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Articles 1 - 30 of 104
Full-Text Articles in Physical Sciences and Mathematics
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. …
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.
Integrated Cyberattack Detection And Resilient Control Strategies Using Lyapunov-Based Economic Model Predictive Control, Henrique Oyama, Helen Durand
Integrated Cyberattack Detection And Resilient Control Strategies Using Lyapunov-Based Economic Model Predictive Control, Henrique Oyama, Helen Durand
Chemical Engineering and Materials Science Faculty Research Publications
The use of an integrated system framework, characterized by numerous cyber/physical components (sensor measurements, signals to actuators) connected through wired/wireless networks, has not only increased the ability to control industrial systems, but also the vulnerabilities to cyberattacks. State measurement cyberattacks could pose threats to process control systems since feedback control may be lost if the attack policy is not thwarted. Motivated by this, we propose three detection concepts based on Lyapunov‐based economic model predictive control (LEMPC) for nonlinear systems. The first approach utilizes randomized modifications to an LEMPC formulation online to potentially detect cyberattacks. The second method detects attacks when …
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 …
Integrated Borehole, Radar, And Seismic Velocity Analysis Reveals Dynamic Spatial Variations Within A Firn Aquifer In Southeast Greenland, S. F. Killingbeck, N. C. Schmerr, L. N. Montgomery, A. D. Booth, P. W. Livermore, J. Guandique, O. L. Miller, S. Burdick, R. R. Forster, L. S. Koenig, A. Legchenko, S. R. M. Ligtenberg, C. Miège, D. K. Solomon, L. J. West
Integrated Borehole, Radar, And Seismic Velocity Analysis Reveals Dynamic Spatial Variations Within A Firn Aquifer In Southeast Greenland, S. F. Killingbeck, N. C. Schmerr, L. N. Montgomery, A. D. Booth, P. W. Livermore, J. Guandique, O. L. Miller, S. Burdick, R. R. Forster, L. S. Koenig, A. Legchenko, S. R. M. Ligtenberg, C. Miège, D. K. Solomon, L. J. West
Environmental Science and Geology Faculty Research Publications
Perennial water storage in firn aquifers has been observed within the lower percolation zone of the southeast Greenland ice sheet. Spatially distributed seismic and radar observations, made ~50 km upstream of the Helheim Glacier terminus, reveal spatial variations of seismic velocity within a firn aquifer. From 1.65 to 1.8 km elevation, shear-wave velocity (Vs) is 1,290 ± 180 m/s in the unsaturated firn, decreasing below the water table (~15 m depth) to 1,130 ± 250 m/s. Below 1.65 km elevation, Vs in the saturated firn is 1,270 ± 220 m/s. The compressional-to-shear velocity ratio decreases in the downstream saturated zone, …
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.
Direct P-Wave Anisotropy Measurements At Homestake Mine: Implications For Wave Propagation In Continental Crust, James Atterholt, Sarah J. Brownlee, Gary L. Pavlis
Direct P-Wave Anisotropy Measurements At Homestake Mine: Implications For Wave Propagation In Continental Crust, James Atterholt, Sarah J. Brownlee, Gary L. Pavlis
Environmental Science and Geology Faculty Research Publications
We measured anisotropic seismic properties of schists of the Homestake Formation located at a depth of 1478 m in the Sanford Underground Research Facility (SURF) in the Black Hills of South Dakota, USA. We deployed a 24-element linear array of three-component geophones in an area in the Homestake Mine called 19-ledge. An airless jackhammer source was used to shoot two profiles: (1) a walkaway survey to appraise any distance dependence and (2) a fan shot profile to measure variations with azimuth. Slowness estimates from the fan shot profile show a statistically significant deviation with azimuth with the expected 180° variation …
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.
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 …
A Framework For Aquatic Invasive Species Surveillance Site Selection And Prioritization In The Us Waters Of The Laurentian Great Lakes, Andrew J. Tucker, W. Lindsay Chadderton, Gust Annis, Alisha D. Davidson, Joel Hoffman, Jon Bossenbroek, Stephen Hensler, Michael Hoff, Erika Jensen, Donna R. Kashian, Sarah Lesage, Timothy Strakosh
A Framework For Aquatic Invasive Species Surveillance Site Selection And Prioritization In The Us Waters Of The Laurentian Great Lakes, Andrew J. Tucker, W. Lindsay Chadderton, Gust Annis, Alisha D. Davidson, Joel Hoffman, Jon Bossenbroek, Stephen Hensler, Michael Hoff, Erika Jensen, Donna R. Kashian, Sarah Lesage, Timothy Strakosh
Environmental Science and Geology Faculty Research Publications
Risk-based prioritization for early detection monitoring is of utmost importance to prevent and mitigate invasive species impacts and is especially needed for large ecosystems where management resources are not sufficient to survey all locations susceptible to invasion. In this paper we describe a spatially-explicit and quantitative approach for identifying the highest risk sites for aquatic invasive species (AIS) introduction into the United States’ waters of the Laurentian Great Lakes, a vast inland sea with a surface area of 246,049 square km and a shoreline length of 16,431 km. We compiled data from geospatial metrics available across all of the US …
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.
Forward And Backward Continuation Ratio Models For Ordinal Response Variables, Xing Liu, Haiyan Bai
Forward And Backward Continuation Ratio Models For Ordinal Response Variables, Xing Liu, Haiyan Bai
Journal of Modern Applied Statistical Methods
There are different types of continuation ratio (CR) models for ordinal response variables. The different model equations, corresponding parameterizations, and nonequivalent results are confusing. The purpose of this study is to introduce different types of forward and backward CR models, demonstrate how to implement these models using Stata, and compare the results using data from the Educational Longitudinal Study of 2002 (ELS:2002).
A Revised Logic Model For Educational Program Evaluation, Zsa-Zsa Booker
A Revised Logic Model For Educational Program Evaluation, Zsa-Zsa Booker
Journal of Modern Applied Statistical Methods
The logic model is an evaluation tool popularly used for obtaining grant funding. Its limitations make it unlike other theory driven evaluation methods. A critical examination of the logic model leads to the construction of an enriched revised logic model.