An examination of the Gonorrhea Cases & Places Study: An analysis of the Theory of Gender and Power, Situational/Environmental Variables Theory, and Sexual Script Theory as it relates to risky sexual behavior in African American adults

Objective. The purpose of the study is to provide a holistic depiction of behavioral & environmental factors contributing to risky sexual behaviors among predominantly high school educated, low-income African Americans residing in urban areas of Houston, TX utilizing the Theory of Gender and Power, Situational/Environmental Variables Theory, and Sexual Script Theory. Methods. A cross-sectional study was conducted via questionnaires among 215 Houston area residents, 149 were women and 66 were male. Measures used to assess behaviors of the population included a history of homelessness, use of crack/cocaine among several other illicit drugs, the type of sexual partner, age of participant, age of most recent sex partner, whether or not participants sought health care in the last 12 months, knowledge of partner's other sexual activities, symptoms of depression, and places where partner's were met. In an effort to determine risk of sexual encounters, a risk index employing the variables used to assess condom use was created categorizing sexual encounters as unsafe or safe. Results. Variables meeting the significance level of p<.15 for the bivariate analysis of each theory were entered into a binary logistic regression analysis. The block for each theory was significant, suggesting that the grouping assignments of each variable by theory were significantly associated with unsafe sexual behaviors. Within the regression analysis, variables such as sex for drugs/money, low income, and crack use demonstrated an effect size of ≥ ± 1, indicating that these variables had a significant effect on unsafe sexual behavioral practices. Conclusions. Variables assessing behavior and environment demonstrated a significant effect when categorized by relation to designated theories.

Development of a Bayesian Joint Logistic Model to Better Study the Association between Haplotypes and Disease

In 2011, there will be an estimated 1,596,670 new cancer cases and 571,950 cancer-related deaths in the US. With the ever-increasing applications of cancer genetics in epidemiology, there is great potential to identify genetic risk factors that would help identify individuals with increased genetic susceptibility to cancer, which could be used to develop interventions or targeted therapies that could hopefully reduce cancer risk and mortality. In this dissertation, I propose to develop a new statistical method to evaluate the role of haplotypes in cancer susceptibility and development. This model will be flexible enough to handle not only haplotypes of any size, but also a variety of covariates. I will then apply this method to three cancer-related data sets (Hodgkin Disease, Glioma, and Lung Cancer). I hypothesize that there is substantial improvement in the estimation of association between haplotypes and disease, with the use of a Bayesian mathematical method to infer haplotypes that uses prior information from known genetics sources. Analysis based on haplotypes using information from publically available genetic sources generally show increased odds ratios and smaller p-values in both the Hodgkin, Glioma, and Lung data sets. For instance, the Bayesian Joint Logistic Model (BJLM) inferred haplotype TC had a substantially higher estimated effect size (OR=12.16, 95% CI = 2.47-90.1 vs. 9.24, 95% CI = 1.81-47.2) and more significant p-value (0.00044 vs. 0.008) for Hodgkin Disease compared to a traditional logistic regression approach. Also, the effect sizes of haplotypes modeled with recessive genetic effects were higher (and had more significant p-values) when analyzed with the BJLM. Full genetic models with haplotype information developed with the BJLM resulted in significantly higher discriminatory power and a significantly higher Net Reclassification Index compared to those developed with haplo.stats for lung cancer. Future analysis for this work could be to incorporate the 1000 Genomes project, which offers a larger selection of SNPs can be incorporated into the information from known genetic sources as well. Other future analysis include testing non-binary outcomes, like the levels of biomarkers that are present in lung cancer (NNK), and extending this analysis to full GWAS studies.

Cost and power analysis of linkage disequilibrium methods for locating genes influencing quantitative traits in humans

Linkage disequilibrium methods can be used to find genes influencing quantitative trait variation in humans. Linkage disequilibrium methods can require smaller sample sizes than linkage equilibrium methods, such as the variance component approach to find loci with a specific effect size. The increase in power is at the expense of requiring more markers to be typed to scan the entire genome. This thesis compares different linkage disequilibrium methods to determine which factors influence the power to detect disequilibrium. The costs of disequilibrium and equilibrium tests were compared to determine whether the savings in phenotyping costs when using disequilibrium methods outweigh the additional genotyping costs.^ Nine linkage disequilibrium tests were examined by simulation. Five tests involve selecting isolated unrelated individuals while four involved the selection of parent child trios (TDT). All nine tests were found to be able to identify disequilibrium with the correct significance level in Hardy-Weinberg populations. Increasing linked genetic variance and trait allele frequency were found to increase the power to detect disequilibrium, while increasing the number of generations and distance between marker and trait loci decreased the power to detect disequilibrium. Discordant sampling was used for several of the tests. It was found that the more stringent the sampling, the greater the power to detect disequilibrium in a sample of given size. The power to detect disequilibrium was not affected by the presence of polygenic effects.^ When the trait locus had more than two trait alleles, the power of the tests maximized to less than one. For the simulation methods used here, when there were more than two-trait alleles there was a probability equal to 1-heterozygosity of the marker locus that both trait alleles were in disequilibrium with the same marker allele, resulting in the marker being uninformative for disequilibrium.^ The five tests using isolated unrelated individuals were found to have excess error rates when there was disequilibrium due to population admixture. Increased error rates also resulted from increased unlinked major gene effects, discordant trait allele frequency, and increased disequilibrium. Polygenic effects did not affect the error rates. The TDT, Transmission Disequilibrium Test, based tests were not liable to any increase in error rates.^ For all sample ascertainment costs, for recent mutations ($<$100 generations) linkage disequilibrium tests were less expensive than the variance component test to carry out. Candidate gene scans saved even more money. The use of recently admixed populations also decreased the cost of performing a linkage disequilibrium test. ^

An empirical evaluation of the Random Forests classifier models for variable selection in a large-scale lung cancer case-control study

Random Forests™ is reported to be one of the most accurate classification algorithms in complex data analysis. It shows excellent performance even when most predictors are noisy and the number of variables is much larger than the number of observations. In this thesis Random Forests was applied to a large-scale lung cancer case-control study. A novel way of automatically selecting prognostic factors was proposed. Also, synthetic positive control was used to validate Random Forests method. Throughout this study we showed that Random Forests can deal with large number of weak input variables without overfitting. It can account for non-additive interactions between these input variables. Random Forests can also be used for variable selection without being adversely affected by collinearities. ^ Random Forests can deal with the large-scale data sets without rigorous data preprocessing. It has robust variable importance ranking measure. Proposed is a novel variable selection method in context of Random Forests that uses the data noise level as the cut-off value to determine the subset of the important predictors. This new approach enhanced the ability of the Random Forests algorithm to automatically identify important predictors for complex data. The cut-off value can also be adjusted based on the results of the synthetic positive control experiments. ^ When the data set had high variables to observations ratio, Random Forests complemented the established logistic regression. This study suggested that Random Forests is recommended for such high dimensionality data. One can use Random Forests to select the important variables and then use logistic regression or Random Forests itself to estimate the effect size of the predictors and to classify new observations. ^ We also found that the mean decrease of accuracy is a more reliable variable ranking measurement than mean decrease of Gini. ^

An examination of the Gonorrhea Cases & Places study: An analysis of the Theory of Gender and Power, Situational/Environmental Variables Theory, and Sexual Script Theory as it relates to risky sexual behavior in African American adults

Objective. The purpose of the study is to provide a holistic depiction of behavioral & environmental factors contributing to risky sexual behaviors among predominantly high school educated, low-income African Americans residing in urban areas of Houston, TX utilizing the Theory of Gender and Power, Situational/Environmental Variables Theory, and Sexual Script Theory. ^ Methods. A cross-sectional study was conducted via questionnaires among 215 Houston area residents, 149 were women and 66 were male. Measures used to assess behaviors of the population included a history of homelessness, use of crack/cocaine among several other illicit drugs, the type of sexual partner, age of participant, age of most recent sex partner, whether or not participants sought health care in the last 12 months, knowledge of partner's other sexual activities, symptoms of depression, and places where partner's were met. In an effort to determine risk of sexual encounters, a risk index employing the variables used to assess condom use was created categorizing sexual encounters as unsafe or safe. ^ Results. Variables meeting the significance level of p<.15 for the bivariate analysis of each theory were entered into a binary logistic regression analysis. The block for each theory was significant, suggesting that the grouping assignments of each variable by theory were significantly associated with unsafe sexual behaviors. Within the regression analysis, variables such as sex for drugs/money, low income, and crack use demonstrated an effect size of ≥±1, indicating that these variables had a significant effect on unsafe sexual behavioral practices. ^ Conclusions. Variables assessing behavior and environment demonstrated a significant effect when categorized by relation to designated theories. ^

HIV incidence estimates and HIV/AIDS concurrent diagnosis in Houston/Harris County

The purpose of this dissertation was to estimate HIV incidence among the individuals who had HIV tests performed at the Houston Department of Health and Human Services (HDHHS) public health laboratory, and to examine the prevalence of HIV and AIDS concurrent diagnoses among HIV cases reported between 2000 and 2007 in Houston/Harris County. ^ The first study in this dissertation estimated the cumulative HIV incidence among the individuals testing at Houston public health laboratory using Serologic Testing Algorithms for Recent HIV Seroconversion (STARHS) during the two year study period (June 1, 2005 to May 31, 2007). The HIV incidence was estimated using two independently developed statistical imputation methods, one developed by the Centers for Disease Control and Prevention (CDC), and the other developed by HDHHS. Among the 54,394 persons who tested for HIV during the study period, 942 tested HIV positive (positivity rate=1.7%). Of these HIV positives, 448 (48%) were newly reported to the Houston HIV/AIDS Reporting System (HARS) and 417 of these 448 blood specimens (93%) were available for STARHS testing. The STARHS results showed 139 (33%) out of the 417 specimens were newly infected with HIV. Using both the CDC and HDHHS methods, the estimated cumulative HIV incidences over the two-year study period were similar: 862 per 100,000 persons (95% CI: 655-1,070) by CDC method, and 925 per 100,000 persons (95% CI: 908-943) by HDHHS method. Consistent with the national finding, this study found African Americans, and men who have sex with men (MSM) accounted for most of the new HIV infections among the individuals testing at Houston public health laboratory. Using CDC statistical method, this study also found the highest cumulative HIV incidence (2,176 per 100,000 persons [95%CI: 1,536-2,798]) was among those who tested in the HIV counseling and testing sites, compared to the sexually transmitted disease clinics (1,242 per 100,000 persons [95%CI: 871-1,608]) and city health clinics (215 per 100,000 persons [95%CI: 80-353]. This finding suggested the HIV counseling and testing sites in Houston were successful in reaching high risk populations and testing them early for HIV. In addition, older age groups had higher cumulative HIV incidence, but accounted for smaller proportions of new HIV infections. The incidence in the 30-39 age group (994 per 100,000 persons [95%CI: 625-1,363]) was 1.5 times the incidence in 13-29 age group (645 per 100,000 persons [95%CI: 447-840]); the incidences in 40-49 age group (1,371 per 100,000 persons [95%CI: 765-1,977]) and 50 or above age groups (1,369 per 100,000 persons [95%CI: 318-2,415]) were 2.1 times compared to the youngest 13-29 age group. The increased HIV incidence in older age groups suggested that persons 40 or above were still at risk to contract HIV infections. HIV prevention programs should encourage more people who are age 40 and above to test for HIV. ^ The second study investigated concurrent diagnoses of HIV and AIDS in Houston. Concurrent HIV/AIDS diagnosis is defined as AIDS diagnosis within three months of HIV diagnosis. This study found about one-third of the HIV cases were diagnosed with HIV and AIDS concurrently (within three months) in Houston/Harris County. Using multivariable logistic regression analysis, this study found being male, Hispanic, older, and diagnosed in the private sector of care were positively associated with concurrent HIV and AIDS diagnoses. By contrast, men who had sex with men and also used injection drugs (MSM/IDU) were 0.64 times (95% CI: 0.44-0.93) less likely to have concurrent HIV and AIDS diagnoses. A sensitivity analysis comparing difference durations of elapsed time for concurrent HIV and AIDS diagnosis definitions (1-month, 3-month, and 12-month cut-offs) affected the effect size of the odds ratios, but not the direction. ^ The results of these two studies, one describing characteristics of the individuals who were newly infected with HIV, and the other study describing persons who were diagnosed with HIV and AIDS concurrently, can be used as a reference for HIV prevention program planning in Houston/Harris County. ^

A dose-response analysis of a school-based nutrition intervention in middle school children

Childhood obesity in the US has reached epidemic proportions. Minority children are affected the most by this epidemic. Although there is no clear relationship between obesity and fruits and vegetables consumption, studies suggest that eating fruits and vegetables could be helpful in preventing childhood obesity. A few school-based interventions targeting youth have been effective at increasing fruits and vegetables intake.^ In Austin, Texas, the Sustainable Food Center delivered the Sprouting Healthy Kids (SHK) program that targeted low socio-economic status children in four intervention middle schools. The SHK program delivered six intervention components. This school-based intervention included: a cafeteria component, in-class lessons, an after-school garden program, a field trip to a local farm, food tasting, and farmers' visits to schools. This study aimed to determine the effects of the SHK intervention in middle school students' preferences, motivation, knowledge, and self-efficacy towards fruits and vegetables intake, as well as the actual fruits and vegetables intake. The study also aimed to determine the effects of exposure to different doses of the SHK intervention on participants' fruits and vegetable intake.^ The SHK was delivered during Spring 2009. A total of 214 students completed the pre-and-posttest surveys measuring self-report fruits and vegetables intake as well as intrapersonal factors. The results showed that the school cafeteria, the food tasting, the after school program, and the farmers' visits had a positive effect on the participants' motivation, knowledge, and self-efficacy towards fruits and vegetables intake. The farmers' visits and the food tasting components increased participants' fruits and vegetables intake. Exposure to two or more intervention components increased participants' fruits and vegetables intake. The statistically significant dose-response effect size was .352, which suggests that each intervention component increased participants' fruits and vegetables consumption this amount. Certain intervention components were more effective than others. Food tasting and farmers visits increased participants fruits and vegetables intake, therefore these components should be offered in an ongoing basis. This study suggests that exposure to multiple intervention components increased behaviors and attitudes towards fruits and vegetables consumption. Findings are consistent that SHK can influence behaviors of middle school students.^

Whence a healthy mind: Correlation of physical fitness and academic performance among schoolchildren

Background. Public schools are a key forum in the fight for child health because of the opportunities they present for physical activity and fitness surveillance. However, because schools are evaluated and funded on the basis of standardized academic performance rather than physical activity, empirical research evaluating the connections between fitness and academic performance is needed to justify curriculum allocations to physical activity. ^ Methods. Analyses were based on a convenience sample of 315,092 individually-matched standardized academic (TAKS™) and fitness (FITNESSGRAM®) test records collected by 13 Texas school districts under state mandates. We categorized each fitness result in quintiles by age and gender and used a mixed effects regression model to compare the academic performance of the top and bottom fitness groups for each fitness test and grade level combination. ^ Results. All fitness variables except BMI showed significant, positive associations with academic performance after sociodemographic covariate adjustments, with effect sizes ranging from 0.07 (95% CI: 0.05,0.08) in girls trunklift-TAKS reading to 0.34 (0.32,0.35) in boys cardiovascular-TAKS math. Cardiovascular fitness showed the largest inter-quintile difference in TAKS score (32-75 points), followed by curl-ups. After an additional adjustment for BMI and curl-ups, cardiovascular associations peaked in 8th-9 th grades (maximum inter-quintile difference 142 TAKS points; effect size 0.75 (0.69,0.82) for 8th grade girls math) and showed dose-response characteristics across quintiles (p<0.001 for both genders and outcomes). BMI analysis demonstrated limited, non-linear association with academic performance after adjustment for sociodemographic, cardiovascular fitness and curl-up variables. Low-BMI Hispanic high school boys showed significantly lower TAKS scores than the moderate (but not high) BMI group. High-BMI non-Hispanic white high school girls showed significantly lower scores than the moderate (but not low) BMI group. ^ Conclusions. In this study, fitness was strongly and significantly related to academic performance. Cardiovascular fitness showed a distinct dose-response association with academic performance independent of other sociodemographic and fitness variables. The association peaked in late middle to early high school. The independent association of BMI to academic performance was only found in two sub-groups and was non-linear, with both low and high BMI posing risk relative to moderate BMI but not to each other. In light of our findings, we recommend that policymakers consider PE mandates in middle-high school and require linkage of academic and fitness records to facilitate longitudinal surveillance. School administrators should consider increasing PE time in pursuit of higher academic test scores, and PE practitioners should emphasize cardiovascular fitness over BMI reduction.^

Performance recovery from exercise: A review from a statistical point of view

Background. Research into methods for recovery from fatigue due to exercise is a popular topic among sport medicine, kinesiology and physical therapy. However, both the quantity and quality of studies and a clear solution of recovery are lacking. An analysis of the statistical methods in the existing literature of performance recovery can enhance the quality of research and provide some guidance for future studies. Methods: A literature review was performed using SCOPUS, SPORTDiscus, MEDLINE, CINAHL, Cochrane Library and Science Citation Index Expanded databases to extract the studies related to performance recovery from exercise of human beings. Original studies and their statistical analysis for recovery methods including Active Recovery, Cryotherapy/Contrast Therapy, Massage Therapy, Diet/Ergogenics, and Rehydration were examined. Results: The review produces a Research Design and Statistical Method Analysis Summary. Conclusion: Research design and statistical methods can be improved by using the guideline from the Research Design and Statistical Method Analysis Summary. This summary table lists the potential issues and suggested solutions, such as, sample size calculation, sports specific and research design issues consideration, population and measure markers selection, statistical methods for different analytical requirements, equality of variance and normality of data, post hoc analyses and effect size calculation.^

Multivariate methods for correlated effects sizes

Current statistical methods for estimation of parametric effect sizes from a series of experiments are generally restricted to univariate comparisons of standardized mean differences between two treatments. Multivariate methods are presented for the case in which effect size is a vector of standardized multivariate mean differences and the number of treatment groups is two or more. The proposed methods employ a vector of independent sample means for each response variable that leads to a covariance structure which depends only on correlations among the $p$ responses on each subject. Using weighted least squares theory and the assumption that the observations are from normally distributed populations, multivariate hypotheses analogous to common hypotheses used for testing effect sizes were formulated and tested for treatment effects which are correlated through a common control group, through multiple response variables observed on each subject, or both conditions.^ The asymptotic multivariate distribution for correlated effect sizes is obtained by extending univariate methods for estimating effect sizes which are correlated through common control groups. The joint distribution of vectors of effect sizes (from $p$ responses on each subject) from one treatment and one control group and from several treatment groups sharing a common control group are derived. Methods are given for estimation of linear combinations of effect sizes when certain homogeneity conditions are met, and for estimation of vectors of effect sizes and confidence intervals from $p$ responses on each subject. Computational illustrations are provided using data from studies of effects of electric field exposure on small laboratory animals. ^

Variation in hospital inpatient charges by payer in Houston, Texas

An analysis of variation in hospital inpatient charges in the greater Houston area is conducted to determine if there are consistent differences among payers. Differences in charges are examined for 59 Composite Diagnosis Related Groups (CDRGs) and two regression equations estimating charges are specified. Simple comparison of mean charges by diagnostic categories are significantly different for 42 (71 percent) of the 59 categories examined. In 41 of the 42 significant categories, charges to Medicaid were less than charges to private insurers. Meta-analytic statistical techniques yielded a weighted average effect size of $-$0.7198 for the 59 diagnostic categories, indicating an overall effect that Medicaid charges were less than private insurance charges. Results of a multiple regression estimating charges showed that private insurance was a significant independent variable, along with age, length of stay, and hospital variables. Results indicated consistent differential charges in the present analysis. ^

The success of worksite nutrition and physical activity interventions with environmental modifications A systematic review

Background: As obesity increases among U.S. workers, employers are implementing programs to increase physical activity and improve diets. Although programs to address individual determinants of obesity have been evaluated, less is known about the effects of workplace programs that change environmental factors, because most reviews have not isolated environmental programs; the one that did was published in 2005. ^ Objective: To update the 2005 review to determine the effectiveness of workplace environmental interventions. ^ Methods: The Medline database was searched for published English language reports (2003-2011) of randomized controlled (RCTs) or quasi-experimental trials (NRCTs) that evaluated strategies to modify physical activity opportunities or food services, targeting employees at least 18 years, not including retirees and that provided data for at least one physical activity, dietary, or health risk indicator. Three coders independently extracted study characteristics and scored the quality of study methods. Program effectiveness was determined using the 2005 review's best evidence approach. ^ Results: Seven studies represented in nine reports met eligibility criteria; three focused on diet and the remainder targeted diet and physical activity interventions. All but one study received a high quality score for internal validity. The evidence for the effectiveness of workplace environmental interventions was at best, inconclusive for diet and physical activity and limited for health risk indicators. The outcome constructs were inconsistent across the studies. ^ Conclusions: Limitations in the methods of the 2005 review made it challenging to draw conclusions about findings for this review that include: variation in outcome measures, reliance on distal measures without proximal behavior change measures, no distinction between changes at the workplace versus outside the workplace, and inappropriate analyses of cluster designs that biased findings toward statistical significance. The best evidence approach relied on vote-counting, using statistical significance alone rather than effect size and confidence intervals. Future research should address these limitations and use more rigorous methods; systematic reviews should use methods of meta-analysis to summarize study findings. These recommendations will help employers to better understand how environmental modifications in the workplace can support their efforts to combat the effects of obesity among employees.^

A simulation study using the hybrid statistic and the meta-analysis t-test for data with matched and unmatched subjects in the interim analysis of clinical trials

An interim analysis is usually applied in later phase II or phase III trials to find convincing evidence of a significant treatment difference that may lead to trial termination at an earlier point than planned at the beginning. This can result in the saving of patient resources and shortening of drug development and approval time. In addition, ethics and economics are also the reasons to stop a trial earlier. In clinical trials of eyes, ears, knees, arms, kidneys, lungs, and other clustered treatments, data may include distribution-free random variables with matched and unmatched subjects in one study. It is important to properly include both subjects in the interim and the final analyses so that the maximum efficiency of statistical and clinical inferences can be obtained at different stages of the trials. So far, no publication has applied a statistical method for distribution-free data with matched and unmatched subjects in the interim analysis of clinical trials. In this simulation study, the hybrid statistic was used to estimate the empirical powers and the empirical type I errors among the simulated datasets with different sample sizes, different effect sizes, different correlation coefficients for matched pairs, and different data distributions, respectively, in the interim and final analysis with 4 different group sequential methods. Empirical powers and empirical type I errors were also compared to those estimated by using the meta-analysis t-test among the same simulated datasets. Results from this simulation study show that, compared to the meta-analysis t-test commonly used for data with normally distributed observations, the hybrid statistic has a greater power for data observed from normally, log-normally, and multinomially distributed random variables with matched and unmatched subjects and with outliers. Powers rose with the increase in sample size, effect size, and correlation coefficient for the matched pairs. In addition, lower type I errors were observed estimated by using the hybrid statistic, which indicates that this test is also conservative for data with outliers in the interim analysis of clinical trials.^

Effect of progressive mandibular advancement on pharyngeal airway size in anesthetized adults.

BACKGROUND: General anesthesia in adult humans is associated with narrowing or complete closure of the pharyngeal airway. The purpose of this study was to determine the effect of progressive mandibular advancement on pharyngeal airway size in normal adults during intravenous infusion of propofol for anesthesia. METHODS: Magnetic resonance imaging was performed in nine normal adults during wakefulness and during propofol anesthesia. A commercially available intraoral appliance was used to manually advance the mandible. Images were obtained during wakefulness without the appliance and during anesthesia with the participants wearing the appliance under three conditions: without mandibular advancement, advancement to 50% maximum voluntary advancement, and maximum advancement. Using computer software, airway area and maximum anteroposterior and lateral airway diameters were measured on the axial images at the level of the soft palate, uvula, tip of the epiglottis, and base of the epiglottis. RESULTS: Airway area across all four airway levels decreased during anesthesia without mandibular advancement compared with airway area during wakefulness (P < 0.007). Across all levels, airway area at 50% advancement during anesthesia was less than that at centric occlusion during wakefulness (P = 0.06), but airway area with maximum advancement during anesthesia was similar to that during wakefulness (P = 0.64). In general, anteroposterior and lateral airway diameters during anesthesia without mandibular advancement were decreased compared with wakefulness and were restored to their wakefulness values with 50% and/or maximal advancement. CONCLUSIONS: Maximum mandibular advancement during propofol anesthesia is required to restore the pharyngeal airway to its size during wakefulness in normal adults.

Effect of patient accrual patterns on power and size of log-rank test for time-to-event outcome in clinical trials

The determination of size as well as power of a test is a vital part of a Clinical Trial Design. This research focuses on the simulation of clinical trial data with time-to-event as the primary outcome. It investigates the impact of different recruitment patterns, and time dependent hazard structures on size and power of the log-rank test. A non-homogeneous Poisson process is used to simulate entry times according to the different accrual patterns. A Weibull distribution is employed to simulate survival times according to the different hazard structures. The current study utilizes simulation methods to evaluate the effect of different recruitment patterns on size and power estimates of the log-rank test. The size of the log-rank test is estimated by simulating survival times with identical hazard rates between the treatment and the control arm of the study resulting in a hazard ratio of one. Powers of the log-rank test at specific values of hazard ratio (≠1) are estimated by simulating survival times with different, but proportional hazard rates for the two arms of the study. Different shapes (constant, decreasing, or increasing) of the hazard function of the Weibull distribution are also considered to assess the effect of hazard structure on the size and power of the log-rank test. ^