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Figure 2 Predicted discrete hazard rates.
The well-known nonparametric textbook approach focuses on utilizing the discrete hazard function to define the parameters of interest.
This method ensures that the alternative discrete hazard rate function of the discrete analogue is exactly same the hazard rate of the underlying continuous one.
Applying discrete hazard models to a unique dataset of renters, this study empirically evaluates individual, neighborhood, and social network characteristics that explain disparities in displacement from housing.
Alternative discrete hazard rate was defined by Roy and Gupta (1992) as ( {lambda}_Y^ k)= log left[{S}_Y k)/{S}_Yleft k+1right)right]. ) This definition overcomes some of the problems classical definition of discrete hazard rate (see also Lai 2013).
The resulting data set is used for a discrete hazard analysis of the determinants of unemployment exits, focusing on the role of variation in the maximum availability of UI benefits across states and over time.
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A discrete hazards model on a person-month file was used to generate the underlying risks for predicting mortality rates.
In addition to the kernel smoothing approach with discrete hazards, a formal flexible regression modelling strategy was adopted as proposed by Boracchi and colleagues [ 19].
The discrete hazards of recurrence and their standard deviations were calculated by means of the life-table method over 4 years.
In addition to the Kernel smoothing approach with discrete hazards, a flexible parametric approach based on the piecewise exponential model was also adopted in order to obtain smoothed hazard estimates [ 15].
We have studied the effects of changes in minimum early retirement age and in the strictness of employment protection on the hazards from career jobs to gradual and permanent retirement by estimating a discrete competing hazard model with two hazards.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com