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- Propensity score (3)
- Propensity score methods (3)
- Computational Biology/Bioinformatics (2)
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- Observational studies (2)
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- GWAS; imputation; bias; meta-analysis; weight (1)
- Publication
Articles 1 - 17 of 17
Full-Text Articles in Physical Sciences and Mathematics
Time-Dependent Cortical Activation In Voluntary Muscle Contraction, Qi Yang, Xiao-Feng Wang, Yin Fang, Vlodek Siemionow, Wanxiang Yao, Guang H. Yue
Time-Dependent Cortical Activation In Voluntary Muscle Contraction, Qi Yang, Xiao-Feng Wang, Yin Fang, Vlodek Siemionow, Wanxiang Yao, Guang H. Yue
Xiaofeng Wang
This study was to characterize dynamic source strength changes estimated from high-density scalp electroencephalogram (EEG) at different phases of a submaximal voluntary muscle contraction. Eight healthy volunteers performed isometric handgrip contractions of the right arm at 20% maximal intensity. Signals of the handgrip force, electromyography (EMG) from the finger flexor and extensor muscles and 64-channel EEG were acquired simultaneously. Sources of the EEG were analyzed at 19 time points across preparation, execution and sustaining phases of the handgrip. A 3-layer boundary element model (BEM) based on the MNI (Montréal Neurological Institute) brain MRI was used to overlay the sources. A …
The Use Of Imputed Values In The Meta-Analysis Of Genome-Wide Association Studies., Shuo Jiao, Li Hsu, Carolyn Hutter, Ulrike Peters
The Use Of Imputed Values In The Meta-Analysis Of Genome-Wide Association Studies., Shuo Jiao, Li Hsu, Carolyn Hutter, Ulrike Peters
Shuo Jiao
In genome-wide association studies (GWAS), it is a common practice to impute the genotypes of untyped single nucleotide polymorphism (SNP) by exploiting the linkage disequilibrium structure among SNPs. The use of imputed genotypes improves genome coverage and makes it possible to perform meta-analysis combining results from studies genotyped on different platforms. A popular way of using imputed data is the "expectation-substitution" method, which treats the imputed dosage as if it were the true genotype. In current practice, the estimates given by the expectation-substitution method are usually combined using inverse variance weighting (IVM) scheme in meta-analysis. However, the IVM is not …
Meta-Analysis Of New Genome-Wide Association Studies Of Colorectal Cancer Risk.
Meta-Analysis Of New Genome-Wide Association Studies Of Colorectal Cancer Risk.
Shuo Jiao
Colorectal cancer is the second leading cause of cancer death in developed countries. Genome-wide association studies (GWAS) have successfully identified novel susceptibility loci for colorectal cancer. To follow up on these findings, and try to identify novel colorectal cancer susceptibility loci, we present results for GWAS of colorectal cancer (2,906 cases, 3,416 controls) that have not previously published main associations. Specifically, we calculated odds ratios and 95% confidence intervals using log-additive models for each study. In order to improve our power to detect novel colorectal cancer susceptibility loci, we performed a meta-analysis combining the results across studies. We selected the …
Social Marketing, Stages Of Change, And Public Health Smoking Interventions, Paula Diehr
Social Marketing, Stages Of Change, And Public Health Smoking Interventions, Paula Diehr
Paula Diehr
As a "thought experiment," the authors used a modified stages of change model for smoking to define homogeneous segments within various hypothetical populations. The authors then estimated the population effect of public health interventions that targeted the different segments. Under most assumptions, interventions that emphasized primary and secondary prevention, by targeting the Never Smoker, Maintenance, or Action segments, resulted in the highest nonsmoking life expectancy. This result is consistent with both social marketing and public health principles. Although the best thing for an individual smoker is to stop smoking, the greatest public health benefit is achieved by interventions that target …
Prevalence Of Piscine Myocarditis Virus (Pmcv) In Marine Fish Species, Torstein Tengs Dr.
Prevalence Of Piscine Myocarditis Virus (Pmcv) In Marine Fish Species, Torstein Tengs Dr.
Dr. Torstein Tengs
No abstract.
Dose-Finding For Multi-Drug Combinations, Nolan A. Wages
Dose-Finding For Multi-Drug Combinations, Nolan A. Wages
Nolan A. Wages
No abstract provided.
Flexible Distributed Lag Models Using Random Functions With Application To Estimating Mortality Displacement From Heat-Related Deaths, Roger D. Peng, Matthew J. Heaton
Flexible Distributed Lag Models Using Random Functions With Application To Estimating Mortality Displacement From Heat-Related Deaths, Roger D. Peng, Matthew J. Heaton
Roger D. Peng
No abstract provided.
Compound Treatments, Transportability, And The Structural Causal Model: The Power And Simplicity Of Causal Graphs., Maya Petersen
Compound Treatments, Transportability, And The Structural Causal Model: The Power And Simplicity Of Causal Graphs., Maya Petersen
Maya Petersen
No abstract provided.
Generalized Benjamini-Hochberg Procedures Using Spacings, Debashis Ghosh
Generalized Benjamini-Hochberg Procedures Using Spacings, Debashis Ghosh
Debashis Ghosh
For the problem of multiple testing, the Benjamini-Hochberg (B-H) procedure has become a very popular method in applications. We show how the B-H procedure can be interpreted as a test based on the spacings corresponding to the p-value distributions. Using this equivalence, we develop a class of generalized B-H procedures that maintain control of the false discovery rate in finite-samples. We also consider the effect of correlation on the procedure; simulation studies are used to illustrate the methodology.
Software For Assumption Weighting For Meta-Analysis Of Genomic Data, Debashis Ghosh, Yihan Li
Software For Assumption Weighting For Meta-Analysis Of Genomic Data, Debashis Ghosh, Yihan Li
Debashis Ghosh
This is the software that accompanies Li and Ghosh, "Assumption weighting for incorporating heterogeneity into meta-analysis of genomic data."
A Causal Framework For Surrogate Endpoints With Semi-Competing Risks Data, Debashis Ghosh
A Causal Framework For Surrogate Endpoints With Semi-Competing Risks Data, Debashis Ghosh
Debashis Ghosh
In this note, we address the problem of surrogacy using a causal modelling framework that differs substantially from the potential outcomes model that pervades the biostatistical literature. The framework comes from econometrics and conceptualizes direct effects of the surrogate endpoint on the true endpoint. While this framework can incorporate the so-called semi-competing risks data structure, we also derive a fundamental non-identifiability result. Relationships to existing causal modelling frameworks are also discussed.
Propensity Score Modelling In Observational Studies Using Dimension Reduction Methods, Debashis Ghosh
Propensity Score Modelling In Observational Studies Using Dimension Reduction Methods, Debashis Ghosh
Debashis Ghosh
Conditional independence assumptions are very important in causal inference modelling as well as in dimension reduction methodologies. These are two very strikingly different statistical literatures, and we study links between the two in this article. The concept of covariate sufficiency plays an important role, and we provide theoretical justication when dimension reduction and partial least squares methods will allow for valid causal inference to be performed. The methods are illustrated with application to a medical study and to simulated data.
Multilevel Latent Class Models With Dirichlet Mixing Distribution, Chong-Zhi Di, Karen Bandeen-Roche
Multilevel Latent Class Models With Dirichlet Mixing Distribution, Chong-Zhi Di, Karen Bandeen-Roche
Chongzhi Di
Latent class analysis (LCA) and latent class regression (LCR) are widely used for modeling multivariate categorical outcomes in social sciences and biomedical studies. Standard analyses assume data of different respondents to be mutually independent, excluding application of the methods to familial and other designs in which participants are clustered. In this paper, we consider multilevel latent class models, in which sub-population mixing probabilities are treated as random effects that vary among clusters according to a common Dirichlet distribution. We apply the Expectation-Maximization (EM) algorithm for model fitting by maximum likelihood (ML). This approach works well, but is computationally intensive when …
Likelihood Ratio Testing For Admixture Models With Application To Genetic Linkage Analysis, Chong-Zhi Di, Kung-Yee Liang
Likelihood Ratio Testing For Admixture Models With Application To Genetic Linkage Analysis, Chong-Zhi Di, Kung-Yee Liang
Chongzhi Di
We consider likelihood ratio tests (LRT) and their modifications for homogeneity in admixture models. The admixture model is a special case of two component mixture model, where one component is indexed by an unknown parameter while the parameter value for the other component is known. It has been widely used in genetic linkage analysis under heterogeneity, in which the kernel distribution is binomial. For such models, it is long recognized that testing for homogeneity is nonstandard and the LRT statistic does not converge to a conventional 2 distribution. In this paper, we investigate the asymptotic behavior of the LRT for …
Comparing Paired Vs. Non-Paired Statistical Methods Of Analyses When Making Inferences About Absolute Risk Reductions In Propensity-Score Matched Samples., Peter C. Austin
Peter Austin
Propensity-score matching allows one to reduce the effects of treatment-selection bias or confounding when estimating the effects of treatments when using observational data. Some authors have suggested that methods of inference appropriate for independent samples can be used for assessing the statistical significance of treatment effects when using propensity-score matching. Indeed, many authors in the applied medical literature use methods for independent samples when making inferences about treatment effects using propensity-score matched samples. Dichotomous outcomes are common in healthcare research. In this study, we used Monte Carlo simulations to examine the effect on inferences about risk differences (or absolute risk …
Optimal Caliper Widths For Propensity-Score Matching When Estimating Differences In Means And Differences In Proportions In Observational Studies., Peter C. Austin
Optimal Caliper Widths For Propensity-Score Matching When Estimating Differences In Means And Differences In Proportions In Observational Studies., Peter C. Austin
Peter Austin
In a study comparing the effects of two treatments, the propensity score is the probability of assignment to one treatment conditional on a subject's measured baseline covariates. Propensity-score matching is increasingly being used to estimate the effects of exposures using observational data. In the most common implementation of propensity-score matching, pairs of treated and untreated subjects are formed whose propensity scores differ by at most a pre-specified amount (the caliper width). There has been a little research into the optimal caliper width. We conducted an extensive series of Monte Carlo simulations to determine the optimal caliper width for estimating differences …
A Tutorial And Case Study In Propensity Score Analysis: An Application To Estimating The Effect Of In-Hospital Smoking Cessation Counseling On Mortality, Peter C. Austin
A Tutorial And Case Study In Propensity Score Analysis: An Application To Estimating The Effect Of In-Hospital Smoking Cessation Counseling On Mortality, Peter C. Austin
Peter Austin
Propensity score methods allow investigators to estimate causal treatment effects using observational or nonrandomized data. In this article we provide a practical illustration of the appropriate steps in conducting propensity score analyses. For illustrative purposes, we use a sample of current smokers who were discharged alive after being hospitalized with a diagnosis of acute myocardial infarction. The exposure of interest was receipt of smoking cessation counseling prior to hospital discharge and the outcome was mortality with 3 years of hospital discharge. We illustrate the following concepts: first, how to specify the propensity score model; second, how to match treated and …