This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.

In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.

Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at gradformat@asu.edu.

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Description
Research has shown that a developmental process of maturing out of alcohol involvement occurs during young adulthood, and that this process is related to both young adult role transitions (e.g., marriage) and personality developmental (e.g., decreased disinhibition and neuroticism). The current study extended past research by testing whether protective marriage

Research has shown that a developmental process of maturing out of alcohol involvement occurs during young adulthood, and that this process is related to both young adult role transitions (e.g., marriage) and personality developmental (e.g., decreased disinhibition and neuroticism). The current study extended past research by testing whether protective marriage and personality effects on maturing out were stronger among more severe late adolescent drinkers, and whether protective marriage effects were stronger among those who experienced more personality development. Parental alcoholism and gender were tested as moderators of marriage, personality, and late adolescent drinking effects on maturing out; and as distal predictors mediated by these effects. Participants were a subsample (N = 844; 51% children of alcoholics; 53% male, 71% non-Hispanic Caucasian, 27% Hispanic; Chassin, Barrera, Bech, & Kossak-Fuller, 1992) from a larger longitudinal study of familial alcoholism. Hypotheses were tested with latent growth models characterizing alcohol consumption and drinking consequence trajectories from late adolescence to adulthood (age 17-40). Past findings were replicated by showing protective effects of becoming married, sensation-seeking reductions, and neuroticism reductions on the drinking trajectories. Moderation tests showed that protective marriage effects on the drinking trajectories were stronger among those with higher pre-marriage drinking in late adolescence (i.e., higher growth intercepts). This might reflect role socialization mechanisms such that more severe drinking produces more conflict with the demands of new roles (i.e., role incompatibility), thus requiring greater drinking reductions to resolve this conflict. In contrast, little evidence was found for moderation of personality effects by late adolescent drinking or for moderation of marriage effects by personality. Parental alcoholism findings suggested complex moderated mediation pathways. Parental alcoholism predicted less drinking reduction through decreasing the likelihood of marriage (mediation) and muting marriage's effect on the drinking trajectories (moderation), but parental alcoholism also predicted more drinking reduction through increasing initial drinking in late adolescence (mediation). The current study provides new insights into naturally occurring processes of recovery during young adulthood and suggests that developmentally-tailored interventions for young adults could harness these natural recovery processes (e.g., by integrating role incompatibility themes and addressing factors that block role effects among those with familial alcoholism).
ContributorsLee, Matthew R. (Author) / Chassin, Laurie (Thesis advisor) / Corbin, William R. (Committee member) / Mackinnon, David P (Committee member) / Presson, Clark C. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Past literature has indicated that the majority of people with alcohol problems never seek treatment and that this is especially true of women. Relatively few studies have investigated how different types of alcohol-related consequences longitudinally predict men and women's perceived need for treatment and their utilization of treatment services. The

Past literature has indicated that the majority of people with alcohol problems never seek treatment and that this is especially true of women. Relatively few studies have investigated how different types of alcohol-related consequences longitudinally predict men and women's perceived need for treatment and their utilization of treatment services. The current study sought to expand the literature by examining whether gender moderates the links between four frequently endorsed types of consequences and perceived need for or actual utilization of treatment. Two-hundred thirty-seven adults ages 21-36 completed a battery of questionnaires at two time points five years apart. Results indicated that there were four broad types of consequences endorsed by both men and women. Multiple-group models and Wald chi square tests indicated that there were no significant relationships between consequences and treatment outcomes. No gender moderation was found but post-hoc power analyses indicated that the study was underpowered to detect moderation. Researchers need to continue to study factors that predict utilization of alcohol treatment services and the process of recovery so that treatment providers can better address the needs of people with alcohol-related consequences in the areas of referral procedures, clinical assessment, and treatment service provision and planning.
ContributorsBeltran Gonzalez, Iris (Author) / Chassin, Laurie (Thesis advisor) / Tein, Jenn-Yun (Committee member) / Corbin, William (Committee member) / Barrera, Jr., Manuel (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Nowadays product reliability becomes the top concern of the manufacturers and customers always prefer the products with good performances under long period. In order to estimate the lifetime of the product, accelerated life testing (ALT) is introduced because most of the products can last years even decades. Much research has

Nowadays product reliability becomes the top concern of the manufacturers and customers always prefer the products with good performances under long period. In order to estimate the lifetime of the product, accelerated life testing (ALT) is introduced because most of the products can last years even decades. Much research has been done in the ALT area and optimal design for ALT is a major topic. This dissertation consists of three main studies. First, a methodology of finding optimal design for ALT with right censoring and interval censoring have been developed and it employs the proportional hazard (PH) model and generalized linear model (GLM) to simplify the computational process. A sensitivity study is also given to show the effects brought by parameters to the designs. Second, an extended version of I-optimal design for ALT is discussed and then a dual-objective design criterion is defined and showed with several examples. Also in order to evaluate different candidate designs, several graphical tools are developed. Finally, when there are more than one models available, different model checking designs are discussed.
ContributorsYang, Tao (Author) / Pan, Rong (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Borror, Connie (Committee member) / Rigdon, Steve (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Juvenile offenders suffer from substance use disorders at higher rates than adolescents in the general public. Substance use disorders also predict an increased risk for re-offending. Therefore, it is important that these juveniles, in particular, receive the appropriate substance use disorder treatment. The present study used logistic regression to test

Juvenile offenders suffer from substance use disorders at higher rates than adolescents in the general public. Substance use disorders also predict an increased risk for re-offending. Therefore, it is important that these juveniles, in particular, receive the appropriate substance use disorder treatment. The present study used logistic regression to test whether race/ethnicity would moderate the match between substance use disorder diagnosis and the receipt of a substance use disorder related service in a sample of male, serious juvenile offenders. Results showed that among those with a substance use disorder diagnosis, there were no race/ethnicity differences in the receipt of the appropriate service. However, among those without a substance use disorder diagnosis, non-Hispanic Caucasians were more likely to receive substance use service than were Hispanics or African-Americans. Post-hoc analyses revealed that when using a broader definition of substance use problems, significant differences by race/ethnicity in the prediction of service receipt were only observed at low levels of substance use problems. These findings shed light on how race/ethnicity may play a role in the recommendation of substance use disorder services in the juvenile justice system.
ContributorsMansion, Andre (Author) / Chassin, Laurie (Thesis advisor) / Dishion, Thomas (Committee member) / Knight, George (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Nonregular screening designs can be an economical alternative to traditional resolution IV 2^(k-p) fractional factorials. Recently 16-run nonregular designs, referred to as no-confounding designs, were introduced in the literature. These designs have the property that no pair of main effect (ME) and two-factor interaction (2FI) estimates are completely confounded. In

Nonregular screening designs can be an economical alternative to traditional resolution IV 2^(k-p) fractional factorials. Recently 16-run nonregular designs, referred to as no-confounding designs, were introduced in the literature. These designs have the property that no pair of main effect (ME) and two-factor interaction (2FI) estimates are completely confounded. In this dissertation, orthogonal arrays were evaluated with many popular design-ranking criteria in order to identify optimal 20-run and 24-run no-confounding designs. Monte Carlo simulation was used to empirically assess the model fitting effectiveness of the recommended no-confounding designs. The results of the simulation demonstrated that these new designs, particularly the 24-run designs, are successful at detecting active effects over 95% of the time given sufficient model effect sparsity. The final chapter presents a screening design selection methodology, based on decision trees, to aid in the selection of a screening design from a list of published options. The methodology determines which of a candidate set of screening designs has the lowest expected experimental cost.
ContributorsStone, Brian (Author) / Montgomery, Douglas C. (Thesis advisor) / Silvestrini, Rachel T. (Committee member) / Fowler, John W (Committee member) / Borror, Connie M. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This dissertation explores different methodologies for combining two popular design paradigms in the field of computer experiments. Space-filling designs are commonly used in order to ensure that there is good coverage of the design space, but they may not result in good properties when it comes to model fitting. Optimal

This dissertation explores different methodologies for combining two popular design paradigms in the field of computer experiments. Space-filling designs are commonly used in order to ensure that there is good coverage of the design space, but they may not result in good properties when it comes to model fitting. Optimal designs traditionally perform very well in terms of model fitting, particularly when a polynomial is intended, but can result in problematic replication in the case of insignificant factors. By bringing these two design types together, positive properties of each can be retained while mitigating potential weaknesses. Hybrid space-filling designs, generated as Latin hypercubes augmented with I-optimal points, are compared to designs of each contributing component. A second design type called a bridge design is also evaluated, which further integrates the disparate design types. Bridge designs are the result of a Latin hypercube undergoing coordinate exchange to reach constrained D-optimality, ensuring that there is zero replication of factors in any one-dimensional projection. Lastly, bridge designs were augmented with I-optimal points with two goals in mind. Augmentation with candidate points generated assuming the same underlying analysis model serves to reduce the prediction variance without greatly compromising the space-filling property of the design, while augmentation with candidate points generated assuming a different underlying analysis model can greatly reduce the impact of model misspecification during the design phase. Each of these composite designs are compared to pure space-filling and optimal designs. They typically out-perform pure space-filling designs in terms of prediction variance and alphabetic efficiency, while maintaining comparability with pure optimal designs at small sample size. This justifies them as excellent candidates for initial experimentation.
ContributorsKennedy, Kathryn (Author) / Montgomery, Douglas C. (Thesis advisor) / Johnson, Rachel T. (Thesis advisor) / Fowler, John W (Committee member) / Borror, Connie M. (Committee member) / Arizona State University (Publisher)
Created2013
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Description
During the initial stages of experimentation, there are usually a large number of factors to be investigated. Fractional factorial (2^(k-p)) designs are particularly useful during this initial phase of experimental work. These experiments often referred to as screening experiments help reduce the large number of factors to a smaller set.

During the initial stages of experimentation, there are usually a large number of factors to be investigated. Fractional factorial (2^(k-p)) designs are particularly useful during this initial phase of experimental work. These experiments often referred to as screening experiments help reduce the large number of factors to a smaller set. The 16 run regular fractional factorial designs for six, seven and eight factors are in common usage. These designs allow clear estimation of all main effects when the three-factor and higher order interactions are negligible, but all two-factor interactions are aliased with each other making estimation of these effects problematic without additional runs. Alternatively, certain nonregular designs called no-confounding (NC) designs by Jones and Montgomery (Jones & Montgomery, Alternatives to resolution IV screening designs in 16 runs, 2010) partially confound the main effects with the two-factor interactions but do not completely confound any two-factor interactions with each other. The NC designs are useful for independently estimating main effects and two-factor interactions without additional runs. While several methods have been suggested for the analysis of data from nonregular designs, stepwise regression is familiar to practitioners, available in commercial software, and is widely used in practice. Given that an NC design has been run, the performance of stepwise regression for model selection is unknown. In this dissertation I present a comprehensive simulation study evaluating stepwise regression for analyzing both regular fractional factorial and NC designs. Next, the projection properties of the six, seven and eight factor NC designs are studied. Studying the projection properties of these designs allows the development of analysis methods to analyze these designs. Lastly the designs and projection properties of 9 to 14 factor NC designs onto three and four factors are presented. Certain recommendations are made on analysis methods for these designs as well.
ContributorsShinde, Shilpa (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie (Committee member) / Fowler, John (Committee member) / Jones, Bradley (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Levels of heavy episodic drinking peak during emerging adulthood and contribute to the experience of negative consequences. Previous research has identified a number of trait-like personality characteristics that are associated with drinking. Studies of the Acquired Preparedness Model have supported positive expectancies, and to a lesser extent negative expectancies, as

Levels of heavy episodic drinking peak during emerging adulthood and contribute to the experience of negative consequences. Previous research has identified a number of trait-like personality characteristics that are associated with drinking. Studies of the Acquired Preparedness Model have supported positive expectancies, and to a lesser extent negative expectancies, as mediators of the relation between trait-like characteristics and alcohol outcomes. However, expectancies measured via self-report may reflect differences in learned expectancies in spite of similar alcohol-related responses, or they may reflect true individual differences in subjective responses to alcohol. The current study addressed this gap in the literature by assessing the relative roles of expectancies and subjective response as mediators within the APM in a sample of 236 emerging adults (74.7% male) participating in a placebo-controlled alcohol challenge study. The study tested four mediation models collapsed across beverage condition as well as eight separate mediation models with four models (2 beverage by 2 expectancy/subjective response) for each outcome (alcohol use and alcohol-related problems). Consistent with previous studies, SS was positively associated with alcohol outcomes in models collapsed across beverage condition. SS was also associated with positive subjective response in collapsed models and in the alcohol models. The hypothesized negative relation between SS and sedation was not significant. In contrast to previous studies, neither stimulation nor sedation predicted either weekly drinking or alcohol-related problems. While stimulation and alcohol use appeared to have a positive and significant association, this relation did not hold when controlling for SS, suggesting that SS and stimulation account for shared variability in drinking behavior. Failure to find this association in the placebo group suggests that, while explicit positive expectancies are related to alcohol use after controlling for levels of sensation seeking, implicit expectancies (at least as assessed by a placebo manipulation) are not. That the relation between SS and stimulation held only in the alcohol condition in analyses separate by beverage condition indicates that sensation seeking is a significant predictor of positive subjective response to alcohol (stimulation), potentially above and beyond expectancies.
ContributorsScott, Caitlin (Author) / Corbin, William (Thesis advisor) / Shiota, Michelle (Committee member) / Chassin, Laurie (Committee member) / Arizona State University (Publisher)
Created2012
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Description
The hypothalamus pituitary adrenal (HPA) axis and the human genome are important components of the biological etiology of externalizing disorders. By studying the associations between specific genetic variants, diurnal cortisol, and externalizing symptoms we can begin to unpack this complex etiology. It was hypothesized that genetic variants from the corticotropine

The hypothalamus pituitary adrenal (HPA) axis and the human genome are important components of the biological etiology of externalizing disorders. By studying the associations between specific genetic variants, diurnal cortisol, and externalizing symptoms we can begin to unpack this complex etiology. It was hypothesized that genetic variants from the corticotropine releasing hormone receptor 1 (CRHR1), FK506 binding protein 51 (FKBP5), catechol-O-methyl transferase (COMT), and dopamine transporter (DAT1) genes and diurnal cortisol intercepts and slopes would separately predict externalizing symptoms. It was also hypothesized that genetic variants would moderate the association between cortisol and externalizing. Participants were 800 twins (51% boys), 88.5% Caucasian, M=7.93 years (SD=0.87) participating in the Wisconsin Twin Project. Hierarchical Linear Modeling (HLM) was used to separate the variance associated with state and trait cortisol measured across three consecutive days and trait cortisol measures were used. There were no main effects of genes on externalizing symptoms. The evening cortisol intercept, the morning cortisol slope and the evening cortisol slope predicted externalizing, but only in boys, such that boys with higher cortisol and flatter slopes across the day also had more externalizing symptoms. The morning cortisol intercept and CRHR1 rs242924 interacted to predict externalizing in both boys and girls, with GG carriers significantly higher compared to TT carriers at one standard deviation below the mean of morning cortisol. For boys only there was a significant interaction between the DAT1 variable number tandem repeat (VNTR) and the afternoon slope and a significant slope for 9/9 carriers and 9/10 carriers such that when the slope was more steep, boys carrying a nine had fewer externalizing symptoms but when the slope was less steep, they had more. Results confirm a link between diurnal trait cortisol and externalizing in boys, as well as moderation of that association by genetic polymorphisms. This is the first study to empirically examine this association and should encourage further research on the biological etiology of externalizing disorder symptoms.
ContributorsSwann, Gregory (Author) / Lemery-Chalfant, Kathryn (Thesis advisor) / Chassin, Laurie (Committee member) / Doane-Sampey, Leah (Committee member) / Arizona State University (Publisher)
Created2012
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Description
A P-value based method is proposed for statistical monitoring of various types of profiles in phase II. The performance of the proposed method is evaluated by the average run length criterion under various shifts in the intercept, slope and error standard deviation of the model. In our proposed approach, P-values

A P-value based method is proposed for statistical monitoring of various types of profiles in phase II. The performance of the proposed method is evaluated by the average run length criterion under various shifts in the intercept, slope and error standard deviation of the model. In our proposed approach, P-values are computed at each level within a sample. If at least one of the P-values is less than a pre-specified significance level, the chart signals out-of-control. The primary advantage of our approach is that only one control chart is required to monitor several parameters simultaneously: the intercept, slope(s), and the error standard deviation. A comprehensive comparison of the proposed method and the existing KMW-Shewhart method for monitoring linear profiles is conducted. In addition, the effect that the number of observations within a sample has on the performance of the proposed method is investigated. The proposed method was also compared to the T^2 method discussed in Kang and Albin (2000) for multivariate, polynomial, and nonlinear profiles. A simulation study shows that overall the proposed P-value method performs satisfactorily for different profile types.
ContributorsAdibi, Azadeh (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie (Thesis advisor) / Li, Jing (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013