A fixed-links modeling approach to assess individual differences in the attentional blink: Analysis of behavioral and psychophysiological data

The attentional blink (AB) is a fundamental limitation of the ability to select relevant information from irrelevant information. It can be observed with the detection rate in an AB task as well as with the corresponding P300 amplitude of the event-related potential. In previous research, however, correlations between these two levels of observation were weak and rather inconsistent. A possible explanation of this finding might be that multiple processes underlie the AB and, thus, obscure a possible relationship between AB-related detection rate and the corresponding P300 amplitude. The present study investigated this assumption by applying a fixed-links modeling approach to represent behavioral individual differences in the AB as a latent variable. Concurrently, this approach enabled us to control for additional sources of variance in AB performance by deriving two additional latent variables. The correlation between the latent variable reflecting behavioral individual differences in AB magnitude and a corresponding latent variable derived from the P300 amplitude was high (r=.70). Furthermore, this correlation was considerably stronger than the correlations of other behavioral measures of the AB magnitude with their psychophysiological counterparts (all rs<.40). Our findings clearly indicate that the systematic disentangling of various sources of variance by utilizing the fixed-links modeling approach is a promising tool to investigate behavioral individual differences in the AB and possible psychophysiological correlates of these individual differences.

Coherence and Historical understanding in children's Biography and Historical Nonfiction Literature: A Content Analysis of Selected Orbis Pictus Books

The purpose of this study was to investigate a selection of children's historical nonfiction literature for evidence of coherence. Although research has been conducted on coherence of textbook material and its influences on comprehension there has been limited study on coherence in children's nonfiction literature. Generally, textual coherence has been seen as critical in the comprehensibility of content area textbooks because it concerns the unity of connections among ideas and information. Disciplinary coherence concerns the extent to which authors of historical text show readers how historians think and write. Since young readers are apprentices in learning historical content and conventions of historical thinking, evidence of disciplinary coherence is significant in nonfiction literature for young readers. The sample of the study contained 32 books published between 1989 and 2000 ranging in length from less than 90 pages to more than 150 pages. Content analysis was the quantitative research technique used to measure 84 variables of textual and disciplinary coherence in three passages of each book, as proportions of the total number of words for each book. Reliability analyses and an examination of 750 correlations showed the extent to which variables were related in the books. Three important findings emerged from the study that should be considered in the selection and use of children's historical nonfiction literature in classrooms. First, characteristics of coherence are significantly related together in high quality nonfiction literature. Second, shorter books have a higher proportion of textual coherence than longer books as measured in three passages. Third, presence of the author is related to characteristics of coherence throughout the books. The findings show that nonfiction literature offers students content that researchers have found textbooks lack. Both younger and older students have the opportunity to learn the conventions of historical thinking as they learn content through nonfiction literature. Further, the children's literature, represented in the Orbis Pictus list, shows students that authors select, interpret, and question information, and give other interpretations. The implications of the study for teaching history, teacher preparation in content and literacy, school practices, children's librarians, and publishers of children's nonfiction are discussed.

An analysis of two methods for the classification of stage of readiness to obtain repeat mammography screening

Background and purpose: Breast cancer continues to be a health problem for women, representing 28 percent of all female cancers and remaining one of the leading causes of death for women. Breast cancer incidence rates become substantial before the age of 50. After menopause, breast cancer incidence rates continue to increase with age creating a long-lasting source of concern (Harris et al., 1992). Mammography, a technique for the detection of breast tumors in their nonpalpable stage when they are most curable, has taken on considerable importance as a public health measure. The lifetime risk of breast cancer is approximately 1 in 9 and occurs over many decades. Recommendations are that screening be periodic in order to detect cancer at early stages. These recommendations, largely, are not followed. Not only are most women not getting regular mammograms, but this circumstance is particularly the case among older women where regular mammography has been proven to reduce mortality by approximately 30 percent. The purpose of this project was to increase our understanding of factors that are associated with stage of readiness to obtain subsequent mammograms. A secondary purpose of this research was to suggest further conceptual considerations toward the extension of the Transtheoretical Model (TTM) of behavior change to repeat screening mammography. ^ Methods. A sample (n = 1,222) of women 50 years and older in a large multi-specialty clinic in Houston, Texas was surveyed by mail questionnaire regarding their previous screening experience and stage of readiness to obtain repeat screening. A computerized database, maintained on all women who undergo mammography at the clinic, was used to identify women who are eligible for the project. The major statistical technique employed to select the significant variables and to examine the man and interaction effects of independent variables on dependent variables was polychotomous stepwise, logistic regression. A prediction model for each stage of readiness definition was estimated. The expected probabilities for stage of readiness were calculated to assess the magnitude and direction of significant predictors. ^ Results. Analysis showed that both ways of defining stage of readiness for obtaining a screening mammogram were associated with specific constructs, including decisional balance and processes of the change. ^ Conclusions. The results of the present study demonstrate that the TTM appears to translate to repeat mammography screening. Findings in the current study also support finding of previous studies that suggest that stage of readiness is associated with respondent decisional balance and the processes of change. ^

An Appropriate Role for the Leadership: A Quantitative Analysis of the Effects of House Leadership on Open-Seat Races

This paper investigates the effects on open-seat races in the United States House of Representatives. This project focuses on the influence that the House leadership exerts on races. Generally, the leadership influences race through spending by party organizations and leadership visits. During each election cycle, national party organizations spend millions of dollars to get their candidates into office. I have developed a multiple regression model that measures different types of spending from the Democratic Congressional Campaign Committee, the National Republican Congressional Committee, and the Republican National Committee and the effects of these spending types on the election results. Also, the study examines the number of visits by each party’s leadership to each race. I introduced control variables that account for the year, the competitiveness of each race, and the individual candidate fundraising. In terms of statistical significance, the results were mixed showing one type of party spending to be highly influential in the outcome of the race. Competitiveness and individual candidate fundraising also achieved statistical significance. The study also includes a qualitative investigation of leadership visits and individual case studies in order to understand better the way in which the data interact in real campaigns.

Application of stellar photometry to the analysis of microarray images

Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

Bayesian generalized linear models for meta-analysis of diagnostic tests

With the recognition of the importance of evidence-based medicine, there is an emerging need for methods to systematically synthesize available data. Specifically, methods to provide accurate estimates of test characteristics for diagnostic tests are needed to help physicians make better clinical decisions. To provide more flexible approaches for meta-analysis of diagnostic tests, we developed three Bayesian generalized linear models. Two of these models, a bivariate normal and a binomial model, analyzed pairs of sensitivity and specificity values while incorporating the correlation between these two outcome variables. Noninformative independent uniform priors were used for the variance of sensitivity, specificity and correlation. We also applied an inverse Wishart prior to check the sensitivity of the results. The third model was a multinomial model where the test results were modeled as multinomial random variables. All three models can include specific imaging techniques as covariates in order to compare performance. Vague normal priors were assigned to the coefficients of the covariates. The computations were carried out using the 'Bayesian inference using Gibbs sampling' implementation of Markov chain Monte Carlo techniques. We investigated the properties of the three proposed models through extensive simulation studies. We also applied these models to a previously published meta-analysis dataset on cervical cancer as well as to an unpublished melanoma dataset. In general, our findings show that the point estimates of sensitivity and specificity were consistent among Bayesian and frequentist bivariate normal and binomial models. However, in the simulation studies, the estimates of the correlation coefficient from Bayesian bivariate models are not as good as those obtained from frequentist estimation regardless of which prior distribution was used for the covariance matrix. The Bayesian multinomial model consistently underestimated the sensitivity and specificity regardless of the sample size and correlation coefficient. In conclusion, the Bayesian bivariate binomial model provides the most flexible framework for future applications because of its following strengths: (1) it facilitates direct comparison between different tests; (2) it captures the variability in both sensitivity and specificity simultaneously as well as the intercorrelation between the two; and (3) it can be directly applied to sparse data without ad hoc correction. ^

A geographic analysis of liver cancer mortality and alcohol dependence or abuse in Texas and the U.S., 1980--2003

Background. Liver cancer mortality continues to be a significant factor in deaths worldwide and in the U.S., yet there remains a lack of studies on how mortality burden is impacted by racial groups or by heavy alcohol use. This study evaluated the geographic distribution of liver cancer mortality across population groups in Texas and the U.S. over a 24-year period, as well as determining whether alcohol dependence or abuse correlates with mortality rates. ^ Methods. The Spatial Scan Statistic was used to identify regions of excess liver cancer mortality in Texas counties and the U.S. from 1980 to 2003. The statistic was conducted with a spatial cluster size of 50% of the population at risk, and all analyses used publicly available data. Alcohol abuse data by state and ethnicity were extracted from SAMHSA datasets for the study period 2000–2004. ^ Results. The results of the geographic analysis of liver cancer mortality in both Texas and the U.S. indicate that there were four and seven regions, respectively, that were identified as having statistically significant excess mortality rates with elevated relative risks ranging from 1.38–2.07 and 1.05–1.623 (p = 0.001), respectively. ^ Conclusion. This study revealed seven regions of excess mortality of liver cancer mortality across the U.S. and four regions of excess mortality in Texas between 1980–2003, as well as demonstrated a correlation between elevated liver cancer mortality rates and reporting of alcohol dependence among Hispanics and Other populations. ^

Racial disparities in CD4 counts at initial HIV-1 diagnosis: Analysis of the Adult Spectrum of HIV disease dataset and public health implications

Introduction. The HIV/AIDS disease burden disproportionately affects minority populations, specifically African Americans. While sexual risk behaviors play a role in the observed HIV burden, other factors including gender, age, socioeconomics, and barriers to healthcare access may also be contributory. The goal of this study was to determine how far down the HIV/AIDS disease process people of different ethnicities first present for healthcare. The study specifically analyzed the differences in CD4 cell counts at the initial HIV-1 diagnosis with respect to ethnicity. The study also analyzed racial differences in HIV/AIDS risk factors. ^ Methods. This is a retrospective study using data from the Adult Spectrum of HIV Disease (ASD), collected by the City of Houston Department of Health. The ASD database contains information on newly reported HIV cases in the Harris County District Hospitals between 1989 and 2000. Each patient had an initial and a follow-up report. The extracted variables of interest from the ASD data set were CD4 counts at the initial HIV diagnosis, race, gender, age at HIV diagnosis and behavioral risk factors. One-way ANOVA was used to examine differences in baseline CD4 counts at HIV diagnosis between racial/ethnic groups. Chi square was used to analyze racial differences in risk factors. ^ Results. The analyzed study sample was 4767. The study population was 47% Black, 37% White and 16% Hispanic [p<0.05]. The mean and median CD4 counts at diagnosis were 254 and 193 cells per ml, respectively. At the initial HIV diagnosis Blacks had the highest average CD4 counts (285), followed by Whites (233) and Hispanics (212) [p<0.001 ]. These statistical differences, however, were only observed with CD4 counts above 350 [p<0.001], even when adjusted for age at diagnosis and gender [p<0.05]. Looking at risk factors, Blacks were mostly affected by intravenous drug use (IVDU) and heterosexuality, whereas Whites and Hispanics were more affected by male homosexuality [ p<0.05]. ^ Conclusion. (1) There were statistical differences in CD4 counts with respect to ethnicity, but these differences only existed for CD4 counts above 350. These differences however do not appear to have clinical significance. Antithetically, Blacks had the highest CD4 counts followed by Whites and Hispanics. (2) 50% of this study group clinically had AIDS at their initial HIV diagnosis (median=193), irrespective of ethnicity. It was not clear from data analysis if these observations were due to failure of early HIV surveillance, HIV testing policies or healthcare access. More studies need to be done to address this question. (3) Homosexuality and bisexuality were the biggest risk factors for Whites and Hispanics, whereas for Blacks were mostly affected by heterosexuality and IVDU, implying a need for different public health intervention strategies for these racial groups. ^

A retrospective analysis of patients referred for tuberculosis testing at Parkland Hospital, Dallas, TX

Tuberculosis (TB) is an infectious disease of great public health importance, particularly to institutions that provide health care to large numbers of TB patients such as Parkland Hospital in Dallas, TX. The purpose of this retrospective chart review was to analyze differences in TB positive and TB negative patients to better understand whether or not there were variables that could be utilized to develop a predictive model for use in the emergency department to reduce the overall number of suspected TB patients being sent to respiratory isolation for TB testing. This study included patients who presented to the Parkland Hospital emergency department between November 2006 and December 2007 and were isolated and tested for TB. Outcome of TB was defined as a positive sputum AFB test or a positive M. tuberculosis culture result. Data were collected utilizing the UT Southwestern Medical Center computerized database OACIS and included demographic information, TB risk factors, physical symptoms, and clinical results. Only two variables were significantly (P<0.05) related to TB outcome: dyspnea (shortness of breath) (P<0.001) and abnormal x-ray (P<0.001). Marginally significant variables included hemoptysis (P=0.06), weight loss (P=0.11), night sweats (P=0.20), history of homelessness or incarceration (P=0.15), and history of positive skin PPD (P=0.19). Using a combination of significant and marginally significant variables, a predictive model was designed which demonstrated a specificity of 24% and a sensitivity of 70%. In conclusion, a predictive model for TB outcome based on patients who presented to the Parkland Hospital emergency department between November 2006 and December 2007 was unsuccessful given the limited number of variables that differed significantly between TB positive and TB negative patients. It is suggested that a future prospective cohort study should be implemented to collect data on TB positive and TB negative patients. It may be possible that a more thorough prospective collection of data may lead to clearer comparisons between TB positive and TB negative patients and ultimately to the design of a more sensitive predictive model for TB outcome. ^

A path analysis of an after-school health and exercise program for elementary school children in El Paso, Texas

As schools are pressured to perform on academics and standardized examinations, schools are reluctant to dedicate increased time to physical activity. After-school exercise and health programs may provide an opportunity to engage in more physical activity without taking time away from coursework during the day. The current study is a secondary data analysis of data from a randomized trial of a 10-week after-school program (six schools, n = 903) that implemented an exercise component based on the CATCH physical activity component and health modules based on the culturally-tailored Bienestar health education program. Outcome variables included BMI and aerobic capacity, health knowledge and healthy food intentions as assessed through path analysis techniques. Both the baseline model (χ2 (df = 8) = 16.90, p = .031; RMSEA = .035 (90% CI of .010–.058), NNFI = 0.983 and the CFI = 0.995) and the model incorporating intervention participation proved to be a good fit to the data (χ2 (df = 10) = 11.59, p = .314. RMSEA = .013 (90% CI of .010–.039); NNFI = 0.996 and CFI = 0.999). Experimental group participation was not predictive of changes in health knowledge, intentions to eat healthy foods or changes in Body Mass Index, but it was associated with increased aerobic capacity, β = .067, p < .05. School characteristics including SES and Language proficiency proved to be significantly associated with changes in knowledge and physical indicators. Further effects of school level variables on intervention outcomes are recommended so that tailored interventions can be developed aimed at the specific characteristics of each participating school. ^

Secondary data analysis of lead screening compliance in high-risk children

Introduction. Despite the ban of lead-containing gasoline and paint, childhood lead poisoning remains a public health issue. Furthermore, a Medicaid-eligible child is 8 times more likely to have an elevated blood lead level (EBLL) than a non-Medicaid child, which is the primary reason for the early detection lead screening mandate for ages 12 and 24 months among the Medicaid population. Based on field observations, there was evidence that suggested a screening compliance issue. Objective. The purpose of this study was to analyze blood lead screening compliance in previously lead poisoned Medicaid children and test for an association between timely lead screening and timely childhood immunizations. The mean months between follow-up tests were also examined for a significant difference between the non-compliant and compliant lead screened children. Methods. Access to the surveillance data of all childhood lead poisoned cases in Bexar County was granted by the San Antonio Metropolitan Health District. A database was constructed and analyzed using descriptive statistics, logistic regression methods and non-parametric tests. Lead screening at 12 months of age was analyzed separately from lead screening at 24 months. The small portion of the population who were also related were included in one analysis and removed from a second analysis to check for significance. Gender, ethnicity, age of home, and having a sibling with an EBLL were ruled out as confounders for the association tests but ethnicity and age of home were adjusted in the nonparametric tests. Results. There was a strong significant association between lead screening compliance at 12 months and childhood immunization compliance, with or without including related children (p<0.00). However, there was no significant association between the two variables at the age of 24 months. Furthermore, there was no significant difference between the median of the mean months of follow-up blood tests among the non-compliant and compliant lead screened population for at the 12 month screening group but there was a significant difference at the 24 month screening group (p<0.01). Discussion. Descriptive statistics showed that 61% and 56% of the previously lead poisoned Medicaid population did not receive their 12 and 24 month mandated lead screening on time, respectively. This suggests that their elevated blood lead level may have been diagnosed earlier in their childhood. Furthermore, a child who is compliant with their lead screening at 12 months of age is 2.36 times more likely to also receive their childhood immunizations on time compared to a child who was not compliant with their 12 month screening. Even though there was no statistical significant association found for the 24 month group, the public health significance of a screening compliance issue is no less important. The Texas Medicaid program needs to enforce lead screening compliance because it is evident that there has been no monitoring system in place. Further recommendations include a need for an increased focus on parental education and the importance of taking their children for wellness exams on time.^

Demographic analysis of Certified Industrial Hygienists (CIH) with the use of survival analysis techniques

Objective. The goal of this study is to characterize the current workforce of CIHs, the lengths of professional practice careers of the past and current CIHs.^ Methods. This is a secondary data analysis of data compiled from all of the nearly 50 annual roster listings of the American Board of Industrial Hygiene (ABIH) for Certified Industrial Hygienists active in each year since 1960. Survival analysis was performed as a technique to measure the primary outcome of interest. The technique which was involved in this study was the Kaplan-Meier method for estimating the survival function.^ Study subjects: The population to be studied is all Certified Industrial Hygienists (CIHs). A CIH is defined by the ABIH as an individual who has achieved the minimum requirements for education, working experience and through examination, has demonstrated a minimum level of knowledge and competency in the prevention of occupational illnesses. ^ Results. A Cox-proportional hazards model analysis was performed by different start-time cohorts of CIHs. In this model we chose cohort 1 as the reference cohort. The estimated relative risk of the event (defined as retirement, or absent from 5 consecutive years of listing) occurred for CIHs for cohorts 2,3,4,5 relative to cohort 1 is 0.385, 0.214, 0.234, 0.299 relatively. The result show that cohort 2 (CIHs issued from 1970-1980) has the lowest hazard ratio which indicates the lowest retirement rate.^ Conclusion. The manpower of CIHs (still actively practicing up to the end of 2009) increased tremendously starting in 1980 and grew into a plateau in recent decades. This indicates that the supply and demand of the profession may have reached equilibrium. More demographic information and variables are needed to actually predict the future number of CIHs needed. ^

A descriptive and exploratory analysis of occupational injuries at a chemical manufacturing facility

A retrospective study of 1353 occupational injuries occurring at a chemical manufacturing facility in Houston, Texas from January, 1982 through May, 1988 was performed to investigate the etiology of the occupational injury process. Injury incidence rates were calculated for various sub-populations of workers to determine differences in the risk of injury for various groups. Linear modeling techniques were used to determine the association between certain collected independent variables and severity of an injury event. Finally, two sub-groups of the worker population, shiftworkers and injury recidivists, were examined. An injury recidivist as defined is any worker experiencing one or more injury per year. Overall, female shiftworkers evidenced the highest average injury incidence rate compared to all other worker groups analyzed. Although the female shiftworkers were younger and less experienced, the etiology of their increased risk of injury remains unclear, although the rigors of performing shiftwork itself or ergonomic factors are suspect. In general, females were injured more frequently than males, but they did not incur more severe injuries. For all workers, many injuries were caused by erroneous or foregone training, and risk taking behaviors. Injuries of these types are avoidable. The distribution of injuries by severity level was bimodal; either injuries were of minor or major severity with only a small number of cases falling in between. Of the variables collected, only the type of injury incurred and the worker's titlecode were statistically significantly associated with injury severity. Shiftworkers did not sustain more severe injuries than other worker groups. Injury to shiftworkers varied as a 24-hour pattern; the greatest number occurred between 1200-1230 hours, (p = 0.002) by Cosinor analysis. Recidivists made up 3.3% of the population (23 males and 10 females), yet suffered 17.8% of the injuries. Although past research suggests that injury recidivism is a random statistical event, analysis of the data by logistic regression implicates gender, area worked, age and job titlecode as being statistically significantly related to injury recidivism at this facility. ^

ECONOMIC ANALYSIS OF THE DEMAND FOR PRESCRIPTION MEDICINE IN THE UNITED STATES

The purpose of this study was to understand the role of principle economic, sociodemographic and health status factors in determining the likelihood and volume of prescription drug use. Econometric demand regression models were developed for this purpose. Ten explanatory variables were examined: family income, coinsurance rate, age, sex, race, household head education level, size of family, health status, number of medical visits, and type of provider seen during medical visits. The economic factors (family income and coinsurance) were given special emphasis in this study.^ The National Medical Care Utilization and Expenditure Survey (NMCUES) was the data source. The sample represented the civilian, noninstitutionalized residents of the United States in 1980. The sample method used in the survey was a stratified four-stage, area probability design. The sample was comprised of 6,600 households (17,123 individuals). The weighted sample provided the population estimates used in the analysis. Five repeated interviews were conducted with each household. The household survey provided detailed information on the United States health status, pattern of health care utilization, charges for services received, and methods of payments for 1980.^ The study provided evidence that economic factors influenced the use of prescription drugs, but the use was not highly responsive to family income and coinsurance for the levels examined. The elasticities for family income ranged from -.0002 to -.013 and coinsurance ranged from -.174 to -.108. Income has a greater influence on the likelihood of prescription drug use, and coinsurance rates had an impact on the amount spent on prescription drugs. The coinsurance effect was not examined for the likelihood of drug use due to limitations in the measurement of coinsurance. Health status appeared to overwhelm any effects which may be attributed to family income or coinsurance. The likelihood of prescription drug use was highly dependent on visits to medical providers. The volume of prescription drug use was highly dependent on the health status, age, and whether or not the individual saw a general practitioner. ^

THE USE OF MULTIVARIATE ANALYSIS OF COVARIANCE IN EVALUATING THE COMPARABILITY OF LABORATORY DETERMINATIONS IN COOPERATIVE STUDIES

The role of clinical chemistry has traditionally been to evaluate acutely ill or hospitalized patients. Traditional statistical methods have serious drawbacks in that they use univariate techniques. To demonstrate alternative methodology, a multivariate analysis of covariance model was developed and applied to the data from the Cooperative Study of Sickle Cell Disease.^ The purpose of developing the model for the laboratory data from the CSSCD was to evaluate the comparability of the results from the different clinics. Several variables were incorporated into the model in order to control for possible differences among the clinics that might confound any real laboratory differences.^ Differences for LDH, alkaline phosphatase and SGOT were identified which will necessitate adjustments by clinic whenever these data are used. In addition, aberrant clinic values for LDH, creatinine and BUN were also identified.^ The use of any statistical technique including multivariate analysis without thoughtful consideration may lead to spurious conclusions that may not be corrected for some time, if ever. However, the advantages of multivariate analysis far outweigh its potential problems. If its use increases as it should, the applicability to the analysis of laboratory data in prospective patient monitoring, quality control programs, and interpretation of data from cooperative studies could well have a major impact on the health and well being of a large number of individuals. ^