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.
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 …
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.
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.
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.
Robustness, Power And Interpretability Of Pairwise Tests Of Discriminant Functions In Manova,
2011
Queens College of CUNY, Flushing
Robustness, Power And Interpretability Of Pairwise Tests Of Discriminant Functions In Manova, Philip H. Ramsey, Patricia P. Ramsey, Priscila Hachimine, Nancy Andiloro
Journal of Modern Applied Statistical Methods
Limiting follow-up hypotheses to be tested can reduce problems relating to the control of Type I and Type II errors in multivariate analysis of variance (MANOVA). Such limitations can also improve the interpretability of results. The importance of sample size, shape of population distribution, within-group correlations and heterogeneity of variances are demonstrated. The protected greatest characteristic root (GCR) procedure is shown to work well for small, group size, N (≤ 10). The unprotected GCR is shown to work well for larger N.
A Comparison Of Factor Rotation Methods For Dichotomous Data,
2011
Ball State University
A Comparison Of Factor Rotation Methods For Dichotomous Data, W. Holmes Finch
Journal of Modern Applied Statistical Methods
Exploratory factor analysis (EFA) is frequently used in the social sciences and is a common component in many validity studies. A core aspect of EFA is the determination of which observed indicator variables are associated with which latent factors through the use of factor loadings. Loadings are initially extracted using an algorithm, such as maximum likelihood or weighted least squares, and then transformed - or rotated - to make them more interpretable. There are a number of rotational techniques available to the researcher making use of EFA. Prior work has discussed the advantages of a number of these criteria from …
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.
Error Analysis On The Generalized Negative Binomial Distribution,
2011
Central Michigan University
Error Analysis On The Generalized Negative Binomial Distribution, Felix Famoye, Oluwakemi Aremu
Journal of Modern Applied Statistical Methods
The generalized negative binomial distribution characterized by three parameters, has been used to fit data from various fields of study. The distribution can model data for which the variance is larger or smaller than the mean, however, it becomes truncated under certain conditions. This truncation error is investigated via a detailed error analysis that determines the parameter space when the model can be used in place of the truncated generalized negative binomial distribution. The fitting of a generalized negative. K. M. Ramachandran is a
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.
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.
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.
Probabilistic Inferences For The Sample Pearson Product Moment Correlation,
2011
University of Maryland
Probabilistic Inferences For The Sample Pearson Product Moment Correlation, Jeffrey R. Harring, John A. Wasko
Journal of Modern Applied Statistical Methods
Fisher’s correlation transformation is commonly used to draw inferences regarding the reliability of tests comprised of dichotomous or polytomous items. It is illustrated theoretically and empirically that omitting test length and difficulty results in inflated Type I error. An empirically unbiased correction is introduced within the transformation that is applicable under any test conditions.
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.
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.
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.
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.
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.
Higher Order C(T, P, S) Crossover Designs,
2011
Christiana Care Hospital System, Newark, Delaware
Higher Order C(T, P, S) Crossover Designs, James F. Reed Iii
Journal of Modern Applied Statistical Methods
A crossover study is a repeated measures design in which each subject is randomly assigned to a sequence of treatments, including at least two treatments. The most damning characteristic of a crossover study is the potential of a carryover effect of one treatment to the next period. To solve the first-order crossover problem characteristic in the classic AB|BA design, the design must be extended. One alternative uses additional treatment sequences in two periods; a second option is to add a third period and repeat one of the treatments. Assuming a traditional model that specifies a first-order carryover effect, this study …
