Thesis (Ph. D.)--University of Wisconsin--Madison, 1981. / Typescript. Vita. eContent provider-neutral record in process. Description based on print version record. Includes bibliographical references (leaves 293-310).

Thesis (Ph. D.)--University of Texas at Austin, 2006. / Vita. Includes bibliographical references.

High levels of self-determination are associated with positive adult outcomes for young adults with developmental disabilities. Project TEAM is an intervention that teaches skills related to self-determination. The primary aims of Project TEAM are attainment of activity goals and increase in curriculum-related knowledge. This secondary analysis of a quasi-experimental study with pre and post measures and two non-randomized groups (Project TEAM participants and a “goal-setting only” comparison group) had two aims: (a) to evaluate if participation in Project TEAM is associated with greater increases in self-determination over time compared to participation in a “goal-setting only” condition; and (b) to identify predictors of change in self-determination. ANCOVA and ANCOVA analyses evaluated change in self-determination over time and regression analyses were used to evaluate predictors of changes in self-determination. The results suggest a non-significant pattern of increase in self-determination for all youth over time. Although no significant within or between group differences were identified for youth-reported changes in self-determination, youth who were younger and/or had lower levels of self-determination at baseline had greater increases in self-determination, with initial self-determination contributing significant unique variance to a predictive model. The inclusion of adaptive behavior as a covariate led to the loss of within group effects for parent-reported changes in self-determination. However, adaptive behavior was not significantly associated with or predictive of changes in parent-reported self-determination. We propose that our results reflect a dynamic relationship between personal characteristics, youths’ and parents’ frames of reference, and perceived self-determination.

Thesis (M.B.A.)--Boston University

Effective reproduction is essential for species survival. Sexual reproduction depends upon functional gonads and reproductive ducts. Zebrafish (Danio rerio) is a popular model organism, but the genetic basis of zebrafish sex determination, gonad development, and reproductive tract development are not fully understood, and understanding this basis could inform about the evolutionary conservation of these genes and the use of zebrafish to investigate and treat reproductive diseases. In chapter I, I give a overview of sex determination systems, gonad development, and reproductive duct development in mammals and fish, and ask how sex is determined and how reproductive ducts develop in zebrafish. In chapter II, I used genome wide association studies (GWAS) to investigate if the genetic basis of sex determination in a variety of zebrafish strains -- two ‘wild-type’ strains cultured for about 30 years in the lab, and four ‘natural’ strains, wild-type strains isolated directly or recently from nature in India -- and identified a sex-associated region on zebrafish chromosome 4 in natural zebrafish strains that was lacking in the lab strains. In chapter III, I investigated whether or not wnt4a is important for zebrafish ovarian development, and found that wnt4a is expressed in the early bipotential gonad and that loss of wnt4a results in male-biased sex ratios, indicating that wnt4a is important for zebrafish ovarian development. In chapter IV, I investigated whether or not wnt4a is important for male reproductive duct development, and found that loss of wnt4a slows the formation of male reproductive ducts and prevents the male fused ducti deferens from connecting to the genital orifice in zebrafish males. Results further showed that wnt4a is expressed in tissue around the site where this connection should occur before and after the connection is formed, revealing a novel wnt4a phenotype in zebrafish that hasn’t been seen thus far, and indicating that wnt4a is necessary for proper male reproductive duct development in zebrafish. This dissertation contains both published and unpublished co-authored material.

Students' self-determination (SD) can positively influence their ability to make choices in planning for their future. The current study is a preliminary validity study on the most recent 21-item version of Shogren and Wehmeyer's Self-Determination Inventory: Student Report (SDI-SR). The SDI-SR was administered to 316 students (ages 13-22) and results were examined with exploratory factor analysis (EFA) and confirmatory factor analysis (CFA). Results of the EFA on a 7-factor solution (TLI = 0.97; RMSEA = 0.04; SRMR = 0.02) aligned with the theoretical basis for the SDI:SR as well as results for the 7-factor CFA using simulated data (TLI = 0.913; RMSEA = 0.047; SRMR = 0.072 and CFI = 0.931); however, the CFA 7-factor solution results on the present study data were slightly lower than what is considered acceptable model fit (TLI = 0.883; RMSEA = 0.04; RMSR = 0.047). These results combined suggest that theory-based 7-factor solution does capture seven latent constructs in this data. A CFA was also conducted with a 5-factor structure based on factor loading from an EFA using the present research data resulting in a better model fit (TLI = 0.912; RMSEA = .075; SRMR = 0.046; and CFI = 0.940) as well as a CFA run with the simulated data resulting in an even better fit (TLI = 0.952; RMSEA = 0.040; SRMR = 0.064; and CFI = 0.967) than the 7-factor solutions. It appears the current study results aligned with five of the latent factors of SD.

Subsampling is an important method in the analysis of Big Data. Subsample size determination (SSSD) plays a crucial part in extracting information from data and in breaking<br>the challenges resulted from huge data sizes. In this thesis, (1) Sample size determination<br>(SSD) is investigated in multivariate parameters, and sample size formulas are obtained for<br>multivariate normal distribution. (2) Sample size formulas are obtained based on concentration inequalities. (3) Improved bounds for McDiarmid’s inequalities are obtained. (4) The<br>obtained results are applied to nonuniform subsampling in Big Data high dimensional linear<br>regression. (5) Numerical studies are conducted.<br>The sample size formula in univariate normal distribution is a melody in elementary<br>statistics. It appears that its generalization to multivariate normal (or more generally multivariate parameters) hasn’t been caught much attention to the best of our knowledge. In<br>this thesis, we introduce a definition for SSD, and obtain explicit formulas for multivariate<br>normal distribution, in gratifying analogy of the sample size formula in univariate normal.<br>Commonly used concentration inequalities provide exponential rates, and sample sizes<br>based on these inequalities are often loose. Talagrand (1995) provided the missing factor to<br>sharpen these inequalities. We obtained the numeric values of the constants in the missing<br>factor and slightly improved his results. Furthermore, we provided the missing factor in<br>McDiarmid’s inequality. These improved bounds are used to give shrunken sample sizes <br>

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