Ordinal Regression Analysis: Predicting Mathematics Proficiency Using The Continuation Ratio Model,
2011
Eastern Connecticut State University
Ordinal Regression Analysis: Predicting Mathematics Proficiency Using The Continuation Ratio Model, Xing Liu, Ann A. O'Connell, Hari Koirala
Journal of Modern Applied Statistical Methods
One commonly used model to analyze ordinal response data is the proportional odds (PO) model. However, if research interest is focused on a particular category and if an individual must pass through lower categories before achieving a higher level, the continuation ratio (CR) model is a more appropriate choice than the PO model. In addition, statistical software, such as Stata and SAS, may use different techniques to estimate the parameters. The CR model is used to illustrate the analysis of ordinal data in education using Stata and SAS and compares the results of fitting the CR model between these two …
Estimation And Hypothesis Testing In Lav Regression With Autocorrelated Errors: Is Correction For Autocorrelation Helpful?,
2011
Texas Christian University
Estimation And Hypothesis Testing In Lav Regression With Autocorrelated Errors: Is Correction For Autocorrelation Helpful?, Terry E. Dielman
Journal of Modern Applied Statistical Methods
Using the Prais-Winsten correction and adding a lagged variable provides improved estimates (smaller MSE) in least absolute value (LAV) regression when moderate to high levels of autocorrelation are present. When comparing empirical levels of significance for hypothesis tests, adding a lagged variable outperforms other approaches but has a relative high empirical level of significance.
Maximum Log Likelihood Estimation Using Em Algorithm And Partition Maximum Log Likelihood Estimation For Mixtures Of Generalized Lambda Distributions,
2011
University of Western Australia
Maximum Log Likelihood Estimation Using Em Algorithm And Partition Maximum Log Likelihood Estimation For Mixtures Of Generalized Lambda Distributions, Steve Su
Journal of Modern Applied Statistical Methods
Two mixture distribution fitting methods based on maximizing the likelihood using generalized lambda distributions are presented. The fitting algorithms are demonstrated on various data and the strengths and weakness of the algorithms which can influence their use under different mixture modeling situations are discussed. The procedures described are available in GLDEX package in R.
On Maximum Likelihood Estimators Of The Parameters Of A Modified Weibull Distribution Using Extreme Ranked Set Sampling,
2011
Al al-Bayt University
On Maximum Likelihood Estimators Of The Parameters Of A Modified Weibull Distribution Using Extreme Ranked Set Sampling, Amer Ibrahim Al-Omari, Said Ali Al-Hadhrami
Journal of Modern Applied Statistical Methods
Extreme ranked set sampling (ERSS) is considered to estimate the three parameters and population mean of the modified Weibull distribution (MWD). The maximum likelihood estimator (MLE) is investigated and compared to the corresponding one based on simple random sampling (SRS). It is found that, the MLE based on ERSS is more efficient than MLE using SRS for estimating the three parameters of the MWD. The ERSS estimator of the population mean of the MWD is also found to be more efficient than the SRS based on the same number of measured units.
Indeterminacy Of Factor Score Estimates In Slightly Misspecified Confirmatory Factor Models,
2011
University of Bonn, Bonn, Germany
Indeterminacy Of Factor Score Estimates In Slightly Misspecified Confirmatory Factor Models, André Beauducel
Journal of Modern Applied Statistical Methods
Two methods to calculate a measure for the quality of factor score estimates have been proposed. These methods were compared by means of a simulation study. The method based on a covariance matrix reproduced from a model leads to smaller effects of sampling error.
Modeling Repairable System Failures With Interval Failure Data And Time Dependent Covariate,
2011
University Putra Malaysia
Modeling Repairable System Failures With Interval Failure Data And Time Dependent Covariate, Jayanthi Arasan, Samira Ehsani
Journal of Modern Applied Statistical Methods
An application of a repairable system model for interval failure data with a time dependent covariate is examined. The performance of several models based on the NHPP when applied to real data on ball bearing failures is also explored. The best model for the data was selected based on results of the likelihood ratio test. The bootstrapping technique was applied to obtain the variance estimate for the estimated expected number of failures. Results demonstrate that the proposed model works well and is easy to implement, in addition the bootstrap variance estimate provides a simple substitute for the traditional estimate.
Non-Homogenous Poisson Process For Evaluating Stage I & Ii Ductal Breast Cancer Treatment,
2011
University of South Florida
Non-Homogenous Poisson Process For Evaluating Stage I & Ii Ductal Breast Cancer Treatment, Chris P. Tsokos, Yong Xu
Journal of Modern Applied Statistical Methods
Non-Homogenous Poisson Process (NHPP), also known as the Power Law process (PLP) or the Weibull Process, is used to evaluate the effectiveness of a given treatment for Stage I & II ductal breast cancer patients. The behavior of the shape parameter of the intensity function is examined to evaluate the response of a given treatment with respect to its effectiveness for a cancer subject.
Salary Equity Studies: An Analysis Of Using The Blinder-Oaxaca Decomposition To Estimate Differences In Faculty Salaries By Gender,
2011
Central Connecticut State University
Salary Equity Studies: An Analysis Of Using The Blinder-Oaxaca Decomposition To Estimate Differences In Faculty Salaries By Gender, Sally A. Lesik, Carolyn R. Fallahi
Journal of Modern Applied Statistical Methods
Parameter estimates for equity studies tested for stability are described. Bootstrap simulation can test whether parameter estimates remain stable given changes in the sample data; fractional polynomials can be used to access functional form specification; and variance inflation factors can be used to test for multicollinearity.
A Sequential Monte Carlo Approach For Online Stock Market Prediction Using Hidden Markov Models,
2011
University of Lagos
A Sequential Monte Carlo Approach For Online Stock Market Prediction Using Hidden Markov Models, Ahani E. Bridget, O. Abass
Journal of Modern Applied Statistical Methods
A sequential Monte Carlo (SMC) algorithm prediction approach is developed based on joint probability distribution in hidden Markov Models (HMM). SMC methods, a general class of Monte Carlo methods, are typically used for sampling from sequences of distributions and simple examples of these algorithms are found extensively throughout the tracking and signal processing literature. Recent developments indicate that these techniques have much more general applicability and can be applied very effectively to statistical inference problems. Due to the problem involved in estimating the parameter of HMM, the HMM is represented in a state space model and the sequential Monte Carlo …
A Pooled Two-Sample Median Test Based On Density Estimation,
2011
George Mason University
A Pooled Two-Sample Median Test Based On Density Estimation, Vadim Y. Bichutskiy
Journal of Modern Applied Statistical Methods
A new method based on density estimation is proposed for medians of two independent samples. The test controls the probability of Type I error and is at least as powerful as methods widely used in statistical practice. The method can be implemented using existing libraries in R.
Identifying Outliers In Fuzzy Time Series,
2011
ManonmaniamSundaranar University
Identifying Outliers In Fuzzy Time Series, S. Suresh, K. Senthamarai Kannan
Journal of Modern Applied Statistical Methods
Time series analysis is often associated with the discovery of patterns and prediction of features. Forecasting accuracy can be improved by removing identified outliers in the data set using the Cook’s distance and Studentized residual test. In this paper a modified fuzzy time series method is proposed based on transition probability vector membership function. It is experimentally shown that the proposed method minimizes the average forecasting error compared with other known existing methods.
Jmasm31: Manova Procedure For Power Calculations (Spss),
2011
Macquarie University
Jmasm31: Manova Procedure For Power Calculations (Spss), Alan Taylor
Journal of Modern Applied Statistical Methods
D’Amico, Neilands & Zambarano (2001) showed how the SPSS MANOVA procedure can be used to conduct power calculations for research designs. This article demonstrates a simple way of entering data required for power calculations into SPSS and provides examples that supplement those given by D’Amico, Neilands & Zambarano.
Higher Order Markov Structure-Based Logistic Model And Likelihood Inference For Ordinal Data,
2011
University of Chittagong, Chittagong, Bangladesh
Higher Order Markov Structure-Based Logistic Model And Likelihood Inference For Ordinal Data, Soma Chowdhury Biswas, M. Ataharul Islam, Jamal Nazrul Islam
Journal of Modern Applied Statistical Methods
Azzalini (1994) proposed a first order Markov chain for binary data. Azzalini’s model is extended for ordinal data and introduces a second order model. Further, the test statistics are developed and the power of the test is determined. An application using real data is also presented.
A Permutation Test For Compound Symmetry With Application To Gene Expression Data,
2011
University of Central Oklahoma
A Permutation Test For Compound Symmetry With Application To Gene Expression Data, Tracy L. Morris, Mark E. Payton, Stephanie A. Santorico
Journal of Modern Applied Statistical Methods
The development and application of a permutation test for compound symmetry is described. In a simulation study the permutation test appears to be a level-α test and is robust to non-normality. However, it exhibits poor power, particularly for small samples.
Comparison Of Several Tests For Combining Several Independent Tests,
2011
Columbus State University
Comparison Of Several Tests For Combining Several Independent Tests, Madhusudan Bhandary, Xuan Zhang
Journal of Modern Applied Statistical Methods
Several tests for combining p-values from independent tests have been considered to address a particular common testing problem. A simulation study shows that Fisher’s (1932) Inverse Chi-square test is optimal based on a power comparison of several different tests.
Discriminant Analysis For Repeated Measures Data: Effects Of Mean And Covariance Misspecification On Bias And Error In Discriminant Function Coefficients,
2011
University of Saskatchewan
Discriminant Analysis For Repeated Measures Data: Effects Of Mean And Covariance Misspecification On Bias And Error In Discriminant Function Coefficients, Tolulope T. Sajobi, Lisa M. Lix, Longhai Li, William Laverty
Journal of Modern Applied Statistical Methods
Discriminant analysis (DA) procedures based on parsimonious mean and/or covariance structures have been proposed for repeated measures (RM) data. Bias and means square error of discriminant function coefficients (DFCs) for DA procedures are investigated when the mean and/or covariance structures are correctly specified and misspecified.
Explicit Equations For Acf In Autoregressive Processes In The Presence Of Heteroscedasticity Disturbances,
2011
The Islamic University of Gaza
Explicit Equations For Acf In Autoregressive Processes In The Presence Of Heteroscedasticity Disturbances, Samir Safi
Journal of Modern Applied Statistical Methods
The autocorrelation function, ACF, is an important guide to the properties of a time series. Explicit equations are derived for ACF in the presence of heteroscedasticity disturbances in pth order autoregressive, AR(p), processes. Two cases are presented: (1) when the disturbance term follows the general covariance matrix, Σ , and (2) when the diagonal elements of Σ are not all identical but σi,j = 0 ∀i ≠ j.
Control Balanced Designs Involving Sequences Of Treatments,
2011
Indian Agricultural Statistics Research Institute
Control Balanced Designs Involving Sequences Of Treatments, Cini Varghese, Seema Jaggi
Journal of Modern Applied Statistical Methods
Designs involving sequences of treatments for test vs. control comparisons are suitable for research in which each experimental unit receives treatments over time in order to compare several test treatments to one (or more) control treatment(s). These designs can be advantageously used in screening experiments and bioequivalence trials. Three series of such designs are constructed in incomplete sequences wherein the first class of designs is variance balanced while the other two classes of designs are partially variance balanced for test versus test comparisons of both direct and residual effects of treatments.
Construction Of Control Charts Based On Six Sigma Initiatives For The Number Of Defects And Average Number Of Defects Per Unit,
2011
P.S.G. College of Arts and Science
Construction Of Control Charts Based On Six Sigma Initiatives For The Number Of Defects And Average Number Of Defects Per Unit, R. Radhakrishnan, P. Balamurugan
Journal of Modern Applied Statistical Methods
A control chart is a statistical device used for the study and control of a repetitive process. In 1931, Shewart suggested control charts based on 3 sigma limits. Today manufacturing companies around the world apply Six Sigma initiatives, with a result offewer product defects. Companies practicing Six Sigma initiatives are expected to produce 3.4 or less number of defects per million opportunities, a concept suggested by Motorola in 1980. If companies practicing Six Sigma initiatives use control limits suggested by Shewhart, then no points will fall outside the control limits due to the improvement in the quality of the process. …
Height-Diameter Relationship In Tree Modeling Using Simultaneous Equation Techniques In Correlated Normal Deviates,
2011
Forestry Research Institute of Nigeria
Height-Diameter Relationship In Tree Modeling Using Simultaneous Equation Techniques In Correlated Normal Deviates, S. O. Oyamakin
Journal of Modern Applied Statistical Methods
In other to study the complex simultaneous relationships existing in forest/tree growth modeling, six estimation methods of a simultaneous equation model are examined to determine how they cope with varying degrees of correlation between pairs of random deviates using average parameter estimates. A two-equation simultaneous system assumed covariance matrix was considered. The model was structured to have a mutual correlation between pairs of random deviates: a violation of the assumption of mutual independence between pairs of such random deviates. The correlation between the pairs of normal deviates were generated using three scenarios r = 0.0, 0.3 and 0.5. The performances …
