Logistic regression models for ordinal response: A study of self-efficacy in colorectal cancer screening

The ordinal logistic regression models are used to analyze the dependant variable with multiple outcomes that can be ranked, but have been underutilized. In this study, we describe four logistic regression models for analyzing the ordinal response variable. ^ In this methodological study, the four regression models are proposed. The first model uses the multinomial logistic model. The second is adjacent-category logit model. The third is the proportional odds model and the fourth model is the continuation-ratio model. We illustrate and compare the fit of these models using data from the survey designed by the University of Texas, School of Public Health research project PCCaSO (Promoting Colon Cancer Screening in people 50 and Over), to study the patient’s confidence in the completion colorectal cancer screening (CRCS). ^ The purpose of this study is two fold: first, to provide a synthesized review of models for analyzing data with ordinal response, and second, to evaluate their usefulness in epidemiological research, with particular emphasis on model formulation, interpretation of model coefficients, and their implications. Four ordinal logistic models that are used in this study include (1) Multinomial logistic model, (2) Adjacent-category logistic model [9], (3) Continuation-ratio logistic model [10], (4) Proportional logistic model [11]. We recommend that the analyst performs (1) goodness-of-fit tests, (2) sensitivity analysis by fitting and comparing different models.^

Social support, health status and health services utilization among the noninstitutionalized elderly: An analysis of the Supplement on Aging to the 1984 national health interview survey

The association between Social Support, Health Status, and Health Services Utilization of the elderly, was explored based on the analysis of data from the Supplement on Aging to the National Health Interview Survey, 1984 (N = 11,497) using a modified framework of Aday and Andersen's Expanded Behavioral Model. The results suggested that Social Support as operationalized in this study was an independent determinant of the use of health services. The quantity of social activities and the use of community services were the two most consistent determinants across different types of health services use.^ The effects of social support on the use of health services were broken down into three components to facilitate explanations of the mechanisms through which social support operated. The Predisposing and Enabling component of Social Support had independent, although not uniform, effects on the use of health services. Only slight substitute effects of social support were detected. These included the substitution of the use of senior centers for longer stay in the hospital and the substitution of help with IADL problems for the use of formal home care services.^ The effect of financial support on the use of health services was found to be different for middle and low income populations. This differential effect was also found for the presence of intimate networks, the frequencies of interaction with children and the perceived availability of support among urban/rural, male/female and white/non-white subgroups.^ The study also suggested that the selection of appropriate Health Status measures should be based on the type of Health Services Utilization in which a researcher is interested. The level of physical function limitation and role activity limitation were the two most consistent predictors of the volume of physician visits, number of hospital days, and average length of stay in the hospital during the past year.^ Some alternative hypotheses were also raised and evaluated, when possible. The impacts of the complex sample design, the reliability and validity of the measures and other limitations of this analysis were also discussed. Finally, a revised framework was proposed and discussed based on the analysis. Some policy implications and suggestions for future study were also presented. ^

Bayesian inference and its application to meta-analysis of epidemiologic data

In Part One, the foundations of Bayesian inference are reviewed, and the technicalities of the Bayesian method are illustrated. Part Two applies the Bayesian meta-analysis program, the Confidence Profile Method (CPM), to clinical trial data and evaluates the merits of using Bayesian meta-analysis for overviews of clinical trials.^ The Bayesian method of meta-analysis produced similar results to the classical results because of the large sample size, along with the input of a non-preferential prior probability distribution. These results were anticipated through explanations in Part One of the mechanics of the Bayesian approach. ^

INFANT MORTALITY IN THE MEXICAN AMERICAN COMMUNITY: AN ANALYSIS OF DIFFERENTIALS IN INFANT, NEONATAL, AND POSTNEONATAL MORTALITY BY ETHNICITY AND PARENTAL NATIVITY, 1974-75 SINGLE LIVE BIRTH COHORT, HARRIS COUNTY, TEXAS

The paradoxically low infant mortality rates for Mexican Americans in Texas have been attributed to inaccuracies in vital registration and idiosyncracies in Mexican migration in rural areas along the U.S.-Mexico border. This study examined infant (IMR), neonatal (NMR), and postneonatal (PNMR) mortality rates of Mexican Americans in an urban, non-border setting, using linked birth and death records of the 1974-75 single live birth cohort (N = 68,584) in Harris County, Texas, which includes the city of Houston and is reported to have nearly complete birth and death registration. The use of parental nativity with the traditional Spanish surname criterion made it possible to distinguish infants of Mexican-born immigrants from those of Blacks, Anglos, other Hispanics, and later-generation, more Anglicized Mexican Americans. Mortality rates were analyzed by ethnicity, parental nativity, and cause of death, with respect to birth weight, birth order, maternal age, legitimacy status, and time of first prenatal care.^ While overall IMRs showed Spanish surname rates slightly higher than Anglo rates, infants of Mexican-born immigrants had much lower NMRs than did Anglos, even for moderately low birth weight infants. However, among infants under 1500 grams, presumably unable to be discharged home in the neonatal period, Mexican Americans had the highest NMR. The inconsistency suggested unreported deaths for Mexican American low birth weight infants after hospital discharge. The PNMR of infants of Mexican immigrants was also lower than for Anglos, and the usual mortality differentials were reversed: high-risk categories of high birth order, high maternal age, and late/no prenatal care had the lowest PNMRs. Since these groups' characteristics are congruent with those of low-income migrants, the data suggested the possibility of migration losses. Cause of death analysis suggested that prematurity and birth injuries are greater problems than heretofore recognized among Mexican Americans, and that home births and "shoebox burials" may be unrecorded even in an urban setting.^ Caution is advised in the interpretation of infant mortality rates for a Spanish surname population of Mexican origin, even in an urban, non-border area with reportedly excellent birth and death registration. ^

THE IMPLEMENTATION OF FEDERAL FAMILY PLANNING POLICY: AN ANALYSIS OF FACTORS AFFECTING STATE EXPENDITURES, FISCAL YEARS 1976-1981 (WOMEN, BUDGET, POPULATION)

The purpose of this study was to analyze the implementation of national family planning policy in the United States, which was embedded in four separate statutes during the period of study, Fiscal Years 1976-81. The design of the study utilized a modification of the Sabatier and Mazmanian framework for policy analysis, which defined implementation as the carrying out of statutory policy. The study was divided into two phases. The first part of the study compared the implementation of family planning policy by each of the pertinent statutes. The second part of the study identified factors that were associated with implementation of federal family planning policy within the context of block grants.^ Implemention was measured here by federal dollars spent for family planning, adjusted for the size of the respective state target populations. Expenditure data were collected from the Alan Guttmacher Institute and from each of the federal agencies having administrative authority for the four pertinent statutes, respectively. Data from the former were used for most of the analysis because they were more complete and more reliable.^ The first phase of the study tested the hypothesis that the coherence of a statute is directly related to effective implementation. Equity in the distribution of funds to the states was used to operationalize effective implementation. To a large extent, the results of the analysis supported the hypothesis. In addition to their theoretical significance, these findings were also significant for policymakers insofar they demonstrated the effectiveness of categorical legislation in implementing desired health policy.^ Given the current and historically intermittent emphasis on more state and less federal decision-making in health and human serives, the second phase of the study focused on state level factors that were associated with expenditures of social service block grant funds for family planning. Using the Sabatier-Mazmanian implementation model as a framework, many factors were tested. Those factors showing the strongest conceptual and statistical relationship to the dependent variable were used to construct a statistical model. Using multivariable regression analysis, this model was applied cross-sectionally to each of the years of the study. The most striking finding here was that the dominant determinants of the state spending varied for each year of the study (Fiscal Years 1976-1981). The significance of these results was that they provided empirical support of current implementation theory, showing that the dominant determinants of implementation vary greatly over time. ^

A comparative analysis of Texas and Louisiana Oil-field NORM Waste Policy

NORM (Naturally Occurring Radioactive Material) Waste Policies for the nation's oil and gas producing states have been in existence since the 1980's, when Louisiana was the first state to develop a NORM regulatory program in 1989. Since that time, expectations for NORM Waste Policies have evolved, as Health, Safety, Environment, and Social responsibility (HSE & SR) grows increasingly important to the public. Therefore, the oil and gas industry's safety and environmental performance record will face challenges in the future, about its best practices for managing the co-production of NORM wastes. ^ Within the United States, NORM is not federally regulated. The U.S. EPA claims it regulates NORM under CERCLA (superfund) and the Clean Water Act. Though, there are no universally applicable regulations for radium-based NORM waste. Therefore, individual states have taken responsibility for developing NORM regulatory programs, because of the potential radiological risk it can pose to man (bone and lung cancer) and his environment. This has led to inconsistencies in NORM Waste Policies as well as a NORM management gap in both state and federal regulatory structures. ^ Fourteen different NORM regulations and guidelines were compared between Louisiana and Texas, the nation's top two petroleum producing states. Louisiana is the country's top crude oil producer when production from its Federal offshore waters are included, and fourth in crude oil production, behind Texas, Alaska, and California when Federal offshore areas are excluded. Louisiana produces more petroleum products than any state but Texas. For these reasons, a comparative analysis between Louisiana and Texas was undertaken to identify differences in their NORM regulations and guidelines for managing, handling and disposing NORM wastes. Moreover, this analysis was undertaken because Texas is the most explored and drilled worldwide and yet appears to lag behind its neighboring state in terms of its NORM Waste Policy and developing an industry standard for handling, managing and disposing NORM. As a result of this analysis, fourteen recommendations were identified.^

DEVELOPMENT OF NOVEL METHODS TO MINIMIZE THE IMPACT OF SEQUENCING ERRORS IN THE NEXT-GENERATION SEQUENCING DATA ANALYSIS

Next-generation sequencing (NGS) technology has become a prominent tool in biological and biomedical research. However, NGS data analysis, such as de novo assembly, mapping and variants detection is far from maturity, and the high sequencing error-rate is one of the major problems. . To minimize the impact of sequencing errors, we developed a highly robust and efficient method, MTM, to correct the errors in NGS reads. We demonstrated the effectiveness of MTM on both single-cell data with highly non-uniform coverage and normal data with uniformly high coverage, reflecting that MTM’s performance does not rely on the coverage of the sequencing reads. MTM was also compared with Hammer and Quake, the best methods for correcting non-uniform and uniform data respectively. For non-uniform data, MTM outperformed both Hammer and Quake. For uniform data, MTM showed better performance than Quake and comparable results to Hammer. By making better error correction with MTM, the quality of downstream analysis, such as mapping and SNP detection, was improved. SNP calling is a major application of NGS technologies. However, the existence of sequencing errors complicates this process, especially for the low coverage (

An analysis of the revenue policy -making process of the Texas Legislature

The purpose of this dissertation was to develop a conceptual framework which can be used to account for policy decisions made by the House Ways and Means Committee (HW&MC) of the Texas House of Representatives. This analysis will examine the actions of the committee over a ten-year period with the goal of explaining and predicting the success of failure of certain efforts to raise revenue.^ The basis framework for modelling the revenue decision-making process includes three major components--the decision alternatives, the external factors and two competing contingency theories. The decision alternatives encompass the particular options available to increase tax revenue. The options were classified as non-innovative or innovative. The non-innovative options included the sales, franchise, property and severance taxes. The innovative options were principally the personal and corporate income taxes.^ The external factors included political and economic constraints that affected the actions of the HW&MC. Several key political constraints on committee decision-making were addressed--including public attitudes, interest groups, political party strength and tradition and precedents. The economic constraints that affected revenue decisions included court mandates, federal mandates and the fiscal condition of the nation and the state.^ The third component of the revenue decision-making framework included two alternative contingency theories. The first alternative theory postulated that the committee structure, including the individual member roles and the overall committee style, resulted in distinctive revenue decisions. This theory will be favored if evidence points to the committee acting autonomously with less concern for the policies of the Speaker of the House. The Speaker assignment theory, postulated that the assignment of committee members shaped or changed the course of committee decision-making. This theory will be favored if there was evidence that the committee was strictly a vehicle for the Speaker to institute his preferred tax policies.^ The ultimate goal of this analysis is to develop an explanation for legislative decision-making about tax policy. This explanation will be based on the linkages across various tax options, political and economic constraints, member roles and committee style and the patterns of committee assignment. ^