Browsing by Subject "Regression analysis"
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Item Arbitrary Symbolism in Natural Language Revisited: When Word Forms Carry Meaning(Public Library of Science, 2012) Reilly, Jamie; Westbury, Chris; Kean, Jacob; Peelle, Jonathan E.; Physical Medicine and Rehabilitation, School of MedicineCognitive science has a rich history of interest in the ways that languages represent abstract and concrete concepts (e.g., idea vs. dog). Until recently, this focus has centered largely on aspects of word meaning and semantic representation. However, recent corpora analyses have demonstrated that abstract and concrete words are also marked by phonological, orthographic, and morphological differences. These regularities in sound-meaning correspondence potentially allow listeners to infer certain aspects of semantics directly from word form. We investigated this relationship between form and meaning in a series of four experiments. In Experiments 1-2 we examined the role of metalinguistic knowledge in semantic decision by asking participants to make semantic judgments for aurally presented nonwords selectively varied by specific acoustic and phonetic parameters. Participants consistently associated increased word length and diminished wordlikeness with abstract concepts. In Experiment 3, participants completed a semantic decision task (i.e., abstract or concrete) for real words varied by length and concreteness. Participants were more likely to misclassify longer, inflected words (e.g., "apartment") as abstract and shorter uninflected abstract words (e.g., "fate") as concrete. In Experiment 4, we used a multiple regression to predict trial level naming data from a large corpus of nouns which revealed significant interaction effects between concreteness and word form. Together these results provide converging evidence for the hypothesis that listeners map sound to meaning through a non-arbitrary process using prior knowledge about statistical regularities in the surface forms of words.Item Attachment Avoidance and Depressive Symptoms: A Test of Moderation by Cognitive Abilities(2014-09-04) Shea, Amanda Marie; Rand, Kevin L.; Stewart, Jesse C.; Cyders, Melissa A.; Ashburn-Nardo, Leslie; Grahame, Nicholas J.The substantial interpersonal and economic costs of depression make it imperative to better understand the predictors and moderators of depressive symptoms. The ability to use social support protects people from depressive symptoms, but individuals high in attachment avoidance tend not to use others as sources of support. Research has found that attachment avoidance is related to depressive symptoms in some samples but not in others (Mikulincer & Shaver, 2007; Shea, 2011). Thus, there appear to be factors that moderate the relationship between attachment avoidance and depressive symptoms. The present study examined if cognitive abilities that facilitate effective emotion regulation strategies moderate the relationship between attachment avoidance and depressive symptoms. Using a sample of college students, attachment avoidance, cognitive abilities, depressive symptoms, and other indices of psychological distress and well-being were measured and examined for evidence of moderation via hierarchical linear regression. The hypothesis that cognitive abilities moderate the relationship between attachment avoidance and depressive symptoms was not supported (ΔR2 = 0.02, p = .68). Factors contributing to the null findings are discussed and conceptual and methodological suggestions are offered for future research.Item Dietary intake and urinary excretion of phytoestrogens in relation to cancer and cardiovascular disease(2014) Reger, Michael Kent; Zollinger, Terrell; Jones, Josette F.; Liu, Ziyue; Zhang, JianjunPhytoestrogens that abound in soy products, legumes, and chickpeas can induce biologic responses in animals and humans due to structural similarity to 17β-estradiol. Although experimental studies suggest that phytoestrogen intake may alter the risk of cancer and cardiovascular disease, few epidemiologic studies have investigated this research question. This dissertation investigated the associations of intake of total and individual phytoestrogens and their urinary biomarkers with these chronic conditions using data previously collected from two US national cohort studies (NHANES and PLCO). Utilizing NHANES data with urinary phytoestrogen concentrations and follow-up mortality, Cox proportional hazards regression (HR; 95% CI) were performed to evaluate the association between total cancer, cardiovascular disease, and all-cause mortality and urinary phytoestrogens. After adjustment for confounders, it was found that higher concentrations of lignans were associated with a reduced risk of death from cardiovascular disease (0.48; 0.24-0.97), whereas higher concentrations of isoflavones (2.14; 1.03-4.47) and daidzein (2.05; 1.02-4.11) were associated with an increased risk. A reduction in all-cause mortality was observed for elevated concentrations of lignans (0.65; 0.43-0.96) and enterolactone (0.65; 0.44-0.97). Utilizing PLCO data and dietary phytoestrogens, Cox proportional hazards regression examined the associations between dietary phytoestrogens and the risk of prostate cancer incidence. After adjustment for confounders, a positive association was found between dietary intake of isoflavones (1.58; 1.11-2.24), genistein (1.42; 1.02-1.98), daidzein (1.62; 1.13-2.32), and glycitein (1.53; 1.09-2.15) and the risk of advanced prostate cancer. Conversely, an inverse association existed between dietary intake of genistein and the risk of non-advanced prostate cancer (0.88; 0.78-0.99) and total prostate cancer (0.90; 0.81-1.00). C-reactive protein (CRP) concentration levels rise in response to inflammation and higher levels are a risk factor for some cancers and cardiovascular disease reported in epidemiologic studies. Logistic regression performed on NHANES data evaluated the association between CRP and urinary phytoestrogen concentrations. Higher concentrations of total and individual phytoestrogens were associated with lower concentrations of CRP. In summary, dietary intake of some phytoestrogens significantly modulates prostate cancer risk and cardiovascular disease mortality. It is possible that these associations may be in part mediated through the influence of phytoestrogen intake on circulating levels of C-reactive protein.Item Effects of Genetic Variants Previously Associated with Fasting Glucose and Insulin in the Diabetes Prevention Program(Public Library of Science, 2012) Florez, Jose C.; Jablonski, Kathleen A.; McAteer, Jarred B.; Franks, Paul W.; Mason, Clinton C.; Mather, Kieren; Horton, Edward; Goldberg, Ronald; Dabelea, Dana; Kahn, Steven E.; Arakaki, Richard F.; Shuldiner, Alan R.; Knowler, William C.; Diabetes Prevention Program Research Group; Medicine, School of MedicineCommon genetic variants have been recently associated with fasting glucose and insulin levels in white populations. Whether these associations replicate in pre-diabetes is not known. We extended these findings to the Diabetes Prevention Program, a clinical trial in which participants at high risk for diabetes were randomized to placebo, lifestyle modification or metformin for diabetes prevention. We genotyped previously reported polymorphisms (or their proxies) in/near G6PC2, MTNR1B, GCK, DGKB, GCKR, ADCY5, MADD, CRY2, ADRA2A, FADS1, PROX1, SLC2A2, GLIS3, C2CD4B, IGF1, and IRS1 in 3,548 Diabetes Prevention Program participants. We analyzed variants for association with baseline glycemic traits, incident diabetes and their interaction with response to metformin or lifestyle intervention. We replicated associations with fasting glucose at MTNR1B (P<0.001), G6PC2 (P = 0.002) and GCKR (P = 0.001). We noted impaired β-cell function in carriers of glucose-raising alleles at MTNR1B (P<0.001), and an increase in the insulinogenic index for the glucose-raising allele at G6PC2 (P<0.001). The association of MTNR1B with fasting glucose and impaired β-cell function persisted at 1 year despite adjustment for the baseline trait, indicating a sustained deleterious effect at this locus. We also replicated the association of MADD with fasting proinsulin levels (P<0.001). We detected no significant impact of these variants on diabetes incidence or interaction with preventive interventions. The association of several polymorphisms with quantitative glycemic traits is replicated in a cohort of high-risk persons. These variants do not have a detectable impact on diabetes incidence or response to metformin or lifestyle modification in the Diabetes Prevention Program.Item Factors in African American social work student persistence(2014-07-30) Green, Jacqualyn F.; Barton, William H., 1949-; Brown, O. Gilbert; Haas, Linda; Hull, Grafton H.; Smith, Linda A.Population estimations for the year 2000 indicate an increase in poor and minorities in the United States (Loden & Rosener, 1991). In view of this growth trend, Berger (1989) suggests a need for social workers with sensitivity to such populations. The presence of minority perspectives provides a valuable contribution to service delivery (Mullen et al., 1993). Efforts to enhance student persistence in graduate schools of social work will contribute to the pool of social workers available in the next century. The purpose of this study is to determine the factors that contribute to African American student persistence in graduate schools of social work. This study applies aspects of Astin's, Tinto's and Green's theories of persistence. Astin's theory of involvement (1975) considers student investment of time in educational pursuits. Tinto's (1975) theory of departure includes background, social and academic aspects in persistence decisions. Green's (1997) theory focuses on the ability of the student to cope with racial issues (racial resilience) and the racial climate of the school (racial responsiveness). One hundred and thirty-five students from two predominantly white and two historically black universities participated in surveys administered to determine the effect of involvement, background, academic, social, resilience factors, and college type upon student persistence outcomes. Interviews held with administrative personnel at each institution provided contextual data. Correlations were used to examine the relationships among all of the variables in the study. T-Tests were conducted to compare outcomes due to university type. Multiple regressions were used to explore the relationships between significant independent variables and persistence. The findings of this study indicate that persistence outcomes of African American graduate social work students are influenced by: (a) academic performance, faculty-student relationships, (c) health, (d) the ability to deal with stress, and (e) ethnic pride (impressions of ethnic group). These findings suggest that social work programs that incorporate aggressive grade monitoring practices, provide diverse opportunities for student-faculty interaction, offer opportunities for health care, stress alternatives, and a culturally relevant curriculum, may positively influence African American student persistence.Item Flexible models of time-varying exposures(2015-05) Wang, Chenkun; Gao, Sujuan; Liu, Hai; Yu, Zhangsheng; Callahan, Christopher M.With the availability of electronic medical records, medication dispensing data offers an unprecedented opportunity for researchers to explore complex relationships among longterm medication use, disease progression and potential side-effects in large patient populations. However, these data also pose challenges to existing statistical models because both medication exposure status and its intensity vary over time. This dissertation focused on flexible models to investigate the association between time-varying exposures and different types of outcomes. First, a penalized functional regression model was developed to estimate the effect of time-varying exposures on multivariate longitudinal outcomes. Second, for survival outcomes, a regression spline based model was proposed in the Cox proportional hazards (PH) framework to compare disease risk among different types of time-varying exposures. Finally, a penalized spline based Cox PH model with functional interaction terms was developed to estimate interaction effect between multiple medication classes. Data from a primary care patient cohort are used to illustrate the proposed approaches in determining the association between antidepressant use and various outcomes.Item Food attentional biases and adiposity: are energy intake and external eating mediators of this relationship?(2015-08) Vrany, Elizabeth; Stewart, Jesse C.; Cyders, Melissa Anne; Mosher, Catherine EstherObesity is a substantial threat to the health of over a third of adults in the United States. Some evidence suggests that food attentional bias, or the tendency to automatically direct attention toward food-related stimuli in the environment, may contribute to the development of obesity in susceptible individuals. This study hypothesized that (1) food attentional bias would be positively associated with adiposity, (2) food attentional bias would be positively associated with energy intake and external eating, and (3) energy intake and external eating would partially mediate the association between food attentional bias and adiposity. Data were collected from a sample of 120 undergraduate students. Three measures of food attentional bias were obtained: reaction time bias obtained from a visual dot-probe task and direction bias and duration bias obtained from eye tracking. Adiposity indices of body mass index (kg/m2) and body fat percent were measured using standard medical devices. Data were obtained for two mediators: 1) energy intake was assessed by web-based automated 24-hour dietary recall and 2) external eating was assessed using the External Eating Subscale of the Dutch Eating Behavior Questionnaire. Separate linear regression models examining the association between each measure of food attentional bias with each measure of adiposity (adjusted for age, sex, race/ethnicity, and subjective hunger) indicated no associations. Similarly, linear regression analyses revealed no associations between measures of food attentional bias and energy intake or external eating. Models testing for statistical mediation demonstrated that energy intake and external eating were not significant mediators. However, mediation analyses demonstrated a significant overall effect and direct effect between direction bias and BMI in a reduced sample used to test for energy intake as a mediator, suggesting the presence of an association which may not have been detected in the larger sample due to methodological issues, measurement error, or type I error. Despite the overall null results, these findings, in conjunction with previous studies on food attentional biases and adiposity, highlight the need for future investigations examining prospective associations between food attentional bias and adiposity.Item From phenotype to genotype: an association study of longitudinal phenotypic markers to Alzheimer's disease relevant SNPs(Oxford University Press, 2012) Wang, Hua; Nie, Feiping; Huang, Heng; Yan, Jingwen; Kim, Sungeun; Nho, Kwangsik; Risacher, Shannon L.; Saykin, Andrew J.; Shen, Li; Alzheimer’s Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineMotivation: Imaging genetic studies typically focus on identifying single-nucleotide polymorphism (SNP) markers associated with imaging phenotypes. Few studies perform regression of SNP values on phenotypic measures for examining how the SNP values change when phenotypic measures are varied. This alternative approach may have a potential to help us discover important imaging genetic associations from a different perspective. In addition, the imaging markers are often measured over time, and this longitudinal profile may provide increased power for differentiating genotype groups. How to identify the longitudinal phenotypic markers associated to disease sensitive SNPs is an important and challenging research topic. Results: Taking into account the temporal structure of the longitudinal imaging data and the interrelatedness among the SNPs, we propose a novel 'task-correlated longitudinal sparse regression' model to study the association between the phenotypic imaging markers and the genotypes encoded by SNPs. In our new association model, we extend the widely used ℓ(2,1)-norm for matrices to tensors to jointly select imaging markers that have common effects across all the regression tasks and time points, and meanwhile impose the trace-norm regularization onto the unfolded coefficient tensor to achieve low rank such that the interrelationship among SNPs can be addressed. The effectiveness of our method is demonstrated by both clearly improved prediction performance in empirical evaluations and a compact set of selected imaging predictors relevant to disease sensitive SNPs.Item Investigating Predictors of Treatment Attrition Among Court-Ordered Batterers(The original doi for the final version of the article is 10.1300/J079v28n04_03. To access the doi, open the following DOI site in your browser and cut and paste the doi name where indicated: [LINK]http://dx.doi.org[/LINK]. [BREAK] Access to the original article may require subscription and authorized logon ID/password. IUPUI faculty/staff/students please check University Library resources before purchasing an article. Questions on finding the original article via our databases? Ask a librarian: [LINK] http://www.ulib.iupui.edu/research/askalibrarian [/LINK]., 2002) Buttell, Frederick P.; Pike, Cathy KingObjective: The purpose of this study was to investigate differences in demographic variables and psychological variables between treatment completers and drop-outs among abusive men entering a court-mandated treatment program. Method: The study gathered Domestic Violence Inventory (DVI) scores from 91 men, 66 treatment completers and 25 drop-outs, beginning court-ordered treatment for domestic violence offenses. Results: Logistic regression analyses indicated that none of the demographic variables or the psychological variables differentiated treatment completers from drop-outs. Conclusion: Implications of the findings for improving retention rates among men attending court-mandated batterer treatment programs were explored and discussed.Item Network-guided sparse learning for predicting cognitive outcomes from MRI measures(Springer, 2013) Yan, Jingwen; Huang, Heng; Risacher, Shannon L.; Kim, Sungeun; Inlow, Mark; Moore, Jason H.; Saykin, Andrew J.; Shen, Li; Department of Radiology and Imaging Sciences, School of MedicineAlzheimer's disease (AD) is characterized by gradual neurodegeneration and loss of brain function, especially for memory during early stages. Regression analysis has been widely applied to AD research to relate clinical and biomarker data such as predicting cognitive outcomes from MRI measures. In particular, sparse models have been proposed to identify the optimal imaging markers with high prediction power. However, the complex relationship among imaging markers are often overlooked or simplified in the existing methods. To address this issue, we present a new sparse learning method by introducing a novel network term to more flexibly model the relationship among imaging markers. The proposed algorithm is applied to the ADNI study for predicting cognitive outcomes using MRI scans. The effectiveness of our method is demonstrated by its improved prediction performance over several state-of-the-art competing methods and accurate identification of cognition-relevant imaging markers that are biologically meaningful.