonic Price Model and the Linear Mixed Effect Model were applied to identify the geographical distribution of LEED and/or Energy Star certified office buildings and their other buildings in their neighborhoods and analyze the impact of the former on the latter. The results were as follows: 1) There was a significant correlation between a LEED and/or Energy Star certified office building and the unit market values of its adjoining buildings through the unit market values of the certified office building, the LEED and/or Energy Star certification achievement, and the major features of LEED certification; 2) There was a varying spillover effect of the certified office building on the median unit market value of buildings depending on their proximities to a LEED and/or Energy Star certified office building. This research provides a firm foundation for further efforts to quantify the spillover effect of LEED and/or Energy Star certification on a neighborhood from an economic standpoint, thus supporting and encouraging growth in the local real estate market and benefitting not only the owners, developers, and investors of the certified office building but also the owners of neighboring buildings. / Ph. D.