Hu et al., 2020 - Google Patents
Modified Kaplan–Meier estimator and Nelson–Aalen estimator with geographical weighting for survival dataHu et al., 2020
View PDF- Document ID
- 13537410198687099878
- Author
- Hu G
- Huffer F
- Publication year
- Publication venue
- Geographical Analysis
External Links
Snippet
The Kaplan–Meier and Nelson–Aalen estimators are universally used methods in clinical studies. In a public health study, people often collect data from different locations of the medical services provider. When some studies need to consider survival curves from …
- 230000004083 survival 0 title abstract description 43
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Hong et al. | Exposure density and neighborhood disparities in COVID-19 infection risk | |
Hu et al. | Local structure can identify and quantify influential global spreaders in large scale social networks | |
Li et al. | Small sample performance of bias‐corrected sandwich estimators for cluster‐randomized trials with binary outcomes | |
ES2836207T3 (en) | Multi-party Secure Computing without Reliable Initializer | |
Toch et al. | Empirical models of privacy in location sharing | |
Panigutti et al. | Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models | |
Scholl et al. | Detecting spatial clustering using a firm-level cluster index | |
Hu et al. | Modified Kaplan–Meier estimator and Nelson–Aalen estimator with geographical weighting for survival data | |
Bardos et al. | Valid auto‐models for spatially autocorrelated occupancy and abundance data | |
US11386216B2 (en) | Verification of privacy in a shared resource environment | |
Blumenstock et al. | Social and spatial ethnic segregation: A framework for analyzing segregation with large-scale spatial network data | |
CN110941856A (en) | Data differential privacy protection sharing platform based on block chain | |
Viana et al. | Disentangling spatial and environmental effects: Flexible methods for community ecology and macroecology | |
Song et al. | Regression analysis of longitudinal data with time‐dependent covariates and informative observation times | |
Zhou et al. | Empirical likelihood ratio test for median and mean residual lifetime | |
Bandyopadhyay et al. | A Spectral Domain Test for Stationarity of Spatio‐Temporal Data | |
Doktorski | Some reiteration theorems for R, L, RR, RL, LR, and LL limiting interpolation spaces | |
US20200074110A1 (en) | Sampling from a remote dataset with a private criterion | |
Lumley et al. | Partial likelihood ratio tests for the Cox model under complex sampling | |
CN114650179A (en) | Risk data monitoring method, device and system, electronic equipment and storage medium | |
Shabanov | On a generalization of Rubin's theorem | |
Gilbert et al. | Power/sample size calculations for assessing correlates of risk in clinical efficacy trials | |
Houssiau et al. | A framework for auditable synthetic data generation | |
Zhang et al. | Understanding and predicting the spatio‐temporal spread of COVID‐19 via integrating diffusive graph embedding and compartmental models | |
US11144673B2 (en) | Centralized system for sensitive data conversion |