No abstract

The standard modeling approach for time-to-event outcomes subject to censoring is based on the hazard function, with hazard ratios capturing the effect of exposures on the risk of outcome. The restricted mean survival time, defined as the expected time to event up to a pre-specified time horizon, provides an alternative useful summary of time-to-event outcomes. Restricted mean survival time can be estimated nonparametrically and can be used to compare groups or interventions when the proportional hazards (PHs) assumption does not hold. Moreover, even when the proportional hazards assumption holds, the restricted mean survival time, an additive measure of risk, provides additional information to the hazard ratio, which is a measure of relative risk that can be difficult to interpret in absence of an estimate of the reference risk. Herein, a generalized fiducial approach is proposed for restricted mean survival time, and its asymptotic properties are investigated. Numerical simulations show the proposed approach provides one- and two-sided confidence intervals with coverage probabilities close to nominal values and controls the type-I error for two-group comparisons even for small sample sizes with a low number of events. Data from a type 1 diabetes study is used for illustration.

Objectives: To determine if trans-laryngeal airflow, important in assessing vocal function in paresis/paralysis and presbylarynges patients with mid-cord glottal gaps, could be predicted by other measures sensitive to mid-cord glottal gap size but with smaller risks of spreading COVID-19, and if any patient factors need consideration. Methods: Four populations were: unilateral vocal fold paresis/paralysis (UVFP, 148), aging and UVFP (UVFP plus aging, 22), bilateral vocal fold paresis/paralysis without airway obstruction (BVFP, 49), and presbylarynges (66). Five measures were selected from the initial clinic visit: mean airflow from repeated /pi/ syllables, longer of 2 /s/ and 2 /z/ productions, higher of 2 cepstral peak prominence smoothed for vowel /a/ (CPPSa), and Glottal Function Index (GFI). S/Z ratios were computed. Stepwise regression models used 3 measures and 5 patient factors (age, sex, etiology, diagnosis, and potentially impaired power source for voicing) to predict airflow. Results: Log-transformations were required to normalize distributions of airflow and S/Z ratio. The final model revealed age, sex, impaired power source, log-transformed S/Z ratio, and GFI predicted log-transformed airflow ( R2 = .275, F[5,278] = 21.1; P < .001). Conclusions: The amount of variance explained by the model was not high, suggesting adding other predictive variables to the model might increase the variance explained.