Not exact matches
We further extended our second multivariable
model to evaluate the influence on our
estimates by adjustment for additional nutrients known to be constituents of milk, but the
hazard ratios were only changed by 4 % or less.
This finding is important because government agencies and consulting companies use 2 - D shallow flow
models to predict dam breaks and floods, as well as to
estimate flood
hazards.
Survival rates were
estimated using the Kaplan - Meier method and compared using the log - rank test and Cox proportional
hazard models.
«In our opinion, regulators should require industry to undergo this kind of numerical
modeling testing prior to drilling to better
estimate the potential
hazard beforehand,» continues Jeoung Seok Yoon.
Overeem's technique «has the potential to give good quantitative rainfall
estimates for real - time
hazards forecasting, as well as regional and global climate
model analysis in regions of the world where the impact could be great,» Baeck says.
We can now use these new
models to better
estimate the potential seismic and volcanic
hazards.»
Cumulative death rates were summarized using Kaplan Meier curves, and
hazard ratios were
estimated using Cox proportional
hazards models.
In an unadjusted Cox
model, alendronate treatment was associated with lower of risk of hip fracture (
hazard ratio [HR], 0.35; 95 % CI, 0.23 - 0.55), and the risk
estimate did not substantially change in multivariable - adjusted Cox
models (Table 2 and Figure 3).
Hazard ratios (HRs) were
estimated using Cox proportional
hazards models stratified by age, prior disease (if appropriate), and randomization status in the WHI dietary modification trial.
Univariate
hazard estimates were generated with unadjusted Cox proportional
hazards models.
We used Cox proportional
hazard models to
estimate hazard ratios (HRs) and 95 % confidence intervals (CIs) of mortality according to fitness, adiposity, age, smoking status, abnormal exercise ECG responses, and baseline medical condition exposure categories.
Next, we fitted Cox proportional
hazard models to
estimate hazard ratios and 95 % confidence intervals according to each exposure variable.
Transforming
hazard into risk: Researchers at Berkeley Lab, LLNL and UC Davis are utilizing ground motion
estimates from a regional - scale geophysics
model to drive infrastructure assessments.
Hazard ratios and 95 % confidence intervals for mortality associated with coffee consumption were
estimated with the use of Cox proportional -
hazards regression
models, with person - years as the underlying time metric; results calculated with age as the underlying time metric were similar.
Hazard ratios for death associated with categories of coffee consumption (< 1, 1, 2 or 3, 4 or 5, and ≥ 6 cups per day), as compared with no coffee consumption, were
estimated from a single
model.
We used time - varying Cox proportional
hazards regression
models with age as the time scale to
estimate the
hazard ratio (HR) and 95 % CI for mortality associated with animal and plant protein intake.
We
estimated hazard ratios (HRs) and 95 % confidence intervals (CIs) with time since entry into the study as the underlying time metric using Cox proportional
hazards regression
models.
Relative risks of clinical depression were
estimated using Cox proportional
hazards regression
models.
Their Landslide
Hazard Assessment for Situational Awareness (LHASA)
model melds information regarding slope, lithology, deforested areas, and proximity to fault zones and roads to derive a map of landslide susceptibility, which is then combined with satellite - derived
estimates of precipitation from the past week to develop «nowcasts» of areas that are susceptible to landslides.
The risk assessment framework comprises hydrological
modelling, threshold - based evaluation of extreme event magnitude and frequency, fully integrated 2D flood
hazard mapping, updated exposure maps, country - specific depth - damage functions and improved vulnerability information to
estimate current and future flood risk.
We also
estimated Cox proportional
hazard models to identify demographic and placement history characteristics associated with the risk of child welfare services involvement.
We use a Cox proportional
hazard model to
estimate the relative
hazard of a second birth.