International Journal of Clinical Biostatistics and Biometrics is an international, peer reviewed, open access journal on conceptual, constructive, experimental, computational, investigational, or theoretical work in all areas of biostatistics and biometrics. The Journal provides the authors with a great platform for publication of their work and for the exchange of their ideas. We aim to publish highest quality clinical content via open access platform providing the readers without charge, immediate and unlimited access.
International Journal of Clinical Biostatistics and Biometrics publishes articles on Data Modeling, Bayesian Probability, Bioinformatic Methods, Biological Experimental Data Modeling, Biostatistic Theory and Methods, Climate and Environmental Data Modeling, Clinical Study Design and Analysis, Clinical Trials and Assessment Methods, Computational Biology, Distribution and Modeling of Disease Dynamics, Epidemiological Data Modeling and Analysis, Evolution and Population Genetics, Genetics and Genetic Epidemiology, Health Services Research and Assessment, Mathematical Biology, Medical Imaging Data Modeling, Pain Management Anesthesia, Public Health and Healthcare Evaluation, Public Health Policy Research, Statistical Computation and Applications, etc. All articles published in the journal are subject to a rigorous peer review process.
Journal Information
Title: International Journal of Clinical Biostatistics and Biometrics
ISSN: 2469-5831
Editor-in-chief: James Michael Hardin
NLM title abbreviation: Int J Clin Biostat Biom
ISO abbreviation: Int J Clin Biostat Biom
Other titles: IJCBB
Category: Public health/Biological Science
DOI: 10.23937/2469-5831
Peer review: Double blind
Review speed: 3 weeks
Fast-track review: 10 days
Publication format (s): Electronic and print
Publication policy: Open Access; COPE guide
Publication type(s): Periodicals
Publisher: ClinMed International Library
Country of publication: USA
Language: English
Contact email: contact@clinmedjournals.org
Articles Search by Keyword | Journal title | Author name | DOI
Open Access DOI:10.23937/2469-5831/1510022 A Heteroscedastic Accelerated Failure Time Model for Survival Analysis Yifan Wang, Tian You and Martin Lysy Article Type: Original Research | First Published: July 03, 2019 Nonparametric and semiparametric methods are commonly used in survival analysis to mitigate the bias due to model misspecification. However, such methods often cannot estimate upper-tail survival quantiles when a sizable proportion of the data are censored, in which case parametric likelihood-based estimators present a viable alternative. In this article, we extend a popular family of parametric survival models which make the Accelerated Failure Time (AFT) assumption to account for heteroscedast...
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Open Access DOI:10.23937/2469-5831/1510021 Dejian Lai, Ahmed A Arif, Haiyun Xu and George L Delclos Article Type: Original Research article | First Published: April 29, 2019 Statistical classification analysis has been widely used in many fields. In this article, we applied and compared three different classification procedures: Logistic regression, Fisher''s linear discriminant function and the second order Bahadur representation to two datasets from two surveys on asthma among healthcare professional in Texas. The first dataset contained 102 subjects and the second dataset 2963. The concordance of the classification from the three statistical procedures with possi...
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Open Access DOI:10.23937/2469-5831/1510020 An Approximation of a Longitudinal Stochastic Model Khalid A Salah Article Type: Research Article | First Published: March 25, 2019 We propose to approximate a model for repeated measures that incorporated random effects, correlated stochastic process and measurements error. The stochastic process used in this paper is the Integrated Ornstein-Uhlenbeck (IOU) process. We consider a Bayesian approach which is motivated by the complexity of the model, thus, we propose to approximate the IOU stochastic process into a continuous spatial model that constructed by convolving a very simple and independent, process with a kernel func...
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Open Access DOI:10.23937/2469-5831/1510019 Xiaoyong Wu, Jayesh P Rai, Guohua Yan, Srivastava DK and Shesh N Rai Article Type: RESEARCH ARTICLE | First Published: March 04, 2019 Assessing the performance of diagnostic tests for repeated binary measurements is very important in clinical trials and diagnostic medicine. The gastric-emptying studies involve 4-hourly measurements of emptying. Empirical results suggest that the gastric emptying results over time are correlated and therefore failure to consider the correlation in statistical measures may not produce satisfactory assessments. If these measurements are highly correlated/associated, early gastric emptying can be ...
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Open Access DOI:10.23937/2469-5831/1510018 Hai Zhu, Mary Akosile, Shuqin Zhang, Nils P Johnson, Dejian Lai and Hongjian Zhu Article Type: Research Article | First Published: July 28, 2018 Right heart catheterization (RHC) is a well-established diagnostic tool for patients with congenital and acquired right heart disease and to actively monitor critically ill patients in the intensive care unit. Notably, previous randomized controlled trials and observational studies provide limited support for the clinical utilization of RHC in critically ill patients. However, traditional statistical methods incorporating propensity scores rely heavily on potentially invalid parametric assumptio...
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Open Access DOI:10.23937/2469-5831/1510017 Partial Variable Selection and its Applications in Biostatistics Jingwen Gu, Ao Yuan, Chunxiao Zhou, Leighton Chan and Ming T Tan Article Type: Research Article | First Published: April 14, 2018 We propose and study a method for partial covariates selection, which only select the covariates with values fall in their effective ranges. The coefficients estimates based on the resulting data is more interpretable based on the effective covariates. This is in contrast to the existing method of variable selection, in which some variables are selected/deleted in whole. To test the validity of the partial variable selection, we extended the Wilks theorem to handle this case. Simulation studies ...
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Open Access DOI:10.23937/2469-5831/1510016 Improved Wald Test for Equivalence Assessment of Analytical Biosimilarity Yu-Ting Weng, Yi Tsong, Meiyu Shen and Chao Wang Article Type: Research Article | First Published: March 15, 2018 The equivalence test in analytical similarity assessment uses a margin of 1.5 times of the standard deviation of a reference product. In the current practice, the standard deviation, estimated from study data, is considered as a fixed constantin the margin....
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Open Access DOI:10.23937/2469-5831/1510015 Analogs of the Wilcoxon-Mann-Whitney Test When There is a Covariate Rand R Wilcox Article Type: Research Article | First Published: December 22, 2017  Certainly the best-known method for making inferences about p is the Wilcoxon-Mann-Whitney (WMW) test. It is well known, however, that under general conditions, the WMW method uses an incorrect estimate of the standard error. Numerous methods have been derived for dealing with this issue....
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Open Access DOI:10.23937/2469-5831/1510014 Ke-Sheng Wang, Ying Liu, Shaoqing Gong, Chun Xu, Xin Xie, Liang Wang and Xingguang Luo Article Type: Research Article | First Published: December 01, 2017  Alzheimer's Disease (AD), the most common form of dementia, is a chronic neurodegenerative disease. The HECT domain and ankyrin repeat containing E3 ubiquitin protein ligase 1 (HACE1) gene is expressed in human brain and may play a role in the pathogenesis of neurodegenerative disorders....
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Open Access DOI:10.23937/2469-5831/1510013 On Sample Size Calculation for Exact Group Sequential Tests for Rare Disease Man Jin and James L Kepner Article Type: Research Article | First Published: October 09, 2017  For a rare disease, all the patients having the disease constitute a small population, and the standard single-stage hypergeometric test is uniformly most powerful to evaluate the response probability of a specific treatment regimen....
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Open Access DOI:10.23937/2469-5831/1510012 A Systematic Approach to Increase Reproducibility in Simulation Studies Xiaoyong Wu and Shesh N Rai Article Type: Research Article | First Published: October 07, 2017  Reproducibility of results in simulation studies plays a key role in statistical science. Although P-value occupies a prominent place for determining statistical significance in replicate studies, there is always possibility of extra variability across samples leading to irreproducible results. Recently, Halsey, et al....
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Open Access DOI:10.23937/2469-5831/1510011 Can We Identify Patients at High Risk of Harm under a Generally Safe Intervention? Gerd K Rosenkranz Article Type: Research Article | First Published: September 23, 2017  Personalized medicine today is primarily addressing efficacy. Here we investigate and illustrate the role that precision medicine could play in drug safety by supporting the identification of subjects at high risk of harm by an otherwise safe and efficacious treatment. Predicting potential harm requires high sensitivity of a classification rule....
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Open Access DOI:10.23937/2469-5831/1510010 Inference Based on Small Randomized Oncology Clinical Trials: Is the Observed Treatment Effect True? Joyce Cheng, Hui Zhang, Shenghui Tang and Rajeshwari Sridhara Article Type: Original Article | First Published: May 20, 2017  The drug development paradigm in oncology has changed in recent times as developments in science and technology have led to more targeted therapies. Drug products are receiving marketing approvals based on single randomized studies enrolling 100-200 patients, including early phase (phase II) clinical trials....
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Open Access DOI:10.23937/2469-5831/1510009 Hierarchical Bayes Approach for Analysis of Item-Level Missing Data Junshan Qiu and Ram Tiwari Article Type: Research Article | First Published: June 30, 2016  Missing data are primarily due to dropout which can be categorized into different types based on its relation to the response process. For simplicity, it is generally assumed that the relation between a specific type of dropout and the response process can be described using a single (indicator) random variable. In case of distinct types of dropout, it is natural to use the multinomial indicator variables to model the dropout....
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Open Access DOI:10.23937/2469-5831/1510008 A Constrained Non-inferiority Approach for Assessing Clinical Efficacy to Establish Biosimilarity Jason JZ Liao Article Type: Research Article | First Published: December 3, 2015  To develop a biosimilar product, it is necessary to demonstrate biosimilarity between the proposed biosimilar product and the reference product in terms of the purity, potency, efficacy, and safety. In this paper, clinical efficacy data required for establishing biosimilarity are considered. Non-inferiority (NI) and equivalence methods are commonly used for analyzing clinical trials to meet this requirement. The equivalence approach often require...
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Open Access DOI:10.23937/2469-5831/1510007 Target Frequency Analysis of functional MRI Data Michael A. Frolich, Paul Jung and Shannon Starr Article Type: Research Article | First Published: November 2, 2015  The field of functional magnetic resonance imaging (fMRI) has grown in usage, applications, and complexity. The results of a general linear model (GLM) analysis vary from one investigator to another as they depend on image preprocessing, model choices and physiological assumptions. There is a need for a simple, efficient and consistent analysis method. Methods: We propose the target frequency analysis (TFA) as an intuitive, computationally effici...
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Open Access DOI:10.23937/2469-5831/1510006 Noise Analysis of Gene Regulatory Networks Using Particle Filter Haixin Wang and Dawit Aberra Article Type: Original Article | First Published: October 03, 2015  One of the most important properties in gene expression is the stochasticity. Gene expression process is noisy and fluctuant. In this paper, the noise of gene regulatory networks (GRNs) using polynomial model and S-system model is analyzed by proposed approach on the basis of particle filter. The measurement noise and process noise are analyzed to test noise effects on the synthetic GRNs. The relation among Root Mean Square (RMS) error, measureme...
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Open Access DOI:10.23937/2469-5831/1510005 Douglas D Gunzler, James C Spilsbury, Michael Fu, Susannah Rose, Neal V Dawson, Shirley Moore and Thomas E Love Article Type: Original Article | First Published: September 28, 2015  As institutions and funders expand their efforts toward multi-disciplinary, interdisciplinary, and even transdisciplinary research, there is a substantial need for scientists who can lead such efforts. The traditional image of a leader of transdisciplinary clinical research is a quantitatively savvy clinician conducting research at some point along the continuum from the 'bench to the bedside'. However, this is not the only alternative. Nonclinic...
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Open Access DOI:10.23937/2469-5831/1510004 Bayesian Survival Analysis of Genetic Variants in PTPRN2 Gene for Age at Onset of Cancer Ke-Sheng Wang, Yue Pan, Weize Wang and Chun Xu Article Type: Research Article | First Published: September 9, 2015  The protein tyrosine phosphatase, receptor type, N polypeptide 2 (PTPRN2) gene may play a role in cancer; however, no study has focused on the associations of genetic variants within the PTPRN2 gene with age at onset (AAO) of cancer. Methods: This study examined 220 single nucleotide polymorphisms (SNPs) within the PTPRN2 gene in the Marshfield sample with 716 cancer cases (any diagnosed cancer, excluding minor skin cancer) and 2,848 non-cancer c...
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Open Access DOI:10.23937/2469-5831/1510003 Emil N. Coman, L. Suzanne Suggs, Maria Coman and Eugen Iordache and Judith Fifield Article Type: Review Article | First Published: September 4, 2015  We provide a comprehensive review of simple and advanced statistical analyses using an intuitive visual approach explicitly modeling Latent Variables (LV), likely to better illuminate what is assumed in each analytical method and what is actually estimated, by translating the causal relationships embedded in the graphical models in equation form. We recommend the graphical display rooted in the century old path analysis, that details all paramete...
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Open Access DOI:10.23937/2469-5831/1510002 Drug Treatment Comparison for Total Knee Replacement Surgery Kevin Soderholm and Rhonda Magel Article Type: Research Article | First Published: September 02, 2015  Data from over 2000 patients receiving knee replacement surgery was gathered from a hospital system in the Midwestern United States. The age group that each patient belonged to was noted, under age 65 or 65 years of age and older, as well as their gender. A variety of drugs in each of three drug categories was studied as to their association with total hospital cost, length of stay, prevalence of early readmissions and prevalence of blood transfu...
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Open Access DOI:10.23937/2469-5831/1510001 Dynamic Factor Analysis for Multivariate Time Series: An Application to Cognitive Trajectories Yorghos Tripodis and Nikolaos Zirogiannis Article Type: Research Article | First Published: August 28, 2015  We propose a dynamic factor model appropriate for large epidemiological studies and develop an estimation algorithm which can handle datasets with large number of subjects and short temporal information. The algorithm uses a two cycle iterative approach for parameter estimation in such a large dataset. Each iteration consists of two distinct cycles, both following an EM algorithm approach. This iterative process will continue until convergence is...
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