Modeling Demand for Recreational Trips of Differing Lengths: A Competing Risks Duration Model with Censoring and Time-varying Covariates

1998 ◽  
Author(s):  
Carol Adaire Jones ◽  
Yusen Sung ◽  
Heng Z. Chen
Keyword(s):  
Competing Risks ◽  
Duration Model ◽  
Time Varying ◽  
Time Varying Covariates

scholarly journals A competing risks model with binary time varying covariates for estimation of breast cancer risks in BRCA1 families

2021 ◽  
pp. 096228022110089
Author(s):  
Yun-Hee Choi ◽  
Hae Jung ◽  
Saundra Buys ◽  
Mary Daly ◽  
Esther M John ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Ovarian Cancer ◽  
Competing Risks ◽  
Brca1 Mutation ◽  
Prophylactic Surgery ◽  
Time Varying ◽  
Cancer Risks ◽  
Competing Risks Model ◽  
Time Varying Covariates ◽  
Risk Reducing

Mammographic screening and prophylactic surgery such as risk-reducing salpingo oophorectomy can potentially reduce breast cancer risks among mutation carriers of BRCA families. The evaluation of these interventions is usually complicated by the fact that their effects on breast cancer may change over time and by the presence of competing risks. We introduce a correlated competing risks model to model breast and ovarian cancer risks within BRCA1 families that accounts for time-varying covariates. Different parametric forms for the effects of time-varying covariates are proposed for more flexibility and a correlated gamma frailty model is specified to account for the correlated competing events.We also introduce a new ascertainment correction approach that accounts for the selection of families through probands affected with either breast or ovarian cancer, or unaffected. Our simulation studies demonstrate the good performances of our proposed approach in terms of bias and precision of the estimators of model parameters and cause-specific penetrances over different levels of familial correlations. We applied our new approach to 498 BRCA1 mutation carrier families recruited through the Breast Cancer Family Registry. Our results demonstrate the importance of the functional form of the time-varying covariate effect when assessing the role of risk-reducing salpingo oophorectomy on breast cancer. In particular, under the best fitting time-varying covariate model, the overall effect of risk-reducing salpingo oophorectomy on breast cancer risk was statistically significant in women with BRCA1 mutation.

Time Varying Trade Intensities and the Deutsche Telekom IPO / Zeitvariable Handelsintensitaten und die Deutsche Telekom IPO

2000 ◽  
Vol 220 (6) ◽  
Author(s):  
Reinhard Hujer ◽  
Joachim Grammig ◽  
Stefan Kokot
Keyword(s):  
Initial Public Offering ◽  
Structural Breaks ◽  
Duration Model ◽  
Time Varying ◽  
Threshold Autoregressive ◽  
Public Offering ◽  
Autoregressive Conditional Duration ◽  
Autoregressive Conditional Duration Model

SummaryWe apply the Threshold Autoregressive Conditional Duration Model (TACD) as proposed by Zhang, Russell, and Tsay (1999) to model the after market trading duration process associated with the initial public offering of the Deutsche Telekom AG share in November of 1996. Special emphasis is devoted to the empirical specification of intra-day seasonality and to the detection of non-stationarity and structural breaks in the trading process.

The third birth in Great Britain

1988 ◽  
Vol 20 (4) ◽  
pp. 489-496 ◽  
Author(s):  
Robert E. Wright ◽  
John F. Ermisch ◽  
P. R. Andrew Hinde ◽  
Heather E. Joshi
Keyword(s):  
Labour Force ◽  
Strong Association ◽  
Labour Force Participation ◽  
Age At First Birth ◽  
Time Varying ◽  
Female Labour ◽  
Subsequent Fertility ◽  
Lower Fertility ◽  
Time Varying Covariates ◽  
The Relationship

SummaryThe relationship between female labour force participation, and other socioeconomic factors, and the probability of having a third birth is examined, using British data collected in the 1980 Women and Employment Survey, by hazard regression modelling with time-varying covariates. The results demonstrate the strong association between demographic factors, e.g. age at first birth and birth interval and subsequent fertility behaviour. Education appears to have little effect. Surprisingly, women who have spent a higher proportion of time as housewives have a lower risk of having a third birth. This finding is in sharp disagreement with the conventional expectation that cumulative labour force participation supports lower fertility. These findings are briefly compared with similar research carried out in Sweden.

Survival Analysis and ROC Analysis in Analyzing Credit Risks

2018 ◽  
pp. 110-133
Author(s):  
Nan Hu ◽  
Haojie Cheng
Keyword(s):  
Competing Risks ◽  
Scoring System ◽  
Roc Analysis ◽  
Credit Scoring ◽  
Scoring Systems ◽  
Time Varying ◽  
Statistical Tool ◽  
Cross Sectional ◽  
Credit Risks ◽  
Over Time

As the aim of large banks has been changing to select customers of highest benefits, it is important for banks to know not only if but also when a customer will default. Survival analyses have been used to estimate over time risk of default or early payoff, two major risks for banks. The major benefit of this method is that it can easily handle censoring and competing risks. An ROC curve, as a statistical tool, was applied to evaluate credit scoring systems. Traditional ROC analyses allow banks to evaluate if a credit-scoring system can correctly classify customers based on their cross-sectional default status, but will fail when assessing a credit-scoring system at a series of future time points, especially when there are censorings or competing risks. The time-dependent ROC analysis was introduced by Hu and Zhou to evaluate credit-scoring systems in a time-varying fashion and it allows us to assess credit scoring systems for predicting default by any time within study periods.

scholarly journals A General and Robust Estimation Method for the Case-Time-Control Design

2019 ◽  
Vol 49 (1) ◽  
pp. 349-365
Author(s):  
Arvid Sjölander ◽  
Yang Ning
Keyword(s):  
Robust Estimation ◽  
Arbitrary Number ◽  
Estimation Method ◽  
Control Design ◽  
Time Varying ◽  
Time Control ◽  
Measured Time ◽  
Important Extension ◽  
Time Varying Covariates

The case-time-control design is a tool to control for measured, time-varying covariates that increase montonically in time within each subject while also controlling for all unmeasured covariates that are constant within each subject across time. Until recently, the design was restricted to data with only two timepoints and a single binary covariate, or data with a binary exposure. Sjölander (2017) made an important extension that allows for an arbitrary number of timepoints and covariates and a nonbinary exposure. However, his estimation method requires fairly strong model assumptions, and it may create bias if these assumptions are violated. We propose a novel estimation method for the case-time-control design, which to a large extent relaxes the model assumptions in Sjölander. We show in simulations that this estimation method performs well under a range of scenarios and gives consistent estimates when Sjölander’s estimation does not.

scholarly journals Irregular sleep and event schedules are associated with poorer self-reported well-being in US college students

SLEEP ◽  
2019 ◽  
Vol 43 (6) ◽  
Author(s):  
Dorothee Fischer ◽  
Andrew W McHill ◽  
Akane Sano ◽  
Rosalind W Picard ◽  
Laura K Barger ◽  
...  
Keyword(s):  
College Students ◽  
Cluster Analysis ◽  
Sleep Duration ◽  
Well Being ◽  
Early Morning ◽  
Time Varying ◽  
Clinical Trial Registration ◽  
Systematic Relationship ◽  
Phase Deviation ◽  
Time Varying Covariates

Abstract Study Objectives Sleep regularity, in addition to duration and timing, is predictive of daily variations in well-being. One possible contributor to changes in these sleep dimensions are early morning scheduled events. We applied a composite metric—the Composite Phase Deviation (CPD)—to assess mistiming and irregularity of both sleep and event schedules to examine their relationship with self-reported well-being in US college students. Methods Daily well-being, actigraphy, and timing of sleep and first scheduled events (academic/exercise/other) were collected for approximately 30 days from 223 US college students (37% females) between 2013 and 2016. Participants rated well-being daily upon awakening on five scales: Sleepy–Alert, Sad–Happy, Sluggish–Energetic, Sick–Healthy, and Stressed–Calm. A longitudinal growth model with time-varying covariates was used to assess relationships between sleep variables (i.e. CPDSleep, sleep duration, and midsleep time) and daily and average well-being. Cluster analysis was used to examine relationships between CPD for sleep vs. event schedules. Results CPD for sleep was a significant predictor of average well-being (e.g. Stressed–Calm: b = −6.3, p < 0.01), whereas sleep duration was a significant predictor of daily well-being (Stressed–Calm, b = 1.0, p < 0.001). Although cluster analysis revealed no systematic relationship between CPD for sleep vs. event schedules (i.e. more mistimed/irregular events were not associated with more mistimed/irregular sleep), they interacted upon well-being: the poorest well-being was reported by students for whom both sleep and event schedules were mistimed and irregular. Conclusions Sleep regularity and duration may be risk factors for lower well-being in college students. Stabilizing sleep and/or event schedules may help improve well-being. Clinical Trial Registration NCT02846077.

Sign in / Sign up

Export Citation Format

Share Document