Monte Carlo Method

Publication Title: 
Journal of Child Psychology and Psychiatry, and Allied Disciplines

BACKGROUND: Genotype x environment interaction (G x E) arises when genes influence sensitivity to the environment. G x E is easily recognized in experimental organisms that permit randomization of genotypes over fixed environmental treatments. Genotype-environment correlation (rGE) arises when genetic effects create or evoke exposure to environmental differences.

Author(s): 
Eaves, Lindon
Silberg, Judy
Erkanli, Alaattin
Publication Title: 
Mathematical biosciences and engineering: MBE

Prisoner's Dilemma is a game theory model used to describe altruistic behavior seen in various populations. This theoretical game is important in understanding why a seemingly selfish strategy does persist and spread throughout a population that is mixing homogeneously at random. For a population with structure determined by social interactions, Prisoner's Dilemma brings to light certain requirements for the altruistic strategy to become established.

Author(s): 
Cameron, Sharon M.
Cintron-Arias, Ariel
Publication Title: 
The American Journal of Tropical Medicine and Hygiene

Artemisinin-based combination therapies (ACTs) are generally regarded as vital in addressing the growing problem posed by the development of antimalarial resistance across sub-Saharan Africa. However, the costs of the new ACTs are likely to be significantly higher than current therapies. Therefore, it is important to examine formally the cost-effectiveness of the more effective yet more expensive ACTs before advocating a switch in policy.

Author(s): 
Coleman, Paul G.
Morel, Chantal
Shillcutt, Sam
Goodman, Catherine
Mills, Anne J.
Publication Title: 
The AAPS journal

Simultaneous modelling of dense and sparse pharmacokinetic data is possible with a population approach. To determine the number of individuals required to detect the effect of a covariate, simulation-based power calculation methodologies can be employed. The Monte Carlo Mapped Power method (a simulation-based power calculation methodology using the likelihood ratio test) was extended in the current study to perform sample size calculations for mixed pharmacokinetic studies (i.e. both sparse and dense data collection).

Author(s): 
Kloprogge, Frank
Simpson, Julie A.
Day, Nicholas P. J.
White, Nicholas J.
Tarning, Joel
Publication Title: 
Statistics in Medicine

In this paper, we develop a Bayesian method for joint analysis of longitudinal measurements and competing risks failure time data. The model allows one to analyze the longitudinal outcome with nonignorable missing data induced by multiple types of events, to analyze survival data with dependent censoring for the key event, and to draw inferences on multiple endpoints simultaneously. Compared with the likelihood approach, the Bayesian method has several advantages. It is computationally more tractable for high-dimensional random effects. It is also convenient to draw inference.

Author(s): 
Hu, Wenhua
Li, Gang
Li, Ning
Publication Title: 
Lifetime Data Analysis

This article studies a general joint model for longitudinal measurements and competing risks survival data. The model consists of a linear mixed effects sub-model for the longitudinal outcome, a proportional cause-specific hazards frailty sub-model for the competing risks survival data, and a regression sub-model for the variance-covariance matrix of the multivariate latent random effects based on a modified Cholesky decomposition.

Author(s): 
Huang, Xin
Li, Gang
Elashoff, Robert M.
Pan, Jianxin
Publication Title: 
Computational and Mathematical Methods in Medicine

This paper develops a new empirical likelihood method for semiparametric linear regression with a completely unknown error distribution and right censored survival data. The method is based on the Buckley-James (1979) estimating equation. It inherits some appealing properties of the complete data empirical likelihood method. For example, it does not require variance estimation which is problematic for the Buckley-James estimator. We also extend our method to incorporate auxiliary information.

Author(s): 
Fang, Kai-Tai
Li, Gang
Lu, Xuyang
Qin, Hong
Publication Title: 
Journal of Manipulative and Physiological Therapeutics

A "Monte Carlo" experiment was performed in order to determine chance concordance rates for multiple test scenarios often encountered in chiropractic diagnosis. The Monte Carlo simulation took into account the following variables: the number of tests involved in the diagnosis; the number of vertebral segments implicated by each test; the proportion of tests in agreement relative to the number of tests performed; and the segmental margin of error accepted.

Author(s): 
Jansen, R. D.
Nansel, D. D.
Publication Title: 
BMJ (Clinical research ed.)

OBJECTIVE: To evaluate the cost effectiveness of acupuncture in the management of persistent non-specific low back pain. DESIGN: Cost effectiveness analysis of a randomised controlled trial. SETTING: Three private acupuncture clinics and 18 general practices in York, England. PARTICIPANTS: 241 adults aged 18-65 with non-specific low back pain of 4-52 weeks' duration. INTERVENTIONS: Ten individualised acupuncture treatments over three months from acupuncturists trained in traditional Chinese medicine (n = 160) or usual care only (n = 81).

Author(s): 
Ratcliffe, J.
Thomas, K. J.
Macpherson, H.
Brazier, J.
Publication Title: 
Medical Physics

As cancer therapy becomes more efficacious and patients survive longer, the potential for late effects increases, including effects induced by radiation dose delivered away from the treatment site. This out-of-field radiation is of particular concern with high-energy radiotherapy, as neutrons are produced in the accelerator head. We recently developed an accurate Monte Carlo model of a Varian 2100 accelerator using MCNPX for calculating the dose away from the treatment field resulting from low-energy therapy.

Author(s): 
Kry, Stephen F.
Titt, Uwe
Followill, David
Pönisch, Falk
Vassiliev, Oleg N.
White, R. Allen
Stovall, Marilyn
Salehpour, Mohammad

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