Effects of Model Misspecification in Estimating Covariate Effects in Survival Analysis for Small Sample Sizes

The results of a Monte Carlo study of the size and power of parametric and semiparametric approaches to inference on covariate effects in survival (time-to-events) models in the presence of model misspecification and an independent censoring mechanism are reported. Basic models employed are a parametric model, where both a baseline distribution and the dependence structure of covariates on the failure times are fully specified (exponential, Weibull, log logistic, log normal, and normal regression models are studied), and a semi-parametric approach (due to Cox) in which the baseline distribution is unspecified. The Cox model performs very well compared to the parametric models for distributions with proportional hazard rates and appears to be robust with regard to the proportional hazard assumption. Appropriate parametric models have the potential of improving the size and power of the tests, although overall they are not appreciably better than the Cox model. In comparing the small sample performance of three statistical tests, the likelihood ratio and Wald tests closely agree with each other (likelihood ratio having a slight advantage), while the score test tends to perform much poorer since it inflates the size and power more than the other two

Changes in Periodontal Health Status Are Associated with Bacterial Community Shifts as Assessed by Quantitative 16S Cloning and Sequencing

The gingival sulcus contains a complex ecosystem that includes many uncultivated bacteria. Understanding the dynamics of this ecosystem in transitions between health and disease is important in advancing our understanding of the bacterial etiology of periodontitis. The objective of this longitudinal study was to examine the stability of bacterial colonization in the gingival crevice and to explore the relationship between shifts in microbial composition and changes in periodontal health status using a comprehensive, quantitative, culture-independent approach. Subgingival plaque samples and periodontal data were collected from 24 subjects over 2 years. Baseline and 2-year plaque samples were analyzed using quantitative ribosomal 16S cloning and sequencing. Ten subjects remained periodontally healthy over 2 years, the periodontal health of seven subjects worsened, and seven subjects showed clinical improvement. Bacterial stability was greatest among healthy, clinically stable subjects and lowest for subjects whose periodontal status worsened (P = 0.01). Higher numbers of species lost or gained were also observed for subjects whose clinical status changed (P = 0.009). This provides evidence that a change in periodontal status is accompanied by shifts within the bacterial community. Based on these data, measures of microbial stability may be useful in clinical diagnosis and prognosis. Regarding individual species, increases in levels of the uncultivated phylotype Veillonella sp. oral clone X042, a gram-negative bacterium and the most common member of the subgingival bacterial community, were associated with periodontal health (P = 0.04), suggesting that this is an important beneficial species. Filifactor alocis, a gram-positive anaerobe, was found at higher levels in subjects with disease (P = 0.01)

Journal of the American Veterinary Medical Association 201 8 1197 1202 UNITED STATES

Forty-eight herds participating in the 1988/1989 Ohio National Animal Health Monitoring System dairy project were monitored for 1 year to determine the effects of environment and management on mortality in preweaned calves. Environmental factors were evaluated by veterinarians during monthly visits to the herds. Management procedures were measured through the use of a questionnaire administered near the end of the project. Mortality in preweaned calves was calculated for each herd by using data from project records on calf mortality and animal inventory, which were collected monthly by veterinarians. Relationships between the management/environment variables and calf mortality were examined by use of analysis of covariance. Herd size, days on a nipple feeder, navel disinfection, type of housing, and whether each calf observed with diarrhea was treated with antibiotics were the variables that had an impact on herd mortality. These variables explained approximately 39% of the variation in mortality among herds

Quantifying the average of the time-varying hazard ratio via a class of transformations

The hazard ratio derived from the Cox model is a commonly used summary statistic to quantify a treatment effect with a time-to-event outcome. The proportional hazards assumption of the Cox model, however, is frequently violated in practice and many alternative models have been proposed in the statistical literature. Unfortunately, the regression coefficients obtained from different models are often not directly comparable. To overcome this problem, we propose a family of weighted hazard ratio measures that are based on the marginal survival curves or marginal hazard functions, and can be estimated using readily available output from various modeling approaches. The proposed transformation family includes the transformations considered by [18] as special cases. In addition, we propose a novel estimate of the weighted hazard ratio based on the maximum departure from the null hypothesis within the transformation family, and develop a Kolmogorov–Smirnov type of test statistic based on this estimate. Simulation studies show that when the hazard functions of two groups either converge or diverge, this new estimate yields a more powerful test than tests based on the individual transformations recommended in [18], with a similar magnitude of power loss when the hazards cross. The proposed estimates and test statistics are applied to a colorectal cancer clinical trial