Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Wayne State University (61)
- University of Windsor (2)
- Claremont Colleges (1)
- Liberty University (1)
- Minnesota State University, Mankato (1)
-
- National University of Uzbekistan (1)
- Olivet Nazarene University (1)
- Southern Methodist University (1)
- Stephen F. Austin State University (1)
- The British University in Egypt (1)
- University of Arkansas, Fayetteville (1)
- University of Denver (1)
- University of Louisville (1)
- University of Nebraska - Lincoln (1)
- University of Nebraska Medical Center (1)
- University of North Florida (1)
- University of Texas Rio Grande Valley (1)
- University of Washington Tacoma (1)
- Western Kentucky University (1)
- Keyword
-
- Binary data (4)
- Statistics (4)
- Bootstrap (3)
- Item response theory (3)
- Logistic regression (3)
-
- Multiple comparisons (3)
- Bayesian (2)
- Bayesian estimation (2)
- Bias (2)
- Binomial distribution (2)
- Categorical data (2)
- Complex survey data (2)
- Confidence interval (2)
- Exponential family (2)
- Heterogeneity (2)
- Logic model (2)
- MCMC (2)
- Markov chain Monte Carlo (2)
- Monte Carlo simulation (2)
- Multicollinearity (2)
- Order statistics (2)
- Participatory evaluation (2)
- Program evaluation (2)
- Regression (2)
- Regression model (2)
- Robust methods (2)
- Small area estimation (2)
- Sports (2)
- Statistical inference (2)
- Trimmed means (2)
- Publication
-
- Journal of Modern Applied Statistical Methods (61)
- Electronic Theses and Dissertations (3)
- Major Papers (2)
- Access*: Interdisciplinary Journal of Student Research and Scholarship (1)
- All Graduate Theses, Dissertations, and Other Capstone Projects (1)
-
- Basic Science Engineering (1)
- Bulletin of National University of Uzbekistan: Mathematics and Natural Sciences (1)
- CMC Senior Theses (1)
- Department of Statistics: Dissertations, Theses, and Student Work (1)
- Graduate Theses and Dissertations (1)
- Masters Theses & Specialist Projects (1)
- PANDION: The Osprey Journal of Research and Ideas (1)
- Pence-Boyce STEM Student Scholarship (1)
- School of Mathematical and Statistical Sciences Faculty Publications and Presentations (1)
- Senior Honors Theses (1)
- Statistical Science Theses and Dissertations (1)
- Theses & Dissertations (1)
- Publication Type
Articles 1 - 30 of 80
Full-Text Articles in Statistics and Probability
Multi-Level Small Area Estimation Based On Calibrated Hierarchical Likelihood Approach Through Bias Correction With Applications To Covid-19 Data, Nirosha Rathnayake
Multi-Level Small Area Estimation Based On Calibrated Hierarchical Likelihood Approach Through Bias Correction With Applications To Covid-19 Data, Nirosha Rathnayake
Theses & Dissertations
Small area estimation (SAE) has been widely used in a variety of applications to draw estimates in geographic domains represented as a metropolitan area, district, county, or state. The direct estimation methods provide accurate estimates when the sample size of study participants within each area unit is sufficiently large, but it might not always be realistic to have large sample sizes of study participants when considering small geographical regions. Meanwhile, high dimensional socio-ecological data exist at the community level, providing an opportunity for model-based estimation by incorporating rich auxiliary information at the individual and area levels. Thus, it is critical …
Confirmative Evaluation: New Cipp Evaluation Model, Tia L. Finney
Confirmative Evaluation: New Cipp Evaluation Model, Tia L. Finney
Journal of Modern Applied Statistical Methods
Struggling trainees often require a substantial investment of time, effort, and resources from medical educators. An emergent challenge involves developing effective ways to accurately identify struggling students and better understand the primary causal factors underlying their poor performance. Identifying the potential reasons for poor performance in medical school is a key first step in developing suitable remediation plans. The SOM Modified Program is a remediation program that aims to ensure academic success for medical students. The purpose of this study is to determine the impact of modifying the CIPP evaluation model by adding a confirmative evaluation step to the model. …
Conditional Distance Correlation Test For Gene Expression Level, Dna Methylation Level And Copy Number, Shanshan Zhang
Conditional Distance Correlation Test For Gene Expression Level, Dna Methylation Level And Copy Number, Shanshan Zhang
Graduate Theses and Dissertations
Over the past years, efforts have been devoted to the genome-wide analysis of genetic and epigenetic profiles to better understand the underlying biological mechanisms of complex diseases such as cancer. It is of great importance to unravel the complex dependence structure between biological factors, and many conditional dependence tests have been developed to meet this need. The traditional partial correlation method can only capture the linear partial correlation, but not the nonlinear correlation. To overcome this limitation, we propose to use the innovative conditional distance correlation (CDC), which measures the conditional dependence between random vectors and detect nonlinear relations. In …
Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das
Statistical Approaches Of Gene Set Analysis With Quantitative Trait Loci For High-Throughput Genomic Studies., Samarendra Das
Electronic Theses and Dissertations
Recently, gene set analysis has become the first choice for gaining insights into the underlying complex biology of diseases through high-throughput genomic studies, such as Microarrays, bulk RNA-Sequencing, single cell RNA-Sequencing, etc. It also reduces the complexity of statistical analysis and enhances the explanatory power of the obtained results. Further, the statistical structure and steps common to these approaches have not yet been comprehensively discussed, which limits their utility. Hence, a comprehensive overview of the available gene set analysis approaches used for different high-throughput genomic studies is provided. The analysis of gene sets is usually carried out based on …
Applying The Data: Predictive Analytics In Sport, Anthony Teeter, Margo Bergman
Applying The Data: Predictive Analytics In Sport, Anthony Teeter, Margo Bergman
Access*: Interdisciplinary Journal of Student Research and Scholarship
The history of wagering predictions and their impact on wide reaching disciplines such as statistics and economics dates to at least the 1700’s, if not before. Predicting the outcomes of sports is a multibillion-dollar business that capitalizes on these tools but is in constant development with the addition of big data analytics methods. Sportsline.com, a popular website for fantasy sports leagues, provides odds predictions in multiple sports, produces proprietary computer models of both winning and losing teams, and provides specific point estimates. To test likely candidates for inclusion in these prediction algorithms, the authors developed a computer model, and test …
Robustness Of The Ewma Sampling Plan To Non-Normality, Uttama Mishra, S. Siddiqui, J. R. Singh
Robustness Of The Ewma Sampling Plan To Non-Normality, Uttama Mishra, S. Siddiqui, J. R. Singh
Journal of Modern Applied Statistical Methods
The effect of non-normality on the OC function of the sampling plan under EWMA is studied by deriving the OC function for a non-normal population represented by the first four terms of an Edgeworth series.
Misguided Opposition To Multiplicity Adjustment Remains A Problem, Andrew V. Frane
Misguided Opposition To Multiplicity Adjustment Remains A Problem, Andrew V. Frane
Journal of Modern Applied Statistical Methods
Fallacious arguments against multiplicity adjustment have been cited with increasing frequency to defend unadjusted tests. These arguments and their enduring impact are discussed in this paper.
Task Interrupted By A Poisson Process, Jarrett Christopher Nantais
Task Interrupted By A Poisson Process, Jarrett Christopher Nantais
Major Papers
We consider a task which has a completion time T (if not interrupted), which is a random variable with probability density function (pdf) f(t), t>0. Before it is complete, the task may be interrupted by a Poisson process with rate lambda. If that happens, then the task must begin again, with the same completion time random variable T, but with a potentially different realization. These interruptions can reoccur, until eventually the task is finished, with a total time of W. In this paper, we will find the Laplace Transform of W in several special cases.
Economic Design Of X̅ Control Chart Under Double Ewma, Manzoor A. Khanday, J. R. Singh
Economic Design Of X̅ Control Chart Under Double Ewma, Manzoor A. Khanday, J. R. Singh
Journal of Modern Applied Statistical Methods
Designing of parameters plays an important role in economic design of control charts for lowering the cost and time. Manipulating sample size (n) and sampling interval (h), the effect of double exponentially weighted moving average (DEWMA) model was studied for the Economic Design (ED) of X̅ control chart. Optimum sizes and level were obtained when the characteristics of an item possesses DEWMA model. When shifts are uncertain the optimal design for DEWMA chart should be more conservative and should be implemented for benefiting the consumers as well as producers.
An Investigation Of Chi-Square And Entropy Based Methods Of Item-Fit Using Item Level Contamination In Item Response Theory, William R. Dardick, Brandi A. Weiss
An Investigation Of Chi-Square And Entropy Based Methods Of Item-Fit Using Item Level Contamination In Item Response Theory, William R. Dardick, Brandi A. Weiss
Journal of Modern Applied Statistical Methods
New variants of entropy as measures of item-fit in item response theory are investigated. Monte Carlo simulation(s) examine aberrant conditions of item-level misfit to evaluate relative (compare EMRj, X2, G2, S-X2, and PV-Q1) and absolute (Type I error and empirical power) performance. EMRj has utility in discovering misfit.
Logistic Regression Under Sparse Data Conditions, David A. Walker, Thomas J. Smith
Logistic Regression Under Sparse Data Conditions, David A. Walker, Thomas J. Smith
Journal of Modern Applied Statistical Methods
The impact of sparse data conditions was examined among one or more predictor variables in logistic regression and assessed the effectiveness of the Firth (1993) procedure in reducing potential parameter estimation bias. Results indicated sparseness in binary predictors introduces bias that is substantial with small sample sizes, and the Firth procedure can effectively correct this bias.
Estimating A Multilevel Model With Complex Survey Data: Demonstration Using Timss, Julie Lorah
Estimating A Multilevel Model With Complex Survey Data: Demonstration Using Timss, Julie Lorah
Journal of Modern Applied Statistical Methods
Analysis of complex survey data is demonstrated for the multilevel model. Description of specific aspects of analysis, including plausible values, sampling weights, and replicate weights is provided. Following this, example TIMSS data and models are described and results are presented.
Concomitant Of Order Statistics From New Bivariate Gompertz Distribution, Sumit Kumar, M. J. S. Khan, Surinder Kumar
Concomitant Of Order Statistics From New Bivariate Gompertz Distribution, Sumit Kumar, M. J. S. Khan, Surinder Kumar
Journal of Modern Applied Statistical Methods
For the new bivariate Gompertz distribution, the expression for probability density function (pdf) of rth order statistics and pdf of concomitant arising from rth order statistics are derived. The properties of concomitant arising from the corresponding order statistics are used to derive these results. The exact expression for moment generating function (mgf) of concomitant of order rth statistics is derived. Also, the mean of concomitant arising from rth order statistics is computed using the mgf of concomitant of rth order statistics, and the exact expression for joint density of concomitant of two non-adjacent order statistics …
Simple Unequal Allocation Procedure For Ranked Set Sampling With Skew Distributions, Dinesh Bhoj, Girish Chandra
Simple Unequal Allocation Procedure For Ranked Set Sampling With Skew Distributions, Dinesh Bhoj, Girish Chandra
Journal of Modern Applied Statistical Methods
A practical unbalanced Ranked Set Sampling (RSS) model is proposed to estimate the population mean of positively skewed distributions. The gains in the relative precisions of the population mean based on the proposed model for chosen distributions are uniformly higher than those based on balanced RSS and the t-model proposed in Kaur et al. (1997). The relative precisions of the simple unequal allocation model are, with one exception, better than (s, t)-model which is better than t-model. The relative precision of the proposed model is very close or equal to the optimal Neyman allocation model.
Almost All Missing Data Are Mnar, Thomas R. Knapp
Almost All Missing Data Are Mnar, Thomas R. Knapp
Journal of Modern Applied Statistical Methods
Rubin (1976, and elsewhere) claimed that there are three kinds of “missingness”: missing completely at random; missing at random; and missing not at random. He gave examples of each. The article that now follows takes an opposing view by arguing that almost all missing data are missing not at random.
A Primer On Statistical Inferences For Finite Populations, Thomas R. Knapp
A Primer On Statistical Inferences For Finite Populations, Thomas R. Knapp
Journal of Modern Applied Statistical Methods
This primer is intended to provide the basic information for sampling without replacement from finite populations.
Jmasm 54: A Comparison Of Four Different Estimation Approaches For Prognostic Survival Oral Cancer Model, Wan Muhamad Amir, Muhammad Azeem, Masitah Hayati Harun, Zalila Ali, Mohamad Shafiq
Jmasm 54: A Comparison Of Four Different Estimation Approaches For Prognostic Survival Oral Cancer Model, Wan Muhamad Amir, Muhammad Azeem, Masitah Hayati Harun, Zalila Ali, Mohamad Shafiq
Journal of Modern Applied Statistical Methods
Four types of estimation approaches for prognostic survival oral cancer model building are considered via a SAS algorithm: Efron’s Method, Exact Method, Breslow’s Method, and Discrete Method. Each method is illustrated separately and compared according to their coefficient parameter. An approach is considered by adding a bootstrapping technique for each handling ties method and a complete SAS algorithm is supplied for each proposed method, including methods for handling ties.
A New Two-Parametric ‘Useful’ Fuzzy Information Measure And Its Properties, Saima Manzoor Sofi, Safina Peerzada, Mirza Abdul Khalique Baig
A New Two-Parametric ‘Useful’ Fuzzy Information Measure And Its Properties, Saima Manzoor Sofi, Safina Peerzada, Mirza Abdul Khalique Baig
Journal of Modern Applied Statistical Methods
A ‘useful’ fuzzy measure of order α and type β is developed. Its validity established with a numerical example.
A New Two Parametric Weighted Generalized Entropy For Lifetime Distributions, Bilal Ahmad Bhat, Mirza Abdul Khaliq Baig
A New Two Parametric Weighted Generalized Entropy For Lifetime Distributions, Bilal Ahmad Bhat, Mirza Abdul Khaliq Baig
Journal of Modern Applied Statistical Methods
The concept of weighted generalized entropy and its dynamic residual (version) is developed. The general expressions of these two uncertainty measures corresponding to some well-known lifetime distributions are derived. It is shown that the proposed dynamic entropy determines the survival function uniquely. Some significant properties and inequalities of this dynamic entropy are also discussed.
Uniform Random Variate Generation With The Linear Congruential Method, Joseph Free
Uniform Random Variate Generation With The Linear Congruential Method, Joseph Free
PANDION: The Osprey Journal of Research and Ideas
This report considers the issue of using a specific linear congruential generator (LCG) to create random variates from the uniform(0,1) distribution. The LCG is used to generate multiple samples of pseudo-random numbers and statistical computation techniques are used to assess whether those samples could have resulted from a uniform(0,1) distribution. Source code is included with this report in the appendix along with annotations.
Even Order Ranked Set Sampling With Auxiliary Variable, Muhammad Tayyab, Muhammad Noor Ul-Amin, Muhammad Hanif
Even Order Ranked Set Sampling With Auxiliary Variable, Muhammad Tayyab, Muhammad Noor Ul-Amin, Muhammad Hanif
Journal of Modern Applied Statistical Methods
Even order ranked set sampling (EORSS) is a novel proposed ranked set sampling scheme connected with an auxiliary variable correlated with the study variable. This scheme quantifies only the one sampling unit which is at even position from each ranking set by employing specific criteria. The performance of the ratio estimator under EORSS is compared to its contemporary estimators in simple random sampling (SRS), ranked set sampling (RSS), median ranked set sampling (MRSS) and quartile ranked set sampling (QRSS) exploiting the same number of quantified units. The simulation results proved that EORSS is an efficient alternative sampling scheme for ratio …
Objectives Driven Participatory Evaluation Model, Dustin R. Saalman
Objectives Driven Participatory Evaluation Model, Dustin R. Saalman
Journal of Modern Applied Statistical Methods
The ability to complete program evaluations of educational programming is typically restricted by the availability of resources, such as time, money and a trained evaluator. Although not a replacement for trained evaluators, promoting evaluative capacity and evaluative thinking within an organization can help mitigate this gap between talent and resources. Participatory evaluation is purported to increase organizational learning and promote evaluative thinking within an organization (Cousins & Whitmore, 1998). Objectives oriented evaluation is an easily understood evaluation method which provides a refined focus program outcome (Madaus & Stufflebeam, 1989). Using an internal evaluation of a new faculty onboarding course at …
Maximum Likelihood Estimations Based On Upper Record Values For Probability Density Function And Cumulative Distribution Function In Exponential Family And Investigating Some Of Their Properties, Saman Hosseini, Parviz Nasiri, Sharad Damodar Gore
Maximum Likelihood Estimations Based On Upper Record Values For Probability Density Function And Cumulative Distribution Function In Exponential Family And Investigating Some Of Their Properties, Saman Hosseini, Parviz Nasiri, Sharad Damodar Gore
Journal of Modern Applied Statistical Methods
A useful subfamily of the exponential family is considered. The ML estimation based on upper record values are calculated for the parameter, Cumulative Density Function, and Probability Density Function of the subfamily. The relationship between MLE based on record values and a random sample are discussed, along with some properties of these estimators, and its utility is shown for large samples.
The Comparison Between Maximum Weighted And Trimmed Likelihood Estimator Of The Simple Circular Regression Model, Ehab A. Mahmood, Habshah Midi, Abdul Ghapor Hussin
The Comparison Between Maximum Weighted And Trimmed Likelihood Estimator Of The Simple Circular Regression Model, Ehab A. Mahmood, Habshah Midi, Abdul Ghapor Hussin
Journal of Modern Applied Statistical Methods
The Maximum Likelihood Estimator (MLE) was used to estimate unknown parameters of the simple circular regression model. However, it is very sensitive to outliers in data set. A robust method to estimate model parameters is proposed.
Bayesian Estimation Of The Parameters Of Discrete Weibull Type (I) Distribution, Samir Kamel Ashour, Mohamed Salem Abdelwahab Muiftah
Bayesian Estimation Of The Parameters Of Discrete Weibull Type (I) Distribution, Samir Kamel Ashour, Mohamed Salem Abdelwahab Muiftah
Journal of Modern Applied Statistical Methods
Bayesian estimation of the continuous Weibull distribution parameters was studied by Ahmad and Ahmad (2013) under the assumption of knowing the shape parameter. Bayesian estimates are considered here of the parameters of the discrete Weibull Type I [DW(I)] distribution and are obtained under two different assumptions: when the shape parameter is known, and when both parameters are independent random variables. A Mathcad program is performed to simulate data from the DW(I) distribution considering different values of the parameters and different sample sizes, and to obtain Bayesian parameter estimates. The resulted estimates are compared to the ML and proportion estimates obtained …
The Logic Model, Participatory Evaluation And Out Of School Art Programs, Kimberly A. Kleinhans
The Logic Model, Participatory Evaluation And Out Of School Art Programs, Kimberly A. Kleinhans
Journal of Modern Applied Statistical Methods
The logic model and participatory evaluation are two popular methods of conducting program evaluation. Although both methods have their strengths, each has distinct weaknesses which can be ameliorated by combining them both together. The combined method is used to evaluate an out of school art program at a museum. Using both the logic model and participatory evaluation yielded beneficial results with more accurate representation of program outcomes.
Jmasm 52: Extremely Efficient Permutation And Bootstrap Hypothesis Tests Using R, Christina Chatzipantsiou, Marios Dimitriadis, Manos Papadakis, Michail Tsagris
Jmasm 52: Extremely Efficient Permutation And Bootstrap Hypothesis Tests Using R, Christina Chatzipantsiou, Marios Dimitriadis, Manos Papadakis, Michail Tsagris
Journal of Modern Applied Statistical Methods
Re-sampling based statistical tests are known to be computationally heavy, but reliable when small sample sizes are available. Despite their nice theoretical properties not much effort has been put to make them efficient. Computationally efficient method for calculating permutation-based p-values for the Pearson correlation coefficient and two independent samples t-test are proposed. The method is general and can be applied to other similar two sample mean or two mean vectors cases.
Identifying Which Of J Independent Binomial Distributions Has The Largest Probability Of Success, Rand Wilcox
Identifying Which Of J Independent Binomial Distributions Has The Largest Probability Of Success, Rand Wilcox
Journal of Modern Applied Statistical Methods
Let p1,…, pJ denote the probability of a success for J independent random variables having a binomial distribution and let p(1) ≤ … ≤ p(J) denote these probabilities written in ascending order. The goal is to make a decision about which group has the largest probability of a success, p(J). Let p̂1,…, p̂J denote estimates of p1,…,pJ, respectively. The strategy is to test J − 1 hypotheses comparing the group with the largest estimate to each of the J − 1 …
Empirical Comparison Of Tests For One-Factor Anova Under Heterogeneity And Non-Normality: A Monte Carlo Study, Diep Nguyen, Eunsook Kim, Yan Wang, Thanh Vinh Pham, Yi-Hsin Chen, Jeffrey D. Kromrey
Empirical Comparison Of Tests For One-Factor Anova Under Heterogeneity And Non-Normality: A Monte Carlo Study, Diep Nguyen, Eunsook Kim, Yan Wang, Thanh Vinh Pham, Yi-Hsin Chen, Jeffrey D. Kromrey
Journal of Modern Applied Statistical Methods
Although the Analysis of Variance (ANOVA) F test is one of the most popular statistical tools to compare group means, it is sensitive to violations of the homogeneity of variance (HOV) assumption. This simulation study examines the performance of thirteen tests in one-factor ANOVA models in terms of their Type I error rate and statistical power under numerous (82,080) conditions. The results show that when HOV was satisfied, the ANOVA F or the Brown-Forsythe test outperformed the other methods in terms of both Type I error control and statistical power even under non-normality. When HOV was violated, the Structured Means …
A Generalized Family Of Lifetime Distributions And Survival Models, Mahmoud Aldeni, Felix Famoye, Carl Lee
A Generalized Family Of Lifetime Distributions And Survival Models, Mahmoud Aldeni, Felix Famoye, Carl Lee
Journal of Modern Applied Statistical Methods
In lifetime data, the hazard function is a common technique for describing the characteristics of lifetime distribution. Monotone increasing or decreasing, and unimodal are relatively simple hazard function shapes, which can be modeled by many parametric lifetime distributions. However, fewer distributions are capable of modeling diverse and more complicated shapes such as N-shaped, reflected N-shaped, W-shaped, and M-shaped hazard rate functions. A generalized family of lifetime distributions, the uniform-R{generalized lambda} (U-R{GL}) are introduced and the corresponding survival models are derived, and applied to two lifetime data sets. The survival model is applied to a right censored lifetime data set.