Using Blackboard Administered Precourse and Post course Tests to Assess Student Readiness to Learn and Change in Knowledge

Students arrive at classes with a varying social situations and course subject knowledge. Blackboard is a web based course delivery program that permits testing of students before arriving at the first class. A pretest was used to assess preexisting subject knowledge(S) and a survey was used to assess non-subject (N) factors that might impact the student’s final grade. A posttest was administered after all content was delivered and used to access change in S. [See PDF for complete abstract]

Nonlinear tests for genetic studies of complex disease

Linkage and association studies are major analytical tools to search for susceptibility genes for complex diseases. With the availability of large collection of single nucleotide polymorphisms (SNPs) and the rapid progresses for high throughput genotyping technologies, together with the ambitious goals of the International HapMap Project, genetic markers covering the whole genome will be available for genome-wide linkage and association studies. In order not to inflate the type I error rate in performing genome-wide linkage and association studies, multiple adjustment for the significant level for each independent linkage and/or association test is required, and this has led to the suggestion of genome-wide significant cut-off as low as 5 × 10 −7. Almost no linkage and/or association study can meet such a stringent threshold by the standard statistical methods. Developing new statistics with high power is urgently needed to tackle this problem. This dissertation proposes and explores a class of novel test statistics that can be used in both population-based and family-based genetic data by employing a completely new strategy, which uses nonlinear transformation of the sample means to construct test statistics for linkage and association studies. Extensive simulation studies are used to illustrate the properties of the nonlinear test statistics. Power calculations are performed using both analytical and empirical methods. Finally, real data sets are analyzed with the nonlinear test statistics. Results show that the nonlinear test statistics have correct type I error rates, and most of the studied nonlinear test statistics have higher power than the standard chi-square test. This dissertation introduces a new idea to design novel test statistics with high power and might open new ways to mapping susceptibility genes for complex diseases. ^

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. ^

Determinants of CD4 cell count decline after treatment interruption

Patients who had started HAART (Highly Active Anti-Retroviral Treatment) under previous aggressive DHHS guidelines (1997) underwent a life-long continuous HAART that was associated with many short term as well as long term complications. Many interventions attempted to reduce those complications including intermittent treatment also called pulse therapy. Many studies were done to study the determinants of rate of fall in CD4 count after interruption as this data would help guide treatment interruptions. The data set used here was a part of a cohort study taking place at the Johns Hopkins AIDS service since January 1984, in which the data were collected both prospectively and retrospectively. The patients in this data set consisted of 47 patients receiving via pulse therapy with the aim of reducing the long-term complications. ^ The aim of this project was to study the impact of virologic and immunologic factors on the rate of CD4 loss after treatment interruption. The exposure variables under investigation included CD4 cell count and viral load at treatment initiation. The rates of change of CD4 cell count after treatment interruption was estimated from observed data using advanced longitudinal data analysis methods (i.e., linear mixed model). Using random effects accounted for repeated measures of CD4 per person after treatment interruption. The regression coefficient estimates from the model was then used to produce subject specific rates of CD4 change accounting for group trends in change. The exposure variables of interest were age, race, and gender, CD4 cell counts and HIV RNA levels at HAART initiation. ^ The rate of fall of CD4 count did not depend on CD4 cell count or viral load at initiation of treatment. Thus these factors may not be used to determine who can have a chance of successful treatment interruption. CD4 and viral load were again studied by t-tests and ANOVA test after grouping based on medians and quartiles to see any difference in means of rate of CD4 fall after interruption. There was no significant difference between the groups suggesting that there was no association between rate of fall of CD4 after treatment interruption and above mentioned exposure variables. ^

A SIMULATION STUDY OF THE SIZE AND POWER OF SOME TWO-SAMPLE TESTS FOR UNEQUALLY CENSORED SURVIVAL DATA (RANK TESTS, LOGRANK, PROPORTIONAL HAZARDS, WILCOXON TESTS, EXPONENTIAL DISTRIBUTION)

Sizes and power of selected two-sample tests of the equality of survival distributions are compared by simulation for small samples from unequally, randomly-censored exponential distributions. The tests investigated include parametric tests (F, Score, Likelihood, Asymptotic), logrank tests (Mantel, Peto-Peto), and Wilcoxon-Type tests (Gehan, Prentice). Equal sized samples, n = 18, 16, 32 with 1000 (size) and 500 (power) simulation trials, are compared for 16 combinations of the censoring proportions 0%, 20%, 40%, and 60%. For n = 8 and 16, the Asymptotic, Peto-Peto, and Wilcoxon tests perform at nominal 5% size expectations, but the F, Score and Mantel tests exceeded 5% size confidence limits for 1/3 of the censoring combinations. For n = 32, all tests showed proper size, with the Peto-Peto test most conservative in the presence of unequal censoring. Powers of all tests are compared for exponential hazard ratios of 1.4 and 2.0. There is little difference in power characteristics of the tests within the classes of tests considered. The Mantel test showed 90% to 95% power efficiency relative to parametric tests. Wilcoxon-type tests have the lowest relative power but are robust to differential censoring patterns. A modified Peto-Peto test shows power comparable to the Mantel test. For n = 32, a specific Weibull-exponential comparison of crossing survival curves suggests that the relative powers of logrank and Wilcoxon-type tests are dependent on the scale parameter of the Weibull distribution. Wilcoxon-type tests appear more powerful than logrank tests in the case of late-crossing and less powerful for early-crossing survival curves. Guidelines for the appropriate selection of two-sample tests are given. ^

Immunologic characteristics of immunogenic variants generated by {\it in vitro\/} treatment of a methylcholanthrene-induced murine fibrosarcoma MCA-F with 1 methyl-3-nitro-1-nitrosoguanidine, 5 -aza-2$\sp\prime$-deoxycytidine, or ultraviolet radiation

This study addresses the questions of whether the frequency of generation and in vivo cross-reactivity of highly immunogenic tumor clones induced in a single parental murine fibrosarcoma cell line MCA-F is more closely related to the agent used to induce the Imm$\sp{+}$ clone or whether these characteristics are independent of the agents used. These questions were addressed by treating the parental tumor cell line MCA-F with UV-B radiation (UV-B), 1-methyl-3-nitro-1-nitrosoguanidine (MNNG), or 5-aza-2$\sp\prime$-deoxycytidine (5-azaCdR). The frequency of Imm$\sp{+}$ variant generation was similarly high for the three different agents, suggesting that the frequency of Imm$\sp{+}$ generation was related more closely to the cell line than to the inducing agent used. Cross-reactivity was tested with two Imm$\sp{+}$ clones from each treatment group in a modified immunoprotection assay that selectively engendered antivariant, but not antiparental immunity. Under these conditions each clone, except one, immunized against itself. The MNNG-induced clones engendered stronger antivariant immunity but a weaker variant cross-reactive immunity could also be detected.^ This study also characterized the lymphocyte populations responsible for antivariant and antiparental immunity in vivo. Using the local adoptive transfer assay (LATA) and antibody plus complement depletion of T-cell subsets, we showed that immunity induced by the Imm$\sp{+}$ variants against the parent MCA-F was transferred by the Thy1.2$\sp{+}$, L3T4a$\sp{+}$, Lyt2.1$\sp{-}$ (CD4$\sp{+}$) population, without an apparent contribution by Thy1.2$\sp{+}$, L3T4a$\sp{-}$, Lyt2.1$\sp{+}$ (CD8$\sp{+}$) cells. A role for Lyt2.1$\sp{+}$T lymphocytes in antivariant, but not antiparent immunity was supported by the results of LATA and CTL assays. Immunization with low numbers of viable Imm$\sp{+}$ cells, or with high numbers of non viable Imm$\sp{+}$ cells engendered only antivariant immunity without parental cross-protection. The associative recognition of parental antigens and variant neoantigens resulting in strong antiparent immunity was investigated using somatic cells hybrids of Imm$\sp{+}$ variants of MCA-F and an antigenically distinct tumor MCA-D. An unexpected result of these latter experiments was the expression of a unique tumor-specific antigen by the hybrid cells. These studies demonstrate that the parental tumor-specific antigen and the variant neoantigen must be coexpressed on the cell surface to engender parental cross-protective immunity. (Abstract shortened with permission of author.) ^

False -positives and false-negatives in tests for trend

False-positive and false-negative values were calculated for five different designs of the trend test and it was demonstrated that a design suggested by Portier and Hoel in 1984 for a different problem produced the lowest false-positive and false-negative rates when applied to historical spontaneous tumor rate data for Fischer Rats. ^