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Social and Behavioral Sciences Commons

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2009

Wayne State University

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Full-Text Articles in Social and Behavioral Sciences

Digitalcommons@Waynestate Policy, Digital Commons Dec 2009

Digitalcommons@Waynestate Policy, Digital Commons

Digital Commons Information

Policy document outlining what types and formats of content can be deposited into DigitalCommons@WayneState, as well as guidelines on copyright, author agreements, and acceptable use.


Op Ed--Another Name For The Out-Of-Print Book Market, Robert P. Holley Nov 2009

Op Ed--Another Name For The Out-Of-Print Book Market, Robert P. Holley

School of Information Sciences Faculty Research Publications

No abstract provided.


Random Ramblings: The Bill And Melinda Gates University Library, Robert P. Holley Nov 2009

Random Ramblings: The Bill And Melinda Gates University Library, Robert P. Holley

School of Information Sciences Faculty Research Publications

No abstract provided.


Digital Learning And Development Environment: Neh White Paper, Nardina N. Mein, Julie Klein, Adrienne Aluzzo, Anne-Marie Armstrong, Matthew Decker, Jonathan Mcglone, Joshua Neds-Fox Nov 2009

Digital Learning And Development Environment: Neh White Paper, Nardina N. Mein, Julie Klein, Adrienne Aluzzo, Anne-Marie Armstrong, Matthew Decker, Jonathan Mcglone, Joshua Neds-Fox

Library Scholarly Publications

Wayne State University’s Digital Learning and Development Environment was a research and development project aimed at developing a prototype for a systematic approach to digital learning using image repositories. The repositories used in the project were two of the Wayne State University Library System’s (WSULS) Digital Collections: Virtual Motor City and Digital Dress. The Collections are web portals providing universal access to digitized objects of cultural history from dispersed holdings of WSULS’s institutional partners. The project integrates easy-to-use technical tools with instructional design principles and resources for digital teaching and learning. The result is a replicable web ...


Back Talk: Books With Feet, Robert P. Holley Nov 2009

Back Talk: Books With Feet, Robert P. Holley

School of Information Sciences Faculty Research Publications

No abstract provided.


Dr. Jekyll (Library Science Professor) And Mr. Hyde (Op Book Vendor), Robert P. Holley Nov 2009

Dr. Jekyll (Library Science Professor) And Mr. Hyde (Op Book Vendor), Robert P. Holley

School of Information Sciences Faculty Research Publications

No abstract provided.


Multiple Search Paths And The General-To-Specific Methodology, Paul Turner Nov 2009

Multiple Search Paths And The General-To-Specific Methodology, Paul Turner

Journal of Modern Applied Statistical Methods

Increased interest in computer automation of the general-to-specific methodology has resulted from research by Hoover and Perez (1999) and Krolzig and Hendry (2001). This article presents simulation results for a multiple search path algorithm that has better properties than those generated by a single search path. The most noticeable improvements occur when the data contain unit roots.


Application Of The Truncated Skew Laplace Probability Distribution In Maintenance System, Gokarna R. Aryal, Chris P. Tsokos Nov 2009

Application Of The Truncated Skew Laplace Probability Distribution In Maintenance System, Gokarna R. Aryal, Chris P. Tsokos

Journal of Modern Applied Statistical Methods

A random variable X is said to have the skew-Laplace probability distribution if its pdf is given by f(x) = 2g(x)G(λx), where g (.) and G (.), respectively, denote the pdf and the cdf of the Laplace distribution. When the skew Laplace distribution is truncated on the left at 0 it is called it the truncated skew Laplace (TSL) distribution. This article provides a comparison of TSL distribution with twoparameter gamma model and the hypoexponential model, and an application of the subject model in maintenance system is studied.


Detecting Lag-One Autocorrelation In Interrupted Time Series Experiments With Small Datasets, Clare Riviello, S. Natasha Beretvas Nov 2009

Detecting Lag-One Autocorrelation In Interrupted Time Series Experiments With Small Datasets, Clare Riviello, S. Natasha Beretvas

Journal of Modern Applied Statistical Methods

The power and type I error rates of eight indices for lag-one autocorrelation detection were assessed for interrupted time series experiments (ITSEs) with small numbers of data points. Performance of Huitema and McKean’s (2000) zHM statistic was modified and compared with the zHM, five information criteria and the Durbin-Watson statistic.


A Maximum Test For The Analysis Of Ordered Categorical Data, Markus Neuhäeuser Nov 2009

A Maximum Test For The Analysis Of Ordered Categorical Data, Markus Neuhäeuser

Journal of Modern Applied Statistical Methods

Different scoring schemes are possible when performing exact tests using scores on ordered categorical data. The standard scheme is based on integer scores, but non-integer scores were proposed to increase power (Ivanova & Berger, 2001). However, different non-integer scores exist and the question arises as to which of the non-integer schemes should be chosen. To solve this problem, a maximum test is proposed. To be precise, the maximum of the competing statistics is used as the new test statistic, rather than arbitrarily choosing one single test statistic.


New Effect Size Rules Of Thumb, Shlomo S. Sawilowsky Nov 2009

New Effect Size Rules Of Thumb, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

Recommendations to expand Cohen’s (1988) rules of thumb for interpreting effect sizes are given to include very small, very large, and huge effect sizes. The reasons for the expansion, and implications for designing Monte Carlo studies, are discussed.


Generating And Comparing Aggregate Variables For Use Across Datasets In Multilevel Analysis, James Chowhan, Laura Duncan Nov 2009

Generating And Comparing Aggregate Variables For Use Across Datasets In Multilevel Analysis, James Chowhan, Laura Duncan

Journal of Modern Applied Statistical Methods

This article examines the creation of contextual aggregate variables from one dataset for use with another dataset in multilevel analysis. The process of generating aggregate variables and methods of assessing the validity of the constructed aggregates are presented, together with the difficulties that this approach presents.


Ordinal Regression Analysis: Fitting The Proportional Odds Model Using Stata, Sas And Spss, Xing Liu Nov 2009

Ordinal Regression Analysis: Fitting The Proportional Odds Model Using Stata, Sas And Spss, Xing Liu

Journal of Modern Applied Statistical Methods

Researchers have a variety of options when choosing statistical software packages that can perform ordinal logistic regression analyses. However, statistical software, such as Stata, SAS, and SPSS, may use different techniques to estimate the parameters. The purpose of this article is to (1) illustrate the use of Stata, SAS and SPSS to fit proportional odds models using educational data; and (2) compare the features and results for fitting the proportional odds model using Stata OLOGIT, SAS PROC LOGISTIC (ascending and descending), and SPSS PLUM. The assumption of the proportional odds was tested, and the results of the fitted models were ...


Jmasm29: Dominance Analysis Of Independent Data (Fortran), Du Feng, Normal Cliff Nov 2009

Jmasm29: Dominance Analysis Of Independent Data (Fortran), Du Feng, Normal Cliff

Journal of Modern Applied Statistical Methods

A Fortran 77 program is provided for an ordinal dominance analysis of independent two-group comparisons. The program calculates the ordinal statistic, d, and statistical inferences about δ. The source codes and an executable file are available at http://www.depts.ttu.edu/hdfs/feng.php.


Level Robust Methods Based On The Least Squares Regression Estimator, Marie Ng, Rand R. Wilcox Nov 2009

Level Robust Methods Based On The Least Squares Regression Estimator, Marie Ng, Rand R. Wilcox

Journal of Modern Applied Statistical Methods

Heteroscedastic consistent covariance matrix (HCCM) estimators provide ways for testing hypotheses about regression coefficients under heteroscedasticity. Recent studies have found that methods combining the HCCM-based test statistic with the wild bootstrap consistently perform better than non-bootstrap HCCM-based methods (Davidson & Flachaire, 2008; Flachaire, 2005; Godfrey, 2006). This finding is more closely examined by considering a broader range of situations which were not included in any of the previous studies. In addition, the latest version of HCCM, HC5 (Cribari-Neto, et al., 2007), is evaluated.


On Type-Ii Progressively Hybrid Censoring, Debasis Kundu, Avijit Joarder, Hare Krishna Nov 2009

On Type-Ii Progressively Hybrid Censoring, Debasis Kundu, Avijit Joarder, Hare Krishna

Journal of Modern Applied Statistical Methods

The progressive Type-II censoring scheme has become quite popular. A drawback of a progressive censoring scheme is that the length of the experiment can be very large if the items are highly reliable. Recently, Kundu and Joarder (2006) introduced the Type-II progressively hybrid censored scheme and analyzed the data assuming that the lifetimes of the items are exponentially distributed. This article presents the analysis of Type-II progressively hybrid censored data when the lifetime distributions of the items follow Weibull distributions. Maximum likelihood estimators and approximate maximum likelihood estimators are developed for estimating the unknown parameters. Asymptotic confidence intervals based on ...


An Inductive Approach To Calculate The Mle For The Double Exponential Distribution, W. J. Hurley Nov 2009

An Inductive Approach To Calculate The Mle For The Double Exponential Distribution, W. J. Hurley

Journal of Modern Applied Statistical Methods

Norton (1984) presented a calculation of the MLE for the parameter of the double exponential distribution based on the calculus. An inductive approach is presented here.


Estimation Of The Standardized Mean Difference For Repeated Measures Designs, Lindsey J. Wolff Smith, S. Natasha Beretvas Nov 2009

Estimation Of The Standardized Mean Difference For Repeated Measures Designs, Lindsey J. Wolff Smith, S. Natasha Beretvas

Journal of Modern Applied Statistical Methods

This simulation study modified the repeated measures mean difference effect size, d=RM , for scenarios with unequal pre- and post-test score variances. Relative parameter and SE bias were calculated for dRM ≠ versus dRM = . Results consistently favored dRM over d=RM with worse positive parameter and negative SE bias identified for d=RM for increasingly heterogeneous variance conditions.


Intermediate R Values For Use In The Fleishman Power Method, Julie M. Smith Nov 2009

Intermediate R Values For Use In The Fleishman Power Method, Julie M. Smith

Journal of Modern Applied Statistical Methods

Several intermediate r values are calculated at three different correlations for use in the Fleishman Power Method for generating correlated data from normal and non-normal populations.


Jmasm28: Gibbs Sampling For 2pno Multi-Unidimensional Item Response Theory Models (Fortran), Yanyan Sheng, Todd C. Headrick Nov 2009

Jmasm28: Gibbs Sampling For 2pno Multi-Unidimensional Item Response Theory Models (Fortran), Yanyan Sheng, Todd C. Headrick

Journal of Modern Applied Statistical Methods

A Fortran 77 subroutine is provided for implementing the Gibbs sampling procedure to a multiunidimensional IRT model for binary item response data with the choice of uniform and normal prior distributions for item parameters. In addition to posterior estimates of the model parameters and their Monte Carlo standard errors, the algorithm also estimates the correlations between distinct latent traits. The subroutine requires the user to have access to the IMSL library. The source code is available at http://www.siuc.edu/~epse1/sheng/Fortran/MUIRT/GSMU2.FOR. An executable file is also provided for download at http://www.siuc.edu ...


Markov Modeling Of Breast Cancer, Chunling Cong, Chris P. Tsokos Nov 2009

Markov Modeling Of Breast Cancer, Chunling Cong, Chris P. Tsokos

Journal of Modern Applied Statistical Methods

Previous work with respect to the treatments and relapse time for breast cancer patients is extended by applying a Markov chain to model three different types of breast cancer patients: alive without ever having relapse, alive with relapse, and deceased. It is shown that combined treatment of tamoxifen and radiation is more effective than single treatment of tamoxifen in preventing the recurrence of breast cancer. However, if the patient has already relapsed from breast cancer, single treatment of tamoxifen would be more appropriate with respect to survival time after relapse. Transition probabilities between three stages during different time periods, 2-year ...


Analysis Of Multifactor Experimental Designs, Phillip I. Good Nov 2009

Analysis Of Multifactor Experimental Designs, Phillip I. Good

Journal of Modern Applied Statistical Methods

In the one-factor case, Good and Lunneborg (2006) showed that the permutation test is superior to the analysis of variance. In the multi-factor case, simulations reveal the reverse is true. The analysis of variance is remarkably robust against departures from normality including instances in which data is drawn from mixtures of normal distributions or from Weibull distributions. The traditional permutation test based on all rearrangements of the data labels is not exact and is more powerful that the analysis of variance only for 2xC designs or when there is only a single significant effect. Permutation tests restricted to synchronized permutations ...


Examples Of Computing Power For Zero-Inflated And Overdispersed Count Data, Suzanne R. Doyle Nov 2009

Examples Of Computing Power For Zero-Inflated And Overdispersed Count Data, Suzanne R. Doyle

Journal of Modern Applied Statistical Methods

Examples of zero-inflated Poisson and negative binomial regression models were used to demonstrate conditional power estimation, utilizing the method of an expanded data set derived from probability weights based on assumed regression parameter values. SAS code is provided to calculate power for models with a binary or continuous covariate associated with zero-inflation.


Least Error Sample Distribution Function, Vassili F. Pastushenko Nov 2009

Least Error Sample Distribution Function, Vassili F. Pastushenko

Journal of Modern Applied Statistical Methods

Email: The empirical distribution function (ecdf) is unbiased in the usual sense, but shows certain order bias. Pyke suggested discrete ecdf using expectations of order statistics. Piecewise constant optimal ecdf saves 200%/N of sample size N. Results are compared with linear interpolation for U(0, 1), which require up to sixfold shorter samples at the same accuracy.


Impact Of Rank-Based Normalizing Transformations On The Accuracy Of Test Scores, Shira R. Soloman, Shlomo S. Sawilowsky Nov 2009

Impact Of Rank-Based Normalizing Transformations On The Accuracy Of Test Scores, Shira R. Soloman, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

The purpose of this article is to provide an empirical comparison of rank-based normalization methods for standardized test scores. A series of Monte Carlo simulations were performed to compare the Blom, Tukey, Van der Waerden and Rankit approximations in terms of achieving the T score’s specified mean and standard deviation and unit normal skewness and kurtosis. All four normalization methods were accurate on the mean but were variably inaccurate on the standard deviation. Overall, deviation from the target moments was pronounced for the even moments but slight for the odd moments. Rankit emerged as the most accurate method among ...


Relationship Between Internal Consistency And Goodness Of Fit Maximum Likelihood Factor Analysis With Varimax Rotation, Gibbs Y. Kanyongo, James B. Schreiber Nov 2009

Relationship Between Internal Consistency And Goodness Of Fit Maximum Likelihood Factor Analysis With Varimax Rotation, Gibbs Y. Kanyongo, James B. Schreiber

Journal of Modern Applied Statistical Methods

This study investigates how reliability (internal consistency) affects model-fitting in maximum likelihood exploratory factor analysis (EFA). This was accomplished through an examination of goodness of fit indices between the population and the sample matrices. Monte Carlo simulations were performed to create pseudo-populations with known parameters. Results indicated that the higher the internal consistency the worse the fit. It is postulated that the observations are similar to those from structural equation modeling where a good fit with low correlations can be observed and also the reverse with higher item correlations.


Estimating Model Complexity Of Feed-Forward Neural Networks, Douglas Landsittel Nov 2009

Estimating Model Complexity Of Feed-Forward Neural Networks, Douglas Landsittel

Journal of Modern Applied Statistical Methods

In a previous simulation study, the complexity of neural networks for limited cases of binary and normally-distributed variables based the null distribution of the likelihood ratio statistic and the corresponding chi-square distribution was characterized. This study expands on those results and presents a more general formulation for calculating degrees of freedom.


Closed Form Confidence Intervals For Small Sample Matched Proportions, James F. Reed Iii Nov 2009

Closed Form Confidence Intervals For Small Sample Matched Proportions, James F. Reed Iii

Journal of Modern Applied Statistical Methods

The behavior of the Wald-z, Wald-c, Quesenberry-Hurst, Wald-m and Agresti-Min methods was investigated for matched proportions confidence intervals. It was concluded that given the widespread use of the repeated-measure design, pretest-posttest design, matched-pairs design, and cross-over design, the textbook Wald-z method should be abandoned in favor of the Agresti-Min alternative.


Approximate Bayesian Confidence Intervals For The Mean Of A Gaussian Distribution Versus Bayesian Models, Vincent A. R. Camara Nov 2009

Approximate Bayesian Confidence Intervals For The Mean Of A Gaussian Distribution Versus Bayesian Models, Vincent A. R. Camara

Journal of Modern Applied Statistical Methods

This study obtained and compared confidence intervals for the mean of a Gaussian distribution. Considering the square error and the Higgins-Tsokos loss functions, approximate Bayesian confidence intervals for the mean of a normal population are derived. Using normal data and SAS software, the obtained approximate Bayesian confidence intervals were compared to a published Bayesian model. Whereas the published Bayesian method is sensitive to the choice of the hyper-parameters and does not always yield the best confidence intervals, it is shown that the proposed approximate Bayesian approach relies only on the observations and often performs better.


Semi-Parametric Of Sample Selection Model Using Fuzzy Concepts, L. Muhamad Safiih, A. A. Kamil, M. T. Abu Osman Nov 2009

Semi-Parametric Of Sample Selection Model Using Fuzzy Concepts, L. Muhamad Safiih, A. A. Kamil, M. T. Abu Osman

Journal of Modern Applied Statistical Methods

The sample selection model has been studied in the context of semi-parametric methods. With the deficiencies of the parametric model, such as inconsistent estimators, semi-parametric estimation methods provide better alternatives. This article focuses on the context of fuzzy concepts as a hybrid to the semiparametric sample selection model. The better approach when confronted with uncertainty and ambiguity is to use the tools provided by the theory of fuzzy sets, which are appropriate for modeling vague concepts. A fuzzy membership function for solving uncertainty data of a semi-parametric sample selection model is introduced as a solution to the problem.