Economic Design Of X̅ Control Chart Under Double Ewma,
2020
Vikram University Ujjain
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,
2020
The George Washington University
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,
2020
Northern Illinois University
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,
2020
Indiana University Bloomington
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,
2020
Babasaheb Bhimrao Ambedkar University
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,
2020
Rutgers University
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.
A Primer On Statistical Inferences For Finite Populations,
2020
University of Rochester
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.
Almost All Missing Data Are Mnar,
2020
University of Rochester
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.
Jmasm 54: A Comparison Of Four Different Estimation Approaches For Prognostic Survival Oral Cancer Model,
2020
Universiti Sains Malaysia
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,
2020
University of Kashmir, Srinagar, India
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,
2020
University of Kashmir, Srinagar, India
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,
2020
University of North Florida
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,
2020
National College of Business Administration & Economics, Lahore, Pakistan
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,
2020
Baker College
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,
2020
Cihan University-Erbil, Iraq
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,
2020
University of Babylon, Iraq
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,
2020
Cairo University, Cairo, Egypt
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,
2020
Wayne State University
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.
A Generalized Family Of Lifetime Distributions And Survival Models,
2020
Western Carolina University
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.
A Revised Logic Model For Educational Program Evaluation,
2020
Wayne State University School of Medicine
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.
