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Articles 31 - 60 of 1115
Full-Text Articles in Social and Behavioral Sciences
Two Different Classes Of Shrinkage Estimators For The Scale Parameter Of The Rayleigh Distribution, Talha Omer, Zawar Hussain, Muhammad Qasim, Said Farooq Shah, Akbar Ali Khan
Two Different Classes Of Shrinkage Estimators For The Scale Parameter Of The Rayleigh Distribution, Talha Omer, Zawar Hussain, Muhammad Qasim, Said Farooq Shah, Akbar Ali Khan
Journal of Modern Applied Statistical Methods
Shrinkage estimators are introduced for the scale parameter of the Rayleigh distribution by using two different shrinkage techniques. The mean squared error properties of the proposed estimator have been derived. The comparison of proposed classes of the estimators is made with the respective conventional unbiased estimators by means of mean squared error in the simulation study. Simulation results show that the proposed shrinkage estimators yield smaller mean squared error than the existence of unbiased estimators.
A Simple Random Sampling Modified Dual To Product Estimator For Estimating Population Mean Using Order Statistics, Sanjay Kumar, Priyanka Chhaparwal
A Simple Random Sampling Modified Dual To Product Estimator For Estimating Population Mean Using Order Statistics, Sanjay Kumar, Priyanka Chhaparwal
Journal of Modern Applied Statistical Methods
Bandopadhyaya (1980) developed a dual to product estimator using robust modified maximum likelihood estimators (MMLE’s). Their properties were obtained theoretically and supported through simulations studies with generated as well as one real data set. Robustness properties in the presence of outliers and confidence intervals were studied.
Extending Singh-Maddala Distribution, Mohamed Ali Ahmed
Extending Singh-Maddala Distribution, Mohamed Ali Ahmed
Journal of Modern Applied Statistical Methods
A new distribution, the exponentiated transmuted Singh-Maddala distribution (ETSM), is presented, and three important special distributions are illustrated. Some mathematical properties are obtained, and parameters estimation method is applied using maximum likelihood. Illustrations based on random numbers and a real data set are given.
How To Apply Multiple Imputation In Propensity Score Matching With Partially Observed Confounders: A Simulation Study And Practical Recommendations, Albee Ling, Maria Montez-Rath, Maya Mathur, Kris Kapphahn, Manisha Desai
How To Apply Multiple Imputation In Propensity Score Matching With Partially Observed Confounders: A Simulation Study And Practical Recommendations, Albee Ling, Maria Montez-Rath, Maya Mathur, Kris Kapphahn, Manisha Desai
Journal of Modern Applied Statistical Methods
Propensity score matching (PSM) has been widely used to mitigate confounding in observational studies, although complications arise when the covariates used to estimate the PS are only partially observed. Multiple imputation (MI) is a potential solution for handling missing covariates in the estimation of the PS. However, it is not clear how to best apply MI strategies in the context of PSM. We conducted a simulation study to compare the performances of popular non-MI missing data methods and various MI-based strategies under different missing data mechanisms. We found that commonly applied missing data methods resulted in biased and inefficient estimates, …
A New Right-Skewed Upside Down Bathtub Shaped Heavy-Tailed Distribution And Its Applications, Sandeep Kumar Maurya, Sanjay K. Singh, Umesh Singh
A New Right-Skewed Upside Down Bathtub Shaped Heavy-Tailed Distribution And Its Applications, Sandeep Kumar Maurya, Sanjay K. Singh, Umesh Singh
Journal of Modern Applied Statistical Methods
A one parameter right skewed, upside down bathtub type, heavy-tailed distribution is derived. Various statistical properties and maximum likelihood approaches for estimation purpose are studied. Five different real data sets with four different models are considered to illustrate the suitability of the proposed model.
On The Level Of Precision Of A Heterogeneous Transfer Function In A Statistical Neural Network Model, Christopher Godwin Udomboso
On The Level Of Precision Of A Heterogeneous Transfer Function In A Statistical Neural Network Model, Christopher Godwin Udomboso
Journal of Modern Applied Statistical Methods
A heterogeneous function of the statistical neural network is presented from two transfer functions: symmetric saturated linear and hyperbolic tangent sigmoid. The precision of the derived heterogeneous model over their respective homogeneous forms are established, both at increased sample sizes hidden neurons. Results further show the sensitivity of the heterogeneous model to increase in hidden neurons.
Vif-Regression Screening Ultrahigh Dimensional Feature Space, Hassan S. Uraibi
Vif-Regression Screening Ultrahigh Dimensional Feature Space, Hassan S. Uraibi
Journal of Modern Applied Statistical Methods
Iterative Sure Independent Screening (ISIS) was proposed for the problem of variable selection with ultrahigh dimensional feature space. Unfortunately, the ISIS method transforms the dimensionality of features from ultrahigh to ultra-low and may result in un-reliable inference when the number of important variables particularly is greater than the screening threshold. The proposed method has transformed the ultrahigh dimensionality of features to high dimension space in order to remedy of losing some information by ISIS method. The proposed method is compared with ISIS method by using real data and simulation. The results show this method is more efficient and more reliable …
A New Generalized Family Of Distributions For Lifetime Data, Maha A. D. Aldahlan, Mohamed G. Khalil, Ahmed Z. Afify
A New Generalized Family Of Distributions For Lifetime Data, Maha A. D. Aldahlan, Mohamed G. Khalil, Ahmed Z. Afify
Journal of Modern Applied Statistical Methods
A new class of continuous distributions called the generalized Burr X-G family is introduced. Some special models of the new family are provided. Some of its mathematical properties including explicit expressions for the quantile and generating functions, ordinary and incomplete moments, order statistics and Rényi entropy are derived. The maximum likelihood is used for estimating the model parameters. The flexibility of the generated family is illustrated by means of two applications to real data sets.
Jmasm 57: Bayesian Survival Analysis Of Lomax Family Models With Stan (R), Mohammed H. A. Abujarad, Athar Ali Khan
Jmasm 57: Bayesian Survival Analysis Of Lomax Family Models With Stan (R), Mohammed H. A. Abujarad, Athar Ali Khan
Journal of Modern Applied Statistical Methods
An attempt is made to fit three distributions, the Lomax, exponential Lomax, and Weibull Lomax to implement Bayesian methods to analyze Myeloma patients using Stan. This model is applied to a real survival censored data so that all the concepts and computations will be around the same data. A code was developed and improved to implement censored mechanism throughout using rstan. Furthermore, parallel simulation tools are also implemented with an extensive use of rstan.
Inference For Step-Stress Partially Accelerated Life Test Model With An Adaptive Type-I Progressively Hybrid Censored Data, Showkat Ahmad Lone, Ahmadur Rahman, Tanveer A. Tarray
Inference For Step-Stress Partially Accelerated Life Test Model With An Adaptive Type-I Progressively Hybrid Censored Data, Showkat Ahmad Lone, Ahmadur Rahman, Tanveer A. Tarray
Journal of Modern Applied Statistical Methods
Consider estimating data of failure times under step-stress partially accelerated life tests based on adaptive Type-I hybrid censoring. The mathematical model related to the lifetime of the test units is assumed to follow Rayleigh distribution. The point and interval maximum-likelihood estimations are obtained for distribution parameter and tampering coefficient. Also, the work is conducted under a traditional Type-I hybrid censoring plan (scheme). A Monte Carlo simulation algorithm is used to evaluate and compare the performances of the estimators of the tempering coefficient and model parameters under both progressively hybrid censoring plans. The comparison is carried out on the basis of …
Fourth Down Decision Making: Challenging The Conservative Nature Of Nfl Coaches, Will Palmquist, Ryan Elmore, Benjamin Williams
Fourth Down Decision Making: Challenging The Conservative Nature Of Nfl Coaches, Will Palmquist, Ryan Elmore, Benjamin Williams
DU Undergraduate Research Journal Archive
This thesis analyzes the hypothesis that coaches in the National Football League are often too conservative in their decision making on fourth downs. I used R Studio and NFL play-by-play data to simulate actual football plays and drives according to different fourth down strategies. By measuring expected points per drive over thousands of simulated drives, we are able to evaluate the effectiveness of different fourth down strategies. This research points to a number of conclusions regarding the nature of NFL coaches on fourth downs as well as the complexity of modeling and simulating decision making in a complex sport such …
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. …
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.
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.
High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner
High Wind Alerts: A System Created With Observations From The X-Band Teaching And Research Radar, Lauren Warner
The Journal of Purdue Undergraduate Research
Following the August 13, 2011, Indiana State Fair stage collapse tragedy, caused by a wind gust from an approaching thunderstorm, Purdue University enforced a wind speed restriction of 30 mph (13 m s-1) for tents at outdoor events. During these events, volunteers stand outside with handheld anemometers, measuring and reporting when the wind speeds exceed this limit. In this study, we report testing of a new system to automate high-wind alerts based on observations from a Doppler radar, the X-band Teaching and Research Radar (XTRRA), near Purdue’s campus. XTRRA scans over campus at low elevations approximately every 5 minutes. Using …
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.