Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing: Author Response To Peer Comments,
2013
Bowling Green State University
Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing: Author Response To Peer Comments, Richard B. Anderson
Journal of Modern Applied Statistical Methods
Richard Anderson responds to comments regarding his target article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.
Estimation Of Variance Using Known Coefficient Of Variation And Median Of An Auxiliary Variable,
2013
Pondicherry University
Estimation Of Variance Using Known Coefficient Of Variation And Median Of An Auxiliary Variable, J. Subramani, G. Kumarapandiyan
Journal of Modern Applied Statistical Methods
A modified ratio type variance estimator for estimating population variance of a study variable when the population median and coefficient of variation of an auxiliary variable are known is proposed. The bias and mean squared error of the proposed estimator are derived and conditions under which the proposed estimator performs better than the traditional ratio type variance estimators and modified ratio type variance estimators are obtained. Using a numerical study results show that the proposed estimator performs better than the traditional ratio type variance estimator and existing modified ratio type variance estimators.
Priorities In Thurstone Scaling And Steady-State Probabilities In Markov Stochastic Modeling,
2013
GfK Custom Research North America, Minneapolis, MN
Priorities In Thurstone Scaling And Steady-State Probabilities In Markov Stochastic Modeling, Stan Lipovetsky
Journal of Modern Applied Statistical Methods
Thurstone scaling is widely used in marketing and advertising research where various methods of applied psychology are utilized. This article considers several analytical tools useful for positioning a set of items on a Thurstone scale via regression modeling and Markov stochastic processing in the form of Chapman-Kolmogorov equations. These approaches produce interval and ratio scales of preferences and enrich the possibilities of paired comparison estimation applied for solving practical problems of prioritization and probability of choice modeling.
On The Gamma-Half Normal Distribution And Its Applications,
2013
Austin Peay State University, Clarksville, TN
On The Gamma-Half Normal Distribution And Its Applications, Ayman Alzaatreh, Kristen Knight
Journal of Modern Applied Statistical Methods
A new distribution, the gamma-half normal distribution, is proposed and studied. Various structural properties of the gamma-half normal distribution are derived. The shape of the distribution may be unimodal or bimodal. Results for moments, limit behavior, mean deviations and Shannon entropy are provided. To estimate the model parameters, the method of maximum likelihood estimation is proposed. Three real-life data sets are used to illustrate the applicability of the gamma-half normal distribution.
The Length-Biased Versus Random Sampling For The Binomial And Poisson Events,
2013
Wright State University
The Length-Biased Versus Random Sampling For The Binomial And Poisson Events, Makarand V. Ratnaparkhi, Uttara V. Naik-Nimbalkar
Journal of Modern Applied Statistical Methods
The equivalence between the length-biased and the random sampling on a non-negative, discrete random variable is established. The length-biased versions of the binomial and Poisson distributions are discussed.
Improved Estimators In Finite Population Surveys: Theory And Applications,
2013
SOSU, Indian Statistical Institute - Kolkata
Improved Estimators In Finite Population Surveys: Theory And Applications, Sunil Kumar
Journal of Modern Applied Statistical Methods
Improved estimators are proposed for estimating the population mean Y̅ of the study variable y using auxiliary variable x in simple random sampling. Explicit expression for the bias and MSE of the proposed family are derived to the first order of approximation. The proposed estimators are compared with other estimators and theoretical findings are illustrated by two numerical examples.
An Approach For Dealing With Statuses Of Non-Statistically Significant Interactions Between Treatments,
2013
Cotton Research Institute, Giza, Egypt
An Approach For Dealing With Statuses Of Non-Statistically Significant Interactions Between Treatments, Zakaria M. Sawan
Journal of Modern Applied Statistical Methods
A field experiment on cotton yield resulted in a non-statistically significant interaction. An approach for follow-up examination between treatments based on least significant difference values was suggested to identify the effect regardless of insignificance. It was found that the classical formula used in calculating the significance of interactions suffers a possible shortage that can be eliminated by applying a suggested revision.
Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing,
2013
Bowling Green State University
Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing, Richard B. Anderson
Journal of Modern Applied Statistical Methods
To counter past assertions that permutation testing is not distribution-free, this article clarifies that the critical p value (alpha) in permutation testing is not a Type I error rate and that a test's validity is independent of the concept of Type I error.
A Response To Anderson's (2013) Conceptual Distinction Between The Critical P Value And Type I Error Rate In Permutation Testing,
2013
University of Padova, Italy
A Response To Anderson's (2013) Conceptual Distinction Between The Critical P Value And Type I Error Rate In Permutation Testing, Fortunato Pesarin, Stefano Bonnini
Journal of Modern Applied Statistical Methods
Pesarin and Bonnini respond to Anderson's (2013) Conceptual Distinction between the Critical p value and Type I Error Rate in Permutation Testing
A Monte Carlo Simulation Of The Robust Rank-Order Test Under Various Population Symmetry Conditions,
2013
University of Wisconsin - Whitewater
A Monte Carlo Simulation Of The Robust Rank-Order Test Under Various Population Symmetry Conditions, William T. Mickelson
Journal of Modern Applied Statistical Methods
The Type I Error Rate of the Robust Rank Order test under various population symmetry conditions is explored through Monte Carlo simulation. Findings indicate the test has difficulty controlling Type I error under generalized Behrens-Fisher conditions for moderately sized samples.
Constructing A More Powerful Test In Two-Level Block Randomized Designs,
2013
Michigan State University
Constructing A More Powerful Test In Two-Level Block Randomized Designs, Spyros Konstantopoulos
Journal of Modern Applied Statistical Methods
A more powerful test is proposed for the treatment effect in two-level block randomized designs where random assignment takes place at the first level. When clustering at the second level is assumed to be known, the proposed test produces higher estimates of power than the typical test.
Bayesian Inference Of Pair-Copula Constriction For Multivariate Dependency Modeling Of Iran’S Macroeconomic Variables,
2013
ShahidChamran University, Ahvaz, Iran
Bayesian Inference Of Pair-Copula Constriction For Multivariate Dependency Modeling Of Iran’S Macroeconomic Variables, M. R. Zadkarami, O. Chatrabgoun
Journal of Modern Applied Statistical Methods
Bayesian inference of pair-copula constriction (PCC) is used for multivariate dependency modeling of Iran’s macroeconomics variables: oil revenue, economic growth, total consumption and investment. These constructions are based on bivariate t-copulas as building blocks and can model the nature of extreme events in bivariate margins individually. The model parameter was estimated based on Markov chain Monte Carlo (MCMC) methods. A MCMC algorithm reveals unconditional as well as conditional independence in Iran’s macroeconomic variables, which can simplify resulting PCC’s for these data.
Using The Bootstrap For Estimating The Sample Size In Statistical Experiments,
2013
University of Dayton
Using The Bootstrap For Estimating The Sample Size In Statistical Experiments, Maher Qumsiyeh
Journal of Modern Applied Statistical Methods
Efron’s (1979) Bootstrap has been shown to be an effective method for statistical estimation and testing. It provides better estimates than normal approximations for studentized means, least square estimates and many other statistics of interest. It can be used to select the active factors - factors that have an effect on the response - in experimental designs. This article shows that the bootstrap can be used to determine sample size or the number of runs required to achieve a certain confidence level in statistical experiments.
The X-Alter Algorithm: A Parameter-Free Method Of Unsupervised Clustering,
2013
Université of Nice Sophia-Antipolis, Nice, France
The X-Alter Algorithm: A Parameter-Free Method Of Unsupervised Clustering, Thomas Laloë, Rémi Servien
Journal of Modern Applied Statistical Methods
Using quantization techniques, Laloë (2010) defined a new clustering algorithm called Alter. This L1-based algorithm is shown to be convergent but suffers two major flaws. The number of clusters, K, must be supplied by the user and the computational cost is high. This article adapts the X-means algorithm (Pelleg & Moore, 2000) to solve both problems.
Estimating Heterogeneous Intra-Class Correlation Coefficients In Dyadic Ecological Momentary Assessment,
2013
Boston Children’s Hospital, Department of Pediatrics, Harvard Medical School
Estimating Heterogeneous Intra-Class Correlation Coefficients In Dyadic Ecological Momentary Assessment, Emily A. Blood, Leslie A. Kalish, Lydia A. Shrier
Journal of Modern Applied Statistical Methods
A method is described for estimating and testing predictors for influence on the variance of momentary behaviors in dyadic ecological momentary assessment data. Results show that the method allows intraclass correlations of momentary observations from two members of the same couple to vary by observation-level, individual-level and couple-level predictors.
Jmasm 32: Multiple Imputation Of Missing Multilevel, Longitudinal Data: A Case When Practical Considerations Trump Best Practices?,
2013
University of British Columbia
Jmasm 32: Multiple Imputation Of Missing Multilevel, Longitudinal Data: A Case When Practical Considerations Trump Best Practices?, Jennifer E. V. Lloyd, Jelena Obradović, Richard M. Carpiano, Frosso Motti-Stefanidi
Journal of Modern Applied Statistical Methods
A pedagogical tool is presented for applied researchers dealing with incomplete multilevel, longitudinal data. It explains why such data pose special challenges regarding missingness. Syntax created to perform a multiply-imputed growth modeling procedure in Stata Version 11 (StataCorp, 2009) is also described.
Bootstrap Interval Estimation Of Reliability Via Coefficient Omega,
2013
Old Dominion University
Bootstrap Interval Estimation Of Reliability Via Coefficient Omega, Miguel A. Padilla, Jasmin Divers
Journal of Modern Applied Statistical Methods
Three different bootstrap confidence intervals (CIs) for coefficient omega were investigated. The CIs were assessed through a simulation study with conditions not previously investigated. All methods performed well; however, the normal theory bootstrap (NTB) CI had the best performance because it had more consistent acceptable coverage under the simulation conditions investigated.
Fitting Proportional Odds Models To Educational Data With Complex Sampling Designs In Ordinal Logistic Regression,
2013
Eastern Connecticut State University
Fitting Proportional Odds Models To Educational Data With Complex Sampling Designs In Ordinal Logistic Regression, Xing Liu, Hari Koirala
Journal of Modern Applied Statistical Methods
The conventional proportional odds (PO) model assumes that data are collected using simple random sampling by which each sampling unit has the equal probability of being selected from a population. However, when complex survey sampling designs are used, such as stratified sampling, clustered sampling or unequal selection probabilities, it is inappropriate to conduct ordinal logistic regression analyses without taking sampling design into account. Failing to do so may lead to biased estimates of parameters and incorrect corresponding variances. This study illustrates the use of PO models with complex survey data to predict mathematics proficiency levels using Stata and compare the …
Environmentally Friendly Sizing Agent From Corn Distillers Dried Grains,
2013
University of Nebraska-Lincoln
Environmentally Friendly Sizing Agent From Corn Distillers Dried Grains, Yue Zhang
College of Education and Human Sciences: Dissertations, Theses, and Student Research
Distillers dried grains (DDGS), the coproducts of corn ethanol production, were used as a textile sizing agent on cotton, polyester and polyester/cotton blends in an effort to find inexpensive and biodegradable alternatives to sizing agents such as poly(vinyl alcohol) that are currently used. Although DDGS is an inexpensive, biodegradable and abundant co-product, it has limited industrial applications. DDGS is a mixture of carbohydrates, proteins and oil which are used as sizing agents or as size additives. The effects of DDGS extraction conditions on sizing evaluation parameters such as fiber adhesion, film properties, viscosity and fabric abrasion were studied in comparison …
Assessment Of Tillage Practices Using Landsat-Tm 5 In Nebraska.,
2013
University of Nebraska-Lincoln
Assessment Of Tillage Practices Using Landsat-Tm 5 In Nebraska., Sonisa Sharma
School of Natural Resources: Dissertations, Theses, and Student Research
Tillage management practices are an important component to crop production and to federal and state conservation efforts and crop subsidy programs. Crop residue created by conservation tillage reduces soil erosion and reduce evaporation from exposed soil. Agro-hydrological models require information on tillage practices to estimate their impacts on soil-water-holding capacity, total evapotranspiration, carbon sequestration, water runoff and water and wind erosion for agricultural lands. Classification of tillage practices using remote sensing offers promise for the rapid collection of tillage information on individual fields over large areas. Using satellite imagery proves to be challenging due to the similarity in spectral signatures …
