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Statistical Methods in Medical Research

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https://www.readbyqxmd.com/read/29984639/a-method-to-account-for-covariate-specific-treatment-effects-when-estimating-biomarker-associations-in-the-presence-of-endogenous-medication-use
#1
Andrew J Spieker, Joseph Ac Delaney, Robyn L McClelland
In the modern era, cardiovascular biomarkers are often measured in the presence of medication use, such that the observed biomarker value for the treated participants is different than their underlying natural history value. However, for certain predictors (e.g. age, gender, and genetic exposures) the observed biomarker value is not of primary interest. Rather, we are interested in estimating the association between these predictors and the natural history of the biomarker that would have occurred in the absence of treatment...
August 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29984638/a-bayesian-hierarchical-model-for-demand-curve-analysis
#2
Yen-Yi Ho, Tien Nhu Vo, Haitao Chu, Mark G LeSage, Xianghua Luo, Chap T Le
Drug self-administration experiments are a frequently used approach to assess the abuse liability and reinforcing property of a compound. It has been used to assess the abuse liabilities of various substances such as psychomotor stimulants and hallucinogens, food, nicotine, and alcohol. The demand curve generated from a self-administration study describes how demand of a drug or non-drug reinforcer varies as a function of price. With the approval of the 2009 Family Smoking Prevention and Tobacco Control Act, demand curve analysis provides crucial evidence to inform the US Food and Drug Administration's policy on tobacco regulation because it produces several important quantitative measurements to assess the reinforcing strength of nicotine...
August 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29984637/variable-selection-in-rank-regression-for-analyzing-longitudinal-data
#3
Liya Fu, You-Gan Wang
In this paper, we consider variable selection in rank regression models for longitudinal data. To obtain both robustness and effective selection of important covariates, we propose incorporating shrinkage by adaptive lasso or SCAD in the Wilcoxon dispersion function and establishing the oracle properties of the new method. The new method can be conveniently implemented with the statistical software R. The performance of the proposed method is demonstrated via simulation studies. Finally, two datasets are analyzed for illustration...
August 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29984636/new-expectation-maximization-type-algorithms-via-stochastic-representation-for-the-analysis-of-truncated-normal-data-with-applications-in-biomedicine
#4
Guo-Liang Tian, Da Ju, Kam Chuen Yuen, Chi Zhang
To analyze univariate truncated normal data, in this paper, we stochastically represent the normal random variable as a mixture of a truncated normal random variable and its complementary random variable. This stochastic representation is a new idea and it is the first time to appear in literature. According to this stochastic representation, we derive important distributional properties for the truncated normal distribution and develop two new expectation-maximization algorithms to calculate the maximum likelihood estimates of parameters of interest for Type I data (without and with covariates) and Type II/III data...
August 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29984635/beta-binomial-analysis-of-variance-model-for-network-meta-analysis-of-diagnostic-test-accuracy-data
#5
Victoria N Nyaga, Marc Arbyn, Marc Aerts
There are several generalized linear mixed models to combine direct and indirect evidence on several diagnostic tests from related but independent diagnostic studies simultaneously also known as network meta-analysis. The popularity of these models is due to the attractive features of the normal distribution and the availability of statistical software to obtain parameter estimates. However, modeling the latent sensitivity and specificity using the normal distribution after transformation is neither natural nor computationally convenient...
August 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29984634/hybrid-copula-mixed-models-for-combining-case-control-and-cohort-studies-in-meta-analysis-of-diagnostic-tests
#6
Aristidis K Nikoloulopoulos
Copula mixed models for trivariate (or bivariate) meta-analysis of diagnostic test accuracy studies accounting (or not) for disease prevalence have been proposed in the biostatistics literature to synthesize information. However, many systematic reviews often include case-control and cohort studies, so one can either focus on the bivariate meta-analysis of the case-control studies or the trivariate meta-analysis of the cohort studies, as only the latter contains information on disease prevalence. In order to remedy this situation of wasting data we propose a hybrid copula mixed model via a combination of the bivariate and trivariate copula mixed model for the data from the case-control studies and cohort studies, respectively...
August 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29984633/bayesian-negative-binomial-family-based-multistate-markov-model-for-the-evaluation-of-periodic-population-based-cancer-screening-considering-incomplete-information-and-measurement-errors
#7
Chen-Yang Hsu, Ming-Fang Yen, Anssi Auvinen, Yueh-Hsia Chiu, Hsiu-Hsi Chen
Population-based cancer screening is often asked but hardly addressed by a question: "How many rounds of screening are required before identifying a cancer of interest staying in the pre-clinical detectable phase (PCDP)?" and also a similar one related to the number of screens required for stopping screening for the low risk group. It can be answered by using longitudinal follow-up data on repeated rounds of screen, namely periodic screen, but such kind of data are rather complicated and fraught with intractable statistical properties including correlated multistate outcomes, unobserved and incomplete (censoring or truncation) information, and imperfect measurements...
August 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29846150/fitting-mechanistic-epidemic-models-to-data-a-comparison-of-simple-markov-chain-monte-carlo-approaches
#8
Michael Li, Jonathan Dushoff, Benjamin M Bolker
Simple mechanistic epidemic models are widely used for forecasting and parameter estimation of infectious diseases based on noisy case reporting data. Despite the widespread application of models to emerging infectious diseases, we know little about the comparative performance of standard computational-statistical frameworks in these contexts. Here we build a simple stochastic, discrete-time, discrete-state epidemic model with both process and observation error and use it to characterize the effectiveness of different flavours of Bayesian Markov chain Monte Carlo (MCMC) techniques...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29846149/modern-statistical-tools-for-inference-and-prediction-of-infectious-diseases-using-mathematical-models
#9
Itai Dattner, Amit Huppert
No abstract text is available yet for this article.
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29846148/modeling-the-spread-of-middle-east-respiratory-syndrome-coronavirus-in-saudi-arabia
#10
Qianying Lin, Alice Py Chiu, Shi Zhao, Daihai He
Middle East respiratory syndrome coronavirus has been persistent in the Middle East region since 2012. Abundant scientific evidence showed that dromedary camels are the primary host of the virus. Majority of human cases (i.e., 75% or 88%) are due to human-to-human transmission, while the others are due to camel-to-human transmission. Mathematical modeling of Middle East respiratory syndrome coronavirus camel-to-camel transmission was lacking. Using the plug-and-play likelihood-based inference framework, we fitted a susceptible-exposed-infectious-recovered-susceptible model of camels to the reported human cases with a constant proportion of human cases from camels (i...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29846147/a-bayesian-hierarchical-model-for-demand-curve-analysis
#11
Yen-Yi Ho, Tien Nhu Vo, Haitao Chu, Xianghua Luo, Chap T Le
Drug self-administration experiments are a frequently used approach to assessing the abuse liability and reinforcing property of a compound. It has been used to assess the abuse liabilities of various substances such as psychomotor stimulants and hallucinogens, food, nicotine, and alcohol. The demand curve generated from a self-administration study describes how demand of a drug or non-drug reinforcer varies as a function of price. With the approval of the 2009 Family Smoking Prevention and Tobacco Control Act, demand curve analysis provides crucial evidence to inform the US Food and Drug Administration's policy on tobacco regulation, because it produces several important quantitative measurements to assess the reinforcing strength of nicotine...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29846146/non-parametric-estimation-of-transition-probabilities-in-non-markov-multi-state-models-the-landmark-aalen-johansen-estimator
#12
Hein Putter, Cristian Spitoni
The topic non-parametric estimation of transition probabilities in non-Markov multi-state models has seen a remarkable surge of activity recently. Two recent papers have used the idea of subsampling in this context. The first paper, by de Uña Álvarez and Meira-Machado, uses a procedure based on (differences between) Kaplan-Meier estimators derived from a subset of the data consisting of all subjects observed to be in the given state at the given time. The second, by Titman, derived estimators of transition probabilities that are consistent in general non-Markov multi-state models...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29846145/on-the-comparison-of-risk-of-death-according-to-different-stages-of-breast-cancer-via-the-long-term-exponentiated-weibull-hazard-model
#13
Hayala Cristina Cavenague de Souza, Gleici da Silva Castro Perdoná, Francisco Louzada, Fernanda Maris Peria
Long-term survivor models have been extensively used for modelling time-to-event data with a significant proportion of patients who do not experience poor outcome. In this paper, we propose a new long-term survivor hazard model, which accommodates comprehensive families of cure rate models as particular cases, including modified Weibull, exponentiated Weibull, Weibull, exponential and Rayleigh distribution, among others. The maximum likelihood estimation procedure is presented. A simulation study evaluates bias and mean square error of the considered estimation procedure as well as the coverage probabilities of the parameters asymptotic and bootstrap confidence intervals...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29846144/group-based-multi-trajectory-modeling
#14
Daniel S Nagin, Bobby L Jones, Valéria Lima Passos, Richard E Tremblay
Identifying and monitoring multiple disease biomarkers and other clinically important factors affecting the course of a disease, behavior or health status is of great clinical relevance. Yet conventional statistical practice generally falls far short of taking full advantage of the information available in multivariate longitudinal data for tracking the course of the outcome of interest. We demonstrate a method called multi-trajectory modeling that is designed to overcome this limitation. The method is a generalization of group-based trajectory modeling...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29846143/a-big-data-pipeline-identifying-dynamic-gene-regulatory-networks-from-time-course-gene-expression-omnibus-data-with-applications-to-influenza-infection
#15
Michelle Carey, Juan Camilo Ramírez, Shuang Wu, Hulin Wu
A biological host response to an external stimulus or intervention such as a disease or infection is a dynamic process, which is regulated by an intricate network of many genes and their products. Understanding the dynamics of this gene regulatory network allows us to infer the mechanisms involved in a host response to an external stimulus, and hence aids the discovery of biomarkers of phenotype and biological function. In this article, we propose a modeling/analysis pipeline for dynamic gene expression data, called Pipeline4DGEData, which consists of a series of statistical modeling techniques to construct dynamic gene regulatory networks from the large volumes of high-dimensional time-course gene expression data that are freely available in the Gene Expression Omnibus repository...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29512437/profile-likelihood-based-analyses-of-infectious-disease-models
#16
Christian Tönsing, Jens Timmer, Clemens Kreutz
Ordinary differential equation models are frequently applied to describe the temporal evolution of epidemics. However, ordinary differential equation models are also utilized in other scientific fields. We summarize and transfer state-of-the art approaches from other fields like Systems Biology to infectious disease models. For this purpose, we use a simple SIR model with data from an influenza outbreak at an English boarding school in 1978 and a more complex model of a vector-borne disease with data from the Zika virus outbreak in Colombia in 2015-2016...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/29260611/a-two-stage-approach-for-estimating-the-parameters-of-an-age-group-epidemic-model-from-incidence-data
#17
Rami Yaari, Itai Dattner, Amit Huppert
Age-dependent dynamics is an important characteristic of many infectious diseases. Age-group epidemic models describe the infection dynamics in different age-groups by allowing to set distinct parameter values for each. However, such models are highly nonlinear and may have a large number of unknown parameters. Thus, parameter estimation of age-group models, while becoming a fundamental issue for both the scientific study and policy making in infectious diseases, is not a trivial task in practice. In this paper, we examine the estimation of the so-called next-generation matrix using incidence data of a single entire outbreak, and extend the approach to deal with recurring outbreaks...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/28571521/estimating-age-specific-reproductive-numbers-a-comparison-of-methods
#18
Carlee B Moser, Laura F White
Large outbreaks, such as those caused by influenza, put a strain on resources necessary for their control. In particular, children have been shown to play a key role in influenza transmission during recent outbreaks, and targeted interventions, such as school closures, could positively impact the course of emerging epidemics. As an outbreak is unfolding, it is important to be able to estimate reproductive numbers that incorporate this heterogeneity and to use surveillance data that is routinely collected to more effectively target interventions and obtain an accurate understanding of transmission dynamics...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/27899706/mixed-hidden-markov-quantile-regression-models-for-longitudinal-data-with-possibly-incomplete-sequences
#19
Maria Francesca Marino, Nikos Tzavidis, Marco Alfò
Quantile regression provides a detailed and robust picture of the distribution of a response variable, conditional on a set of observed covariates. Recently, it has be been extended to the analysis of longitudinal continuous outcomes using either time-constant or time-varying random parameters. However, in real-life data, we frequently observe both temporal shocks in the overall trend and individual-specific heterogeneity in model parameters. A benchmark dataset on HIV progression gives a clear example. Here, the evolution of the CD4 log counts exhibits both sudden temporal changes in the overall trend and heterogeneity in the effect of the time since seroconversion on the response dynamics...
July 2018: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/27885051/linear-rank-testing-of-a-non-binary-responder-analysis-efficacy-score-to-evaluate-pharmacotherapies-for-substance-use-disorders
#20
Tyson H Holmes, Shou-Hua Li, David J McCann
The design of pharmacological trials for management of substance use disorders is shifting toward outcomes of successful individual-level behavior (abstinence or no heavy use). While binary success/failure analyses are common, McCann and Li (CNS Neurosci Ther 2012; 18: 414-418) introduced "number of beyond-threshold weeks of success" (NOBWOS) scores to avoid dichotomized outcomes. NOBWOS scoring employs an efficacy "hurdle" with values reflecting duration of success. Here, we evaluate NOBWOS scores rigorously...
July 2018: Statistical Methods in Medical Research
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