Analyzing the Robustness of Semi-Parametric Duration Models for the Study of Repeated Events

2014 ◽  
Vol 22 (2) ◽  
pp. 183-204 ◽  
Author(s):  
Janet M. Box-Steffensmeier ◽  
Suzanna Linn ◽  
Corwin D. Smidt
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Time Dependence ◽  
Frailty Model ◽  
Duration Models ◽  
Sample Sizes ◽  
Know How ◽  
Data Limitations ◽  
Repeated Events ◽  
Event Dependence

Estimators within the Cox family are often used to estimate models for repeated events. Yet, there is much we still do not know about the performance of these estimators. In particular, we do not know how they perform given time dependence, different censoring rates, and a varying number of events and sample sizes. We use Monte Carlo simulations to demonstrate the performance of a variety of popular semi-parametric estimators as these data aspects change and under conditions of event dependence and heterogeneity, both, or neither. We conclude that the conditional frailty model outperforms other standard estimators under a wide array of data-generating processes, and data limitations rarely alter its performance.

Event Dependence and Heterogeneity in Duration Models: The Conditional Frailty Model

2007 ◽  
Vol 15 (3) ◽  
pp. 237-256 ◽  
Author(s):  
Janet M. Box-Steffensmeier ◽  
Suzanna De Boef ◽  
Kyle A. Joyce
Keyword(s):  
Political Science ◽  
State Policy ◽  
Frailty Model ◽  
Event History ◽  
Duration Models ◽  
Terrorist Attacks ◽  
Repeated Events ◽  
Event Dependence ◽  
State Policy Adoption ◽  
Event Times

We introduce the conditional frailty model, an event history model that separates and accounts for both event dependence and heterogeneity in repeated events processes. Event dependence and heterogeneity create within-subject correlation in event times thereby violating the assumptions of standard event history models. Simulations show the advantage of the conditional frailty model. Specifically they demonstrate the model's ability to disentangle the sources of within-subject correlation as well as the gains in both efficiency and bias of the model when compared to the widely used alternatives, which often produce conflicting conclusions. Two substantive political science problems illustrate the usefulness and interpretation of the model: state policy adoption and terrorist attacks.

scholarly journals Performance of the Beta-Binomial Model for Clustered Binary Responses: Comparison with Generalized Estimating Equations

2021 ◽  
Vol 19 (1) ◽  
pp. 2-25
Author(s):  
Seongah Im
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Generalized Estimating Equations ◽  
Estimating Equations ◽  
Small Sample ◽  
Binomial Model ◽  
Sample Sizes ◽  
Binary Responses ◽  
Large Sample ◽  
Generalized Estimating

This study examined performance of the beta-binomial model in comparison with GEE using clustered binary responses resulting in non-normal outcomes. Monte Carlo simulations were performed under varying intracluster correlations and sample sizes. The results showed that the beta-binomial model performed better for small sample, while GEE performed well under large sample.

Time Dependence of the Segregation of Diffusing Solute in Nanocrystalline Materials

2002 ◽  
Vol 731 ◽  
Author(s):  
Irina V Belova ◽  
Graeme E Murch
Keyword(s):  
Monte Carlo ◽  
Grain Boundary ◽  
Monte Carlo Simulations ◽  
Time Dependence ◽  
Nanocrystalline Materials ◽  
Diffusion Length ◽  
Solute Diffusion ◽  
Reasonable Approximation ◽  
Solute Diffusivity ◽  
First Time

AbstractAt long times the effective solute diffusivity can be described by the (modified) Hart-Mortlock and Maxwell-Garnett equations for diffusion parallel and perpendicular to the grain boundary respectively. In this paper we analyze for the first time the time dependence of the effective solute diffusivity for these conditions. We assume that there are local regions (delineated by the diffusion length) in the grains adjacent to the grain boundary where the solute is equilibrated with the grain boundary. We write equations for the effective solute diffusivity with this assumption. Comparison with Monte Carlo simulations shows that this is quite a reasonable approximation for solute diffusion parallel to the grain boundary. For diffusion perpendicular to the grain boundary it is only a fair approximation unless the segregation is weak.

scholarly journals Smoothed Maximum Score Estimation of Discrete Duration Models

2019 ◽  
Vol 12 (2) ◽  
pp. 64 ◽  
Author(s):  
Sadat Reza ◽  
Paul Rilstone
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Discrete Time ◽  
Hazard Rate ◽  
Duration Models ◽  
Finite Sample ◽  
Time Duration ◽  
Maximum Score ◽  
Finite Sample Properties ◽  
Error Distributions

This paper extends Horowitz’s smoothed maximum score estimator to discrete-time duration models. The estimator’s consistency and asymptotic distribution are derived. Monte Carlo simulations using various data generating processes with varying error distributions and shapes of the hazard rate are conducted to examine the finite sample properties of the estimator. The bias-corrected estimator performs reasonably well for the models considered with moderately-sized samples.

Specifying Weights in Spatial Forecasting Models: The Results of Some Experiments

1982 ◽  
Vol 14 (5) ◽  
pp. 571-584 ◽  
Author(s):  
F Stetzer
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Weight Function ◽  
Effective Area ◽  
Space Time ◽  
Distance Decay ◽  
Model Parameters ◽  
Sample Sizes ◽  
Forecasting Models ◽  
Estimation Of Model Parameters

The application of space-time forecasting models requires the specification of a set of place-to-place weights. The existing literature contains several recommendations for this specification. By a series of Monte Carlo simulations, various weighting rules are compared in terms of estimation of model parameters and accuracy of forecasts. It is shown that specification of the weights is important, especially when sample sizes are small and the data autocorrelated. Generally, the effective area of the weight function is more important than its distance decay.

scholarly journals An Exact and a Monte Carlo Proposal to the Fisher–Pitman Permutation Tests for Paired Replicates and for Independent Samples

2007 ◽  
Vol 7 (3) ◽  
pp. 402-412 ◽  
Author(s):  
Johannes Kaiser
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Permutation Tests ◽  
Rank Test ◽  
Interval Scale ◽  
Exact Tests ◽  
Sample Sizes ◽  
Signed Rank ◽  
Wilcoxon Signed Rank Test ◽  
Signed Rank Test

This article concerns the nonparametric Fisher–Pitman tests for paired replicates and independent samples. After outlining the theory of exact tests, I derive Monte Carlo simulations for both of them. Simulations can be useful if one deals with many observations because of the complexity of the algorithms in regard to sample sizes. The tests are designed to be a more powerful alternative to the Wilcoxon signed-rank test and the Wilcoxon–Mann–Whitney rank-sum test if the observations are given on at least an interval scale. The results gained by Monte Carlo versions of the tests are accurate enough in comparison to the exact versions. Finally, I give examples for using both supplemented tests.

Low-voltage EDS of magnesium ferrite Dendrites in a FEG-SEM

1996 ◽  
Vol 54 ◽  
pp. 478-479
Author(s):  
Matthew T. Johnson ◽  
Ian M. Anderson ◽  
Jim Bentley ◽  
C. Barry Carter
Keyword(s):  
Monte Carlo ◽  
Quantitative Analysis ◽  
Monte Carlo Simulations ◽  
Cross Section ◽  
Spatial Resolution ◽  
Low Voltage ◽  
Magnesium Ferrite ◽  
X Ray ◽  
Interaction Volume ◽  
Ferrite Spinel

Energy-dispersive X-ray spectrometry (EDS) performed at low (≤ 5 kV) accelerating voltages in the SEM has the potential for providing quantitative microanalytical information with a spatial resolution of ∼100 nm. In the present work, EDS analyses were performed on magnesium ferrite spinel [(MgxFe1−x)Fe2O4] dendrites embedded in a MgO matrix, as shown in Fig. 1. spatial resolution of X-ray microanalysis at conventional accelerating voltages is insufficient for the quantitative analysis of these dendrites, which have widths of the order of a few hundred nanometers, without deconvolution of contributions from the MgO matrix. However, Monte Carlo simulations indicate that the interaction volume for MgFe2O4 is ∼150 nm at 3 kV accelerating voltage and therefore sufficient to analyze the dendrites without matrix contributions.Single-crystal {001}-oriented MgO was reacted with hematite (Fe2O3) powder for 6 h at 1450°C in air and furnace cooled. The specimen was then cleaved to expose a clean cross-section suitable for microanalysis.

MONTE CARLO SIMULATIONS OF ELECTRON DRIFT VELOCITIES IN THE NOBLE GASES AND THEIR MIXTURES

1979 ◽  
Vol 40 (C7) ◽  
pp. C7-63-C7-64
Author(s):  
A. J. Davies ◽  
J. Dutton ◽  
C. J. Evans ◽  
A. Goodings ◽  
P.K. Stewart
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Simulations ◽  
Noble Gases ◽  
Electron Drift
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