Four Period Crossover Designs,
2012
Christiana Care Hospital System, Newark, Delaware
Four Period Crossover Designs, James F. Reed Iii
Journal of Modern Applied Statistical Methods
In higher-order four period crossover designs with two treatments, sixteen possible treatment sequences can result: AAAA, AAAB, AABA, AABB, ABAA, ABAB, ABBA, ABBB and their duals. Higher-order crossover designs are useful for several reasons: they allow estimation of a treatment effect even in the presence of a carry-over effect, they provide estimates of intra-subject variability and they draw inference on the carry-over effect. The real question related to a two-treatment four-period crossover design is the real world application of these designs. This article considers four designs: Design I: ABBA and its dual; Design II: ABBA, AABB and their duals, Design …
Gamma-Pareto Distribution And Its Applications,
2012
Austin Peay State University, Clarksville, TN
Gamma-Pareto Distribution And Its Applications, Ayman Alzaatreh, Felix Famoye, Carl Lee
Journal of Modern Applied Statistical Methods
A new distribution, the gamma-Pareto, is defined and studied and various properties of the distribution are obtained. Results for moments, limiting behavior and entropies are provided. The method of maximum likelihood is proposed for estimating the parameters and the distribution is applied to fit three real data sets.
A Weighted Exponential Detection Function Model For Line Transect Data,
2012
Al-Hussian Bin Talal University, Ma’an, Jordan
A Weighted Exponential Detection Function Model For Line Transect Data, Faisal Ababneh, Omar M. Eidous
Journal of Modern Applied Statistical Methods
A new parametric model is proposed for modeling the density function of perpendicular distances in line transects sampling. The model can be considered a weighted exponential model in the sense that it combines two exponential models with different weights. The proposed model is appealing because it is monotone decreasing with distance from transect line; in contrast to the classical exponential model, it satisfies the shoulder condition at the origin. Simulation results for a wide range of target densities show reasonable and good performances of the weighted exponential model in most considered cases compared to the classical exponential and the half-normal …
Ordinal Regression Analysis: Using Generalized Ordinal Logistic Regression Models To Estimate Educational Data,
2012
Eastern Connecticut State University
Ordinal Regression Analysis: Using Generalized Ordinal Logistic Regression Models To Estimate Educational Data, Xing Liu, Hari Koirala
Journal of Modern Applied Statistical Methods
The proportional odds (PO) assumption for ordinal regression analysis is often violated because it is strongly affected by sample size and the number of covariate patterns. To address this issue, the partial proportional odds (PPO) model and the generalized ordinal logit model were developed. However, these models are not typically used in research. One likely reason for this is the restriction of current statistical software packages: SPSS cannot perform the generalized ordinal logit model analysis and SAS requires data restructuring. This article illustrates the use of generalized ordinal logistic regression models to predict mathematics proficiency levels using Stata and compares …
Robust Regression Estimates In The Prediction Of Latent Variables In Structural Equation Models,
2012
Federal University of Lavras, Brazil
Robust Regression Estimates In The Prediction Of Latent Variables In Structural Equation Models, Marcelo Angelo Cirillo, Lúcia Pereira Barroso
Journal of Modern Applied Statistical Methods
The incorporation of the robust regression methods Least Median Square (LMS) and Least Trimmed Squares (LTS) is proposed in structural equation modeling. Results show that, in situations of high deviations of symmetry, the evaluated methods would be recommended for applications including smaller sample sizes.
Comparison Of Re-Sampling Methods To Generalized Linear Models And Transformations In Factorial And Fractional Factorial Designs,
2012
University of Dayton
Comparison Of Re-Sampling Methods To Generalized Linear Models And Transformations In Factorial And Fractional Factorial Designs, Maher Qumsiyeh, Gerald Shaughnessy
Journal of Modern Applied Statistical Methods
Experimental situations in which observations are not normally distributed frequently occur in practice. A common situation occurs when responses are discrete in nature, for example counts. One way to analyze such experimental data is to use a transformation for the responses; another is to use a link function based on a generalized linear model (GLM) approach. Re-sampling is employed as an alternative method to analyze non-normal, discrete data. Results are compared to those obtained by the previous two methods.
Statistical Inferences For Lomax Distribution Based On Record Values (Bayesian And Classical),
2012
University of Payame Noor, Tehran, Iran
Statistical Inferences For Lomax Distribution Based On Record Values (Bayesian And Classical), Parviz Nasiri, Saman Hosseini
Journal of Modern Applied Statistical Methods
A maximum likelihood estimation (MLE) based on records is obtained and a proper prior distribution to attain a Bayes estimation (both informative and non-informative) based on records for quadratic loss and squared error loss functions is also calculated. The study considers the shortest confidence interval and Highest Posterior Distribution confidence interval based on records, and using Mean Square Error MSE criteria for point estimation and length criteria for interval estimation, their appropriateness to each other is examined.
Empirical Sampling From Permutation Space With Unique Patterns,
2012
University of Benin, Nigeria
Empirical Sampling From Permutation Space With Unique Patterns, Justice I. Odiase
Journal of Modern Applied Statistical Methods
The exact distribution of a test statistic ultimately guarantees that the probability of a Type I error is exactly α. Several methods for estimating the exact distribution of a test statistic have evolved over the years with inherent computational problems and varying degrees of accuracy. The unique pattern of permutations resulting from using experimental data to sample within the permutation space without the risk of repeating permutations is identified. The method presented circumvents the theoretical requirements of asymptotic procedures and the computational difficulties associated with an exhaustive enumeration of permutations. Results show that time and space complexities are drastically reduced …
Weight: Does It Really Matter?,
2012
Columbus State University
Weight: Does It Really Matter?, Jennifer L. Brown, Gerald Halpin, Glennelle Halpin
Journal of Modern Applied Statistical Methods
Differential weighting promises to improve the validity of a measure. This study examines whether similar results would be found using weighted, unweighted and standardized z scores from the All Stars Core survey. It was concluded that the weighted systems were developed to equate the questions within the scales and to ease the process for customers without access to data analysis programs; however, the standardized scores were the more appropriate method for equating the test items.
Ratio Type Estimator Of Ratio Of Two Population Means In Stratified Random Sampling,
2012
Vikram University, Ujjain, M.P., India
Ratio Type Estimator Of Ratio Of Two Population Means In Stratified Random Sampling, Rajesh Tailor, Sunil Chouhan
Journal of Modern Applied Statistical Methods
A ratio estimator is proposed for the ratio of two population means using auxiliary information in stratified random sampling. Bias and mean squared error expressions are obtained under large sample approximation, and the proposed estimator is compared both theoretically and empirically with the conventional estimator of ratio for two population means in stratified random sampling.
Parameter Estimation With Mixture Item Response Theory Models: A Monte Carlo Comparison Of Maximum Likelihood And Bayesian Methods,
2012
Ball State University
Parameter Estimation With Mixture Item Response Theory Models: A Monte Carlo Comparison Of Maximum Likelihood And Bayesian Methods, W. Holmes Finch, Brian F. French
Journal of Modern Applied Statistical Methods
The Mixture Item Response Theory (MixIRT) can be used to identify latent classes of examinees in data as well as to estimate item parameters such as difficulty and discrimination for each of the groups. Parameter estimation via maximum likelihood (MLE) and Bayesian estimation based on the Markov Chain Monte Carlo (MCMC) are compared for classification accuracy and parameter estimation bias for difficulty and discrimination. Standard error magnitude and coverage rates were compared across number of items, number of latent groups, group size ratio, total sample size and underlying item response model. Results show that MCMC provides more accurate group membership …
A Study On Underwriting Cycle Of Property Insurance Industry Of China,
2012
College of Hunan University, Changsha Hunan Province, China
A Study On Underwriting Cycle Of Property Insurance Industry Of China, Lin Zhang, Linjuan Tang
Journal of Modern Applied Statistical Methods
Methods in underwriting cycle research are compared. A second-order autoregressive model, which includes structural transition and Christiano-Fitzgerald (CF) Filter method, is used to analyze China’s underwriting cycle with annual property insurance loss ratio data from 1982 to 2008. Results show that the underwriting cycle is 11-12 years and, from the phase of underwriting cycle, management suggestions about underwriting cycle phenomenon are provided.
Regression Models For Mixed Over-Dispersed Poisson And Continuous Clustered Data: Modeling Bmi And Number Of Cigarettes Smoked Per Day,
2012
Brigham and Women's Hospital, Boston, MA
Regression Models For Mixed Over-Dispersed Poisson And Continuous Clustered Data: Modeling Bmi And Number Of Cigarettes Smoked Per Day, Folefac Atem, Julius S. Ngwa, Abidemi Adeniji
Journal of Modern Applied Statistical Methods
Clustered data, multiple observations collected on the same experimental unit, is common in epidemiological studies. Bivariate outcome data is often the result of interest in two correlated response variables. An efficient method is presented for dealing with bivariate outcomes when one outcome is continuous and the other is a count using a simple transformation to handle over-dispersed Poisson data. A multilevel analysis was performed on data from the National Health Interview Survey (NHIS) with body mass index (BMI) and the number of cigarettes smoked per day (NCS) as responses. Results show that these random effects models yield misleading results in …
Steady State Probabilities Of A Three Preemptive Single Server Queue,
2012
Qatar University
Steady State Probabilities Of A Three Preemptive Single Server Queue, Ameen Jameel Alawneh
Journal of Modern Applied Statistical Methods
A three preemptive priority queuing system is considered where customers with three priorities joined a queue according to a Poisson process. A customer with higher priority needs to enter the service immediately upon arrival. The recursive formulas approach was extended to determine the steady state probabilities of such a priority queuing system.
Estimation Of Multinomial Proportions Using Higher Order Moments Of Scrambling Variables In Randomized Response Sampling,
2012
Texas A&M University
Estimation Of Multinomial Proportions Using Higher Order Moments Of Scrambling Variables In Randomized Response Sampling, Cheng C. Chen, Sarjinder Singh
Journal of Modern Applied Statistical Methods
An extension to estimating multinomial proportions of potentially sensitive attributes in survey sampling is proposed using higher order moments of scrambling variables at the estimation stage to produce unbiased estimators. The variance and covariance expressions are derived and the relative efficiency of the proposed estimators based on scrambling variables is investigated.
Inverted Exponential Distribution Under A Bayesian Viewpoint,
2012
S. N. Medical College, Agra, U. P., India
Inverted Exponential Distribution Under A Bayesian Viewpoint, Gyan Prakash
Journal of Modern Applied Statistical Methods
The objective of this study was to examine the properties of Bayes estimators of the parameter, reliability function and hazard rate under the symmetric and asymmetric loss functions for the inverted exponential model. The Bayes predictive interval and the Bayes estimate of shift point are also determined. A simulation study was carried out to study the properties of the Bayes estimators.
Underlying Distributions In Loglinear Models Of Discrete Data,
2012
Educational Testing Service, Princeton, NJ
Underlying Distributions In Loglinear Models Of Discrete Data, Tim Moses
Journal of Modern Applied Statistical Methods
The implications of loglinear models based on underlying uniform and binomial distribution are assessed with respect to modeling eight distributions. Regarding statistical selection of the loglinear models’ parameterizations, results indicate that better fitting models are obtained when the distribution being modeled is dissimilar to the underlying distribution used. For loglinear models with predetermined numbers of parameters, results suggest that better fitting models can be obtained when the distribution being modeled is similar to the underlying distribution.
Robust Modifications Of The Levene And O’Brien Tests For Spread,
2012
Universiti Sains, Malaysia
Robust Modifications Of The Levene And O’Brien Tests For Spread, Abdul R. Othman, The Sin Yan, H. J. Keselman, Rand R. Wilcox, James Algina
Journal of Modern Applied Statistical Methods
Variants of Levene’s and O’Brien’s procedures not investigated by Keselman, Wilcox & Algina (2008) were examined. Simulations indicate that a new O’Brien variant provides very good Type I error control and is simpler for applied researchers to compute than the method recommended by Keselman, et al.
An Extension Of The Seasonal Kpss Test,
2012
University of Prince Edward Island, Charlottetown, PEI, Canada
An Extension Of The Seasonal Kpss Test, Sami Khedhiri, Ghassen El Montasser
Journal of Modern Applied Statistical Methods
The limit theory of the seasonal KPSS test is established under the null hypothesis using seasonal dummy variables. Taking these variables into account can result in improved finite sample performance of the test. The seasonal KPSS test can be interpreted as a test of deterministic seasonality and it may be used in addition to seasonal unit root tests to analyze the dynamic properties of time series. The seasonal indicator variables provide the test with an explicit model-based regression that in itself constitutes a support for its limit theory.
Improved Estimator In The Presence Of Multicollinearity,
2012
King Khalid University, Saudi Arabia
Improved Estimator In The Presence Of Multicollinearity, Ghadban Khalaf
Journal of Modern Applied Statistical Methods
The performances of two biased estimators for the general linear regression model under conditions of collinearity are examined and a new proposed ridge parameter is introduced. Using Mean Square Error (MSE) and Monte Carlo simulation, the resulting estimator’s performance is evaluated and compared with the Ordinary Least Square (OLS) estimator and the Hoerl and Kennard (1970a) estimator. Results of the simulation study indicate that, with respect to MSE criteria, in all cases investigated the proposed estimator outperforms both the OLS and the Hoerl and Kennard estimators.
