Social and Behavioral Sciences Commons^™

A Comparison Between Biased And Unbiased Estimators In Ordinary Least Squares Regression, Ghadban Khalaf

Journal of Modern Applied Statistical Methods

During the past years, different kinds of estimators have been proposed as alternatives to the Ordinary Least Squares (OLS) estimator for the estimation of the regression coefficients in the presence of multicollinearity. In the general linear regression model, Y = Xβ + e, it is known that multicollinearity makes statistical inference difficult and may even seriously distort the inference. Ridge regression, as viewed here, defines a class of estimators of β indexed by a scalar parameter k. Two methods of specifying k are proposed and evaluated in terms of Mean Square Error (MSE) by …

Discriminating Between Generalized Exponential Distribution And Some Life Test Models Based On Population Quantiles, B. Srinivasa Rao, R. R. L Kantam

Journal of Modern Applied Statistical Methods

A test statistic based on population quantiles using sample order statistics is suggested. The quantiles of the test statistics are evaluated for generalized exponential distribution. Similar test statistic based on moments of sample order statistic is referred and the proposed test formula is compared with it. Between the pairs of the above models it is established that the test formula proposed by us is more effective and useful than the formula based on the moments of order statistics as developed by Sultan (2007).

Comparison Of Parameters Of Lognormal Distribution Based On The Classical And Posterior Estimates, Raja Sultan, S. P. Ahmad

Journal of Modern Applied Statistical Methods

Lognormal distribution is widely used in scientific field, such as agricultural, entomological, biology etc. If a variable can be thought as the multiplicative product of some positive independent random variables, then it could be modelled as lognormal. In this study, maximum likelihood estimates and posterior estimates of the parameters of lognormal distribution are obtained and using these estimates we calculate the point estimates of mean and variance for making comparisons.

On Bayesian Estimation And Predictions For Two-Component Mixture Of The Gompertz Distribution, Navid Feroze, Muhammad Aslam

Journal of Modern Applied Statistical Methods

Mixtures models have received sizeable attention from analysts in the recent years. Some work on Bayesian estimation of the parameters of mixture models have appeared. However, the were restricted to the Bayes point estimation The methodology for the Bayesian interval estimation of the parameters for said models is still to be explored. This paper proposes the posterior interval estimation (along with point estimation) for the parameters of a two-component mixture of the Gompertz distribution. The posterior predictive intervals are also derived and evaluated. Different informative and non-informative priors are assumed under a couple of loss functions for the posterior analysis. …

A Generalized Class Of Estimators For Finite Population Variance In Presence Of Measurement Errors, Prayas Sharma, Rajesh Singh

Journal of Modern Applied Statistical Methods

The problem of estimating the population variance is presented using auxiliary information in the presence of measurement errors. The estimators in this article use auxiliary information to improve efficiency and assume that measurement error is present both in study and auxiliary variable. A numerical study is carried out to compare the performance of the proposed estimator with other estimators and the variance per unit estimator in the presence of measurement errors.

Robust Regression Estimators When There Are Tied Values, Rand R. Wilcox, Florence Clark

Journal of Modern Applied Statistical Methods

It is well known that when using the ordinary least squares regression estimator, outliers among the dependent variable can result in relatively poor power. Many robust regression estimators have been derived that address this problem, but the bulk of the results assume that the dependent variable is continuous. It is demonstrated that when there are tied values, several robust regression estimators can perform poorly in terms of controlling the Type I error probability, even with a large sample size. The presence of tied values does not necessarily mean that they perform poorly, but there is the issue of whether there …

Testing The Assumption Of Non-Differential Misclassification In Case-Control Studies, Tze-San Lee, Qin Hui

Journal of Modern Applied Statistical Methods

One of the not yet solved issues regarding the misclassification in case-control studies is whether the misclassification rates are the same for both cases and controls. Currently, a common practice is to assume that the rates are the same, that is, the non-differential misclassification assumption. However, it has been suspected that this assumption may not be valid in practical applications. Unfortunately, no test is available so far to test the validity of the non-differential misclassification assumption. A method is presented to test the validity of non-differential misclassification assumption in case-control studies with 2 × 2 tables when validation data are …

Ordered Logit Regression Modeling Of The Self-Rated Health In Hawai‘I, With Comparisons To The Ols Model, Hosik Min

Journal of Modern Applied Statistical Methods

Despite the ordinal nature of Self-Rated Health (SRH) variable, logistic regression models or regression models have been used without adequate justification for these applications. It is shown that ordered-logit regression model is the appropriate statistical strategy to estimate SRH, whereas the Ordinary LeastSquares model leads to biased conclusions.

Approximation Multivariate Distribution Of Main Indices Of Tehran Stock Exchange With Pair-Copula, G. Parham, A. Daneshkhah, O. Chatrabgoun

Journal of Modern Applied Statistical Methods

The multivariate distribution of five main indices of Tehran stock exchange is approximated using a pair-copula model. A vine graphical model is used to produce an n-dimensional copula. This is accomplished using a flexible copula called a minimum information (MI) copula as a part of pair-copula construction. Obtained results show that the achieved model has a good level of approximation.

Agenda: Free, Prior And Informed Consent: Pathways For A New Millennium, University Of Colorado Boulder. Getches-Wilkinson Center For Natural Resources, Energy, And The Environment, University Of Colorado Boulder. School Of Law. American Indian Law Program

Free, Prior and Informed Consent: Pathways for a New Millennium (November 1)

Presented by the University of Colorado's American Indian Law Program and the Getches-Wilkinson Center for Natural Resources, Energy & the Environment.

The United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP), along with treaties, instruments, and decisions of international law, recognizes that indigenous peoples have the right to give "free, prior, and informed consent" to legislation and development affecting their lands, natural resources, and other interests, and to receive remedies for losses of property taken without such consent. With approximately 150 nations, including the United States, endorsing the UNDRIP, this requirement gives rise to emerging standards, obligations, and opportunities …

Indigenous Peoples’ Right Of Free Prior Informed Consent With Respect To Indigenous Lands, Territories And Resources (United Nations Workshop, 17-19 January 2005), Indian Law Resource Center

Free, Prior and Informed Consent: Pathways for a New Millennium (November 1)

3 pages.

U.N. Doc PFII/2004/WS.2/6

Principles Of International Law For Multilateral Development Banks: The Obligation To Respect Human Rights, Robert T. Coulter, Leonardo A. Crippa, Emily Wann

Free, Prior and Informed Consent: Pathways for a New Millennium (November 1)

41 pages.

"January, 2009"

www.indianlaw.org

Indigenous Peoples’ Right Of Free Prior Informed Consent With Respect To Indigenous Lands, Territories And Resources (June 28, 2010), Indian Law Resource Center

Free, Prior and Informed Consent: Pathways for a New Millennium (November 1)

3 pages.

"June 28, 2010"

Free, Prior And Informed Consent: Ilo 169 And Undrip, Kelsey Peterson

Free, Prior and Informed Consent: Pathways for a New Millennium (November 1)

2 pages.

"Kelsey Peterson, American Indian Law Program Fellow, University of Colorado Law School Class of 2015"

Automatic Domain Identification For Linked Open Data, Sarasi Lalithsena, Pascal Hitzler, Amit P. Sheth, Prateek Jain

Kno.e.sis Publications

Linked Open Data (LOD) has emerged as one of the largest collections of interlinked structured datasets on the Web. Although the adoption of such datasets for applications is increasing, identifying relevant datasets for a specific task or topic is still challenging. As an initial step to make such identification easier, we provide an approach to automatically identify the topic domains of given datasets. Our method utilizes existing knowledge sources, more specifically Freebase, and we present an evaluation which validates the topic domains we can identify with our system. Furthermore, we evaluate the effectiveness of identified topic domains for the purpose …

Introduction To Empowered Partnerships: Community-Based Participatory Action Research For Environmental Justice, Christopher M. Bacon, Saneta Devuono-Powell, Mary Louise Frampton, Tony Lopresti, Camille Pannu

Environmental Studies and Sciences

This article introduces a special section on empowered partnerships that deepens a dialogue initiated during the 2010 symposium titled EmPowered Partnerships: Community-Based Participatory Action Research for Environmental Justice. The articles in this section will be divided between issues 1 and 2 of the Journal. After briefly reviewing the definitions and the steps associated with community-based participatory action research (CBPAR), we identify the synergies connecting the underlying principles and values of the environmental justice (EJ) movement and CBPAR. The principles-based comparison is part of an ongoing effort to craft a framework that produces research partnerships that are simultaneously more responsive to …

Semantics-Empowered Big Data Processing With Applications, Krishnaprasad Thirunarayan, Amit P. Sheth

Kno.e.sis Publications

We discuss the nature of Big Data and address the role of semantics in analyzing and processing Big Data that arises in the context of Physical-Cyber-Social Systems. We organize our research around the Five Vs of Big Data, where four of the Vs are harnessed to produce the fifth V - value. To handle the challenge of Volume, we advocate semantic perception that can convert low-level observational data to higher-level abstractions more suitable for decision-making. To handle the challenge of Variety, we resort to the use of semantic models and annotations of data so that much of the intelligent processing …

The Cost Of Green Infrastructure: Worth The Investment?, Martha Sheils

Green Infrastructure

Is GI worth the investment?

• LID techniques often lead to cost savings when we look at WHOLE PROJECT COSTS

• Natural Infrastructure investments for flood control, drinking water protection and wildlife habitat can yield SIGNIFICANT AVOIDED COSTS and additional co-benefits to communitites

Generalized Modified Ratio Estimator For Estimation Of Finite Population Mean, Jambulingam Subramani

Journal of Modern Applied Statistical Methods

A generalized modified ratio estimator is proposed for estimating the population mean using the known population parameters. It is shown that the simple random sampling without replacement sample mean, the usual ratio estimator, the linear regression estimator and all the existing modified ratio estimators are the particular cases of the proposed estimator. The bias and the mean squared error of the proposed estimator are derived and are compared with that of existing estimators. The conditions for which the proposed estimator performs better than the existing estimators are also derived. The performance of the proposed estimator is assessed with that of …

Test For Intraclass Correlation Coefficient Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara

Journal of Modern Applied Statistical Methods

Three tests are proposed based on F-distribution, Likelihood Ratio Test (LRT) and large sample Z-test for intraclass correlation coefficient under unequal family sizes based on a single multinormal sample. It has been found that the test based on F-distribution consistently and reliably produces results superior to those of Likelihood Ratio Test (LRT) and large sample Z-test in terms of size for various combinations of intraclass correlation coefficient values. The power of this test based on F-distribution is competitive with the power of the LRT and the power of Z-test is slightly better than the powers of F-test and LRT when …

Variables Sampling Plan For Correlated Data, J. R. Singh, R. Sankle, M. Ahmad Khanday

Journal of Modern Applied Statistical Methods

The sampling plan for the mean for correlated data is studied. The Operating Characteristic (OC) of the variable sampling plan for mean for correlated data are calculated and compared with the OC of known σ case.

Case-Control Studies With Jointly Misclassified Exposure And Confounding Variables, Tze-San Lee

Journal of Modern Applied Statistical Methods

The issue of 2 × 2 × 2 case-control studies is addressed when both exposure and confounding variables are jointly misclassified. Two scenarios are considered: the classification errors of exposure and confounding variables are independent or not independent. The bias-adjusted cell probability estimates which account for the misclassification bias are presented. The effect of misclassification on the measure of crude odds ratio either unstratified or stratified by the confounder, Mantel-Haenszel summary odds ratio, the confounding component in the crude odds ratio, the first and second order multiplicative interaction are assessed through the sensitivity analysis from using the data on the …

How Good Is Best? Multivariate Case Of Ehrenberg-Weisberg Analysis Of Residual Errors In Competing Regressions, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

A.S.C. Ehrenberg first noticed and S. Weisberg then formalized a property of pairwise regression to keep its quality almost at the same level of precision while the coefficients of the model could vary over a wide span of values. This paper generalizes the estimates of the percent change in the residual standard deviation to the case of competing multiple regressions. It shows that in contrast to the simple pairwise model, the coefficients of multiple regression can be changed over a wider range of the values including the opposite by signs coefficients. Consideration of these features facilitates better understanding the properties …

Comparison Of Three Calculation Methods For A Bayesian Inference Of P(Π1 > Π2), Yohei Kawasaki, Asanao Shimokawa, Etsuo Miyaoka

Journal of Modern Applied Statistical Methods

In Bayesian inference, some researchers have examined the difference of binominal proportions using θ = P(π₁ > π₂ − Δ₀|X₁,X₂), where X_i denote binomial random variable with parameter π_i. An approximate method and the MCMC method are compared with an exact method for θ, and results of actual clinical trials using θ are presented.

Parameter Estimations Based On Kumaraswamy Progressive Type Ii Censored Data With Random Removals, Navid Feroze, Ibrahim El-Batal

Journal of Modern Applied Statistical Methods

The estimation of two parameters of the Kumaraswamy distribution is considered under Type II progressive censoring with random removals, where the number of units removed at each failure time has a binomial distribution. The MLE was used to obtain the estimators of the unknown parameters, and the asymptotic variance - covariance matrix was also obtained. The formula to compute the expected test time was derived. A numerical study was carried out for different combinations of model parameters. Different censoring schemes were used for the estimation, and performance of these schemes was compared.

Akaike Information Criterion To Select The Parametric Detection Function For Kernel Estimator Using Line Transect Data, Omar Eidous, Samar Al-Salman

Journal of Modern Applied Statistical Methods

Among different candidate parametric detection functions, it is suggested to use Akaike Information Criterion (AIC) to select the most appropriate one of them to fit line transect data. Four different detection functions are considered in this paper. Two of them are taken to satisfy the shoulder condition assumption and the other two estimators do not satisfy this condition. Once the appropriate detection function is determined, it also can be used to select the smoothing parameter of the nonparametric kernel estimator. For a wide range of target densities, a simulation results show the reasonable and good performances of the …

Vol. 12, No. 2 (Full Issue), Jmasm Editors

Journal of Modern Applied Statistical Methods

No abstract provided.

The Tornado Warning Process: A Review Of Current Research, Challenges, And Opportunities, Jerry Brotzge, William Donner

Sociology Faculty Publications

With the unusually violent tornado season of 2011, there has been a renewed national interest, through such programs as NOAA's Weather Ready Nation initiative, to reevaluate and improve our tornado warning process. This literature review provides an interdisciplinary, end-to-end examination of the tornado warning process. Following the steps outlined by the Integrated Warning System, current research in tornado prediction and detection, the warning decision process, warning dissemination, and public response are reviewed, and some of the major challenges for improving each stage are highlighted. The progress and challenges in multi-day to short-term tornado prediction are discussed, followed by an examination …

Constructing Confidence Intervals For Effect Sizes In Anova Designs, Li-Ting Chen, Chao-Ying Joanne Peng

Journal of Modern Applied Statistical Methods

A confidence interval for effect sizes provides a range of plausible population effect sizes (ES) that are consistent with data. This article defines an ES as a standardized linear contrast of means. The noncentral method, Bonett’s method, and the bias-corrected and accelerated bootstrap method are illustrated for constructing the confidence interval for such an effect size. Results obtained from the three methods are discussed and interpretations of results are offered.

Bayesian Joinpoint Regression Model For Childhood Brain Cancer Mortality, Ram C. Kafle, Netra Khanal, Chris P. Tsokos

Journal of Modern Applied Statistical Methods

The Bayesian approach of joinpoint regression is widely used to analyze trends in cancer mortality, incidence and survival data. The Bayesian joinpoint regression model was used to study the childhood brain cancer mortality rate and its average percentage change (APC) per year. Annual observed mortality counts of children ages 0-19 from 1969-2009 obtained from Surveillance Epidemiology and End Results (SEER) database of National Cancer Institute (NCI) were analyzed. It was assumed that death counts are probabilistically characterized by the Poisson distribution and they were modeled using log link function. Results were compared with the mortality trend obtained using joinpoint software …