Assessing Methods for Assigning SNPs to Genes in Gene-Based Tests of Association Using Common Variants

Gene-based tests of association are frequently applied to common SNPs (MAF>5%) as an alternative to single-marker tests. In this analysis we conduct a variety of simulation studies applied to five popular gene-based tests investigating general trends related to their performance in realistic situations. In particular, we focus on the impact of non-causal SNPs and a variety of LD structures on the behavior of these tests. Ultimately, we find that non-causal SNPs can significantly impact the power of all gene-based tests. On average, we find that the “noise” from 6–12 non-causal SNPs will cancel out the “signal” of one causal SNP across five popular gene-based tests. Furthermore, we find complex and differing behavior of the methods in the presence of LD within and between non-causal and causal SNPs. Ultimately, better approaches for a priori prioritization of potentially causal SNPs (e.g., predicting functionality of non-synonymous SNPs), application of these methods to sequenced or fully imputed datasets, and limited use of window-based methods for assigning inter-genic SNPs to genes will improve power. However, significant power loss from non-causal SNPs may remain unless alternative statistical approaches robust to the inclusion of non-causal SNPs are developed.

The impact of eliminating extraneous sound and light on students' achievement: An empirical study

The impact of eliminating extraneous sound and light on students’ achievement was investigated under four conditions: Light and Sound controlled, Sound Only controlled, Light Only controlled and neither Light nor Sound controlled. Group, age and gender were the control variables. Four randomly selected groups of high school freshmen students with different backgrounds were the participants in this study. Academic achievement was the dependent variable measured on a pretest, a posttest and a post-posttest, each separated by an interval of 15 days. ANOVA was used to test the various hypotheses related to the impact of eliminating sound and light on student learning. Independent sample T tests on the effect of gender indicated a significant effect while age was non- significant. Follow up analysis indicated that sound and light are not potential sources of extraneous load when tested individually. However, the combined effect of sound and light seems to be a potential source of extrinsic load. The findings revealed that the performance of the Sound and Light controlled group was greater during the posttest and post-posttest. The overall performance of boys was greater than that of girls. Results indicated a significant interaction effect between group and gender on treatment subjects. However gender alone was non-significant. Performance of group by age had no significant interaction and age alone was non-significant in the posttest and post-posttest. Based on the results obtained sound and light combined seemed to be the potential sources of extraneous load in this type of learning environment. This finding supports previous research on the effect of sound and light on learning. The findings of this study show that extraneous sound and light have an impact on learning. These findings can be used to design better learning environments. Such environments can be achieved with different electric lighting and sound systems that provide optimal color rendering, low glare, low flicker, low noise and reverberation. These environments will help people avoid unwanted distraction, drowsiness, and photosensitive behavior.

A study of stock market fluctuations and their relation to business conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubblelike deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the nonfundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.

Adapting Mpowerment to a Rural Area

As HIV/AIDS continues to disproportionately impact men who have sex with men (MSM) (CDC, 2010a), effective and timely prevention strategies for this population must be developed. Specifically, evidence-based interventions that can be easily adapted and have proven effectiveness are needed. Hence, the purpose of the current study was to assess the impact of the Mpowerment Project (Hayes, Rebchook, & Kegeles, 2003), a community level HIV prevention program originally designed for young urban gay men, when adapted for rural gay men. The Mpowerment Project is recognized as evidence- based intervention by the CDC (CDC, 2009b). The current study is an extension of this research, assessing Mpowerment model fidelity and the behavioral and attitudinal changes that occurred among participants. Data were collected from participants in a rural area of southeast Idaho from 2002-2004. Data were collected prior to M-Group participation and at a three months follow-up. The 66 individuals completing the M-Group pre and posttest assessment also attended a minimum of three study events and a maximum of 226 events. Results revealed no significant changes in attitudinal variables and all but one behavioral variable among Rural Mpowerment (R-MP) participants. The one significant behavior change was an increase in reported safer sex discussion among friends, indicating a possible change in the social norm regarding safer sex. Results also indicate that program fidelity was maintained and the Mpowerment Project is adaptable to rural areas. However, there was no indication of attitudinal changes in participants of this study. There were no changes in behavioral variables aside from discussion about safer sex with friends increasing. The lack of evidence-based interventions for rural gay men highlights the need for further research on the community impact of the Mpowerment Project on rural participants.

The relationship between staff perceptions of principal leadership and school performance

The climate of a school can be defined as the set of internal characteristics that distinguishes one school from another and influences the behavior of its members (Hoy & Hannum, 1997). Schools with a positive climate have been shown to positively impact students (Hoy, 1972). A principal’s leadership style influences the climate that, in turn, impacts student performance. ^ In this work, the researcher investigated Miami-Dade County Public Schools in order to determine if there was a relationship between instructional staff members’ perceptions of their school’s principals, a derivative of the district’s school climate studies, and their schools’ grades. ^ Eight School Climate Survey items were inter-correlated. The smallest intercorrelation was .83, which is still a large intercorrelation, and the largest intercorrelation was .96. Pearson’s correlation analysis (Healey, 2004) was run to determine the relationship between schools’ earned points and averaged survey responses. Survey items 8, 9, 12 and 13 had weak (less than .30) positive correlations to schools’ earned points. Survey items 7, 10, 11 and 14 had moderate (above .30) positive correlations to schools’ earned points. ^ The researcher created a composite variable (Pallant, 2007) from all the School Climate Survey responses. This composite variable, titled Principal Leadership Score, allowed the researcher to determine that approximately 9% of the variance in the points earned by schools in 2009 can be accounted for by how teachers in this study perceived the leadership of their principals. ^ This study’s findings of a moderate positive correlation between teachers’ perceptions of principal leadership and school performance supports earlier research linking school climate and school performance. Due to the fact that the leadership of the principal affects, either positively or negatively, the learning and working environment of students and teachers, it is recommended that principals use the eight School Climate Survey items examined within this study as guides (Pepper & Thomas, 2002). Through focusing on these survey items, principals may be propelled to self-identify their leadership strengths as well as leadership weaknesses.^

Adapting Mpowerment to a rural area

As HIV/AIDS continues to disproportionately impact men who have sex with men (MSM) (CDC, 2010a), effective and timely prevention strategies for this population must be developed. Specifically, evidence-based interventions that can be easily adapted and have proven effectiveness are needed. Hence, the purpose of the current study was to assess the impact of the Mpowerment Project (Hayes, Rebchook, & Kegeles, 2003), a community level HIV prevention program originally designed for young urban gay men, when adapted for rural gay men. The Mpowerment Project is recognized as evidence- based intervention by the CDC (CDC, 2009b). The current study is an extension of this research, assessing Mpowerment model fidelity and the behavioral and attitudinal changes that occurred among participants. Data were collected from participants in a rural area of southeast Idaho from 2002-2004. Data were collected prior to M-Group participation and at a three months follow-up. The 66 individuals completing the M-Group pre and posttest assessment also attended a minimum of three study events and a maximum of 226 events. Results revealed no significant changes in attitudinal variables and all but one behavioral variable among Rural Mpowerment (R-MP) participants. The one significant behavior change was an increase in reported safer sex discussion among friends, indicating a possible change in the social norm regarding safer sex. Results also indicate that program fidelity was maintained and the Mpowerment Project is adaptable to rural areas. However, there was no indication of attitudinal changes in participants of this study. There were no changes in behavioral variables aside from discussion about safer sex with friends increasing. The lack of evidence-based interventions for rural gay men highlights the need for further research on the community impact of the Mpowerment Project on rural participants.

Temporal changes in immigration stress, adaptation, and the factors contributing to the immigration -adaptation process in newly immigrant parents

The adaptation process to a new land can be an arduous transition for families who migrate from their countries in an attempt to evade negative life conditions. Family-based immigration has been the cornerstone of immigration policy for the U.S. However, there has been a relative lack of attention given in immigration studies to the impact of immigration particularly on parents. Furthermore, little is known about their adjustment to their post-migration circumstances, particularly the initial phase of migration, where the psychological impact of immigration tends to be concentrated. It is even rarer that investigators have addressed longitudinally the dynamic process of parents' adaptation to a new ecology, which can shed a great deal of light on its mechanisms. In this dissertation, changes over time in levels of stress, adjustment (affect balance and life satisfaction), and the factors (social support, economic hardship, and discrimination) contributing to stress and adjustment were examined in newly immigrant parents from Argentina, Colombia, Cuba, Haiti, and the West Indies. Moderating effects of gender and country-of-origin were examined as well. This study also aimed to investigate to what extent the contributing factors impacted stress and adjustment, not only concurrently, but also over the first three years of post-migration. Analysis of variance results showed that both affect balance and social support increased whereas life satisfaction decreased over time. There was no significant change in stress, however. Both gender and group effects were also observed. Mothers experienced higher stress whereas fathers experienced higher discrimination. Among groups, Haitians appeared at the greatest risk in terms of stress, discrimination, and economic hardship. A structural equation modeling analysis showed that the relative importance of contributing factors changed over time in the process of immigrants' adaptation. Yet, social support emerged as a powerful protective factor in that its effects carried over time, and discrimination was a primary mediator through which other predictors were related to stress and adjustment. These findings shed light on the "hows and whys" of the immigration-adaptation process, by demonstrating the significance of specific conditions of life change to psychological outcomes as newly immigrant parents adapt to their post-migration ecology.

A Study of Stock Market Fluctuations and their Relations to Business Conditions

Most research on stock prices is based on the present value model or the more general consumption-based model. When applied to real economic data, both of them are found unable to account for both the stock price level and its volatility. Three essays here attempt to both build a more realistic model, and to check whether there is still room for bubbles in explaining fluctuations in stock prices. In the second chapter, several innovations are simultaneously incorporated into the traditional present value model in order to produce more accurate model-based fundamental prices. These innovations comprise replacing with broad dividends the more narrow traditional dividends that are more commonly used, a nonlinear artificial neural network (ANN) forecasting procedure for these broad dividends instead of the more common linear forecasting models for narrow traditional dividends, and a stochastic discount rate in place of the constant discount rate. Empirical results show that the model described above predicts fundamental prices better, compared with alternative models using linear forecasting process, narrow dividends, or a constant discount factor. Nonetheless, actual prices are still largely detached from fundamental prices. The bubble-like deviations are found to coincide with business cycles. The third chapter examines possible cointegration of stock prices with fundamentals and non-fundamentals. The output gap is introduced to form the non-fundamental part of stock prices. I use a trivariate Vector Autoregression (TVAR) model and a single equation model to run cointegration tests between these three variables. Neither of the cointegration tests shows strong evidence of explosive behavior in the DJIA and S&P 500 data. Then, I applied a sup augmented Dickey-Fuller test to check for the existence of periodically collapsing bubbles in stock prices. Such bubbles are found in S&P data during the late 1990s. Employing econometric tests from the third chapter, I continue in the fourth chapter to examine whether bubbles exist in stock prices of conventional economic sectors on the New York Stock Exchange. The ‘old economy’ as a whole is not found to have bubbles. But, periodically collapsing bubbles are found in Material and Telecommunication Services sectors, and the Real Estate industry group.