A simple correction for ties when censoring times depend on covariates

Sexual Debut Ages in Heterosexual Norwegians Across Six Birth Cohorts

This study aims to estimate six different sexual debut ages in heterosexual Norwegians in six birth cohorts of the general population in Norway. The results are based on a 2020 national web panel survey of 18-89-year-olds in Norway (n = 4160). There was a general decline in the median debut age from those aged 70+ to those 18-29 (born 1991-2002). Oral sex with a female partner has become increasingly common among men at an earlier age across generations. The same pattern was found in women as well with regard to oral sex with a male partner and receptive anal sex. There was a slight increase in median debut age in 18-29-year-olds for receptive vaginal sex (born 1991-2002). The median debut age for vaginal sex was fairly stable for generations of men and women born after 1950.

Handling ties in continuous outcomes for confounder adjustment with rank-ordered logit and its application to ordinal outcomes

The rank-ordered logit (rologit) model was recently introduced as a robust approach for analysing continuous outcomes, with the linear exposure effect estimated by scaling the rank-based log-odds estimate. Here we extend the application of the rologit model to continuous outcomes with ties and ordinal outcomes treated as imperfectly-observed continuous outcomes. By identifying the functional relationship between survival times and continuous outcomes, we explicitly establish the equivalence between the rologit and Cox models to justify the use of the Breslow, Efron and perturbation methods in the analysis of continuous outcomes with ties. Using simulation, we found all three methods perform well with few ties. Although an increasing extent of ties increased the bias of the log-odds and linear effect estimates and resulted in reduced power, which was somewhat worse when the model was mis-specified, the perturbation method maintained a type I error around 5%, while the Efron method became conservative with heavy ties but outperformed Breslow. In general, the perturbation method had the highest power, followed by the Efron and then the Breslow method. We applied our approach to three real-life datasets, demonstrating a seamless analytical workflow that uses stratification for confounder adjustment in studies of continuous and ordinal outcomes.

Hazard ratio estimation and inference in clinical trials with many tied event times

The medical literature contains numerous examples of randomized clinical trials with time-to-event endpoints in which large numbers of events accrued over relatively short follow-up periods, resulting in many tied event times. A generally common feature across such examples was that the logrank test was used for hypothesis testing and the Cox proportional hazards model was used for hazard ratio estimation. We caution that this common practice is particularly risky in the setting of many tied event times for two reasons. First, the estimator of the hazard ratio can be severely biased if the Breslow tie-handling approximation for the Cox model (the default in SAS and Stata software) is used. Second, the 95% confidence interval for the hazard ratio can include one even when the corresponding logrank test p-value is less than 0.05. To help establish a better practice, with applicability for both superiority and noninferiority trials, we use theory and simulations to contrast Wald and score tests based on well-known tie-handling approximations for the Cox model. Our recommendation is to report the Wald test p-value and corresponding confidence interval based on the Efron approximation. The recommended test is essentially as powerful as the logrank test, the accompanying point and interval estimates of the hazard ratio have excellent statistical properties even in settings with many tied event times, inferential alignment between the p-value and confidence interval is guaranteed, and implementation is straightforward using commonly used software.

A statistical model to detect asymptomatic infectious individuals with an application in the Phytophthora alni-induced alder decline

In some diseases-in particular, tree root infection-stages of infection and inoculum production level and timing are not readily observable because of uncertainty or time lags in symptom appearance. Here, we pose a criterion, based on relative hazard of disease symptoms, to discriminate between healthy and asymptomatic infected individuals. We design a statistical procedure to estimate the criterion for a 6-year survey of alder decline along a northeastern French river. Individual tree symptom hazard was modeled with Cox's regression model, taking estimation of local infection pressure as a risk factor. From an inoculum production experiment, we thereafter assessed the inoculum production level of target trees, including symptomatic and asymptomatic trees ranked according to their symptoms hazard. Using receiver operating characteristic methods, we first evaluated the criterion performance and determined the discrimination threshold to sort out asymptomatic individuals into healthy and infected. Then, we highlighted the fact that the infected asymptomatic trees were among the major inoculum producers whereas severely declining and dead trees were found to be poor inoculum sources.

Analysis of first coitus

The analysis of age of coital debut is central to a description of sexual behavior. Age of coital debut data typically shares some characteristics that make analysis difficult. For one, age is reported in whole years and, furthermore, some subjects do not report debut. We aimed to find a regression model that fits this type of data well and gives simple and interpretable results. We studied age of debut in four cross-sectional surveys (1987-2002) for a total of 18,000 subjects from the adult Norwegian population. We compared a Cox-model with a linear parametric survival model. Survival methods are natural tools for analyzing age of coital debut. The debut ages did not follow the proportional hazard model well and an additive parametric survival model was the better regression model for the Norwegian data set. Furthermore, the additive model was easier to interpret. The analysis showed a substantial change in age of debut in the cohorts born 1927-1984, with a drop of 1 year for men and 2.3 years for women. Women in the oldest cohorts reported their debut 0.8 years later and in the youngest cohorts 0.5 years earlier than did men. A parametric survival model gives results that are easier to interpret and fits the Norwegian data better than the Cox-model.

Partial-likelihood analysis of spatio-temporal point-process data

We investigate the use of a partial likelihood for estimation of the parameters of interest in spatio-temporal point-process models. We identify an important distinction between spatially discrete and spatially continuous models. We focus our attention on the spatially continuous case, which has not previously been considered. We use an inhomogeneous Poisson process and an infectious disease process, for which maximum-likelihood estimation is tractable, to assess the relative efficiency of partial versus full likelihood, and to illustrate the relative ease of implementation of the former. We apply the partial-likelihood method to a study of the nesting pattern of common terns in the Ebro Delta Natural Park, Spain.