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Articles 1171 - 1200 of 13174
Full-Text Articles in Entire DC Network
Final Report: Section 3. Public Outreach, Horsley Witten Group, Inc.
Final Report: Section 3. Public Outreach, Horsley Witten Group, Inc.
Phase I Final Report
No abstract provided.
Final Report: Section 6. Smart Growth Case Study – Easton, Horsley Witten Group, Inc.
Final Report: Section 6. Smart Growth Case Study – Easton, Horsley Witten Group, Inc.
Phase I Final Report
No abstract provided.
Final Report: Section 2. Data Collection, Horsley Witten Group, Inc.
Final Report: Section 2. Data Collection, Horsley Witten Group, Inc.
Phase I Final Report
No abstract provided.
Final Report: Cover, Acknowledgement, Table Of Contents, List Of Figures And List Of Tables, Horsley Witten Group, Inc.
Final Report: Cover, Acknowledgement, Table Of Contents, List Of Figures And List Of Tables, Horsley Witten Group, Inc.
Phase I Final Report
No abstract provided.
Final Report: Executive Summary, Horsley Witten Group, Inc.
Final Report: Executive Summary, Horsley Witten Group, Inc.
Phase I Final Report
No abstract provided.
Final Report: Section 4. Sub-Watershed Analysis – Water Balance, Horsley Witten Group, Inc.
Final Report: Section 4. Sub-Watershed Analysis – Water Balance, Horsley Witten Group, Inc.
Phase I Final Report
No abstract provided.
Final Report: Water And Sewer Service Area Maps (By Town), Horsley Witten Group, Inc.
Final Report: Water And Sewer Service Area Maps (By Town), Horsley Witten Group, Inc.
Phase I Final Report
No abstract provided.
Final Report: Section 5. Stream Buffer And Habitat Analysis, Horsley Witten Group, Inc.
Final Report: Section 5. Stream Buffer And Habitat Analysis, Horsley Witten Group, Inc.
Phase I Final Report
No abstract provided.
Final Report: Data And Assessment (Full Report), Horsley Witten Group, Inc.
Final Report: Data And Assessment (Full Report), Horsley Witten Group, Inc.
Phase I Final Report
No abstract provided.
Vol. 7, No. 2 (Full Issue), Jmasm Editors
Vol. 7, No. 2 (Full Issue), Jmasm Editors
Journal of Modern Applied Statistical Methods
No abstract provided.
Multi-Group Confirmatory Factor Analysis For Testing Measurement Invariance In Mixed Item Format Data, Kim H. Koh, Bruno D. Zumbo
Multi-Group Confirmatory Factor Analysis For Testing Measurement Invariance In Mixed Item Format Data, Kim H. Koh, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
This simulation study investigated the empirical Type I error rates of using the maximum likelihood estimation method and Pearson covariance matrix for multi-group confirmatory factor analysis (MGCFA) of full and strong measurement invariance hypotheses with mixed item format data that are ordinal in nature. The results indicate that mixed item formats and sample size combinations do not result in inflated empirical Type I error rates for rejecting the true measurement invariance hypotheses. Therefore, although the common methods are in a sense sub-optimal, they don’t lead to researchers claiming that measures are functioning differently across groups – i.e., a lack of …
Estimating Explanatory Power In A Simple Regression Model Via Smoothers, Rand R. Wilcox
Estimating Explanatory Power In A Simple Regression Model Via Smoothers, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Consider the regression model Y = γ(X) + ε , where γ(X) is some conditional measure of location associated with Y , given X. Let Υ̂ be some estimate of Y, given X, and let τ2 (Y) be some measure of variation. Explanatory power is η2 = τ2 (Υ̂) /τ2(Y) . When γ(X) = β0 + β1X and τ2(Y) is the variance of Y , η2 = ρ2 , …
Data Mining Ceo Compensation, Susan M. Adams, Atul Gupta, Dominique M. Haughton, John D. Leeth
Data Mining Ceo Compensation, Susan M. Adams, Atul Gupta, Dominique M. Haughton, John D. Leeth
Journal of Modern Applied Statistical Methods
The need to pre-specify expected interactions between variables is an issue in multiple regression. Theoretical and practical considerations make it impossible to pre-specify all possible interactions. The functional form of the dependent variable on the predictors is unknown in many cases. Two ways are described in which the data mining technique Multivariate Adaptive Regression Splines (MARS) can be utilized: first, to obtain possible improvements in model specification, and second, to test for the robustness of findings from a regression analysis. An empirical illustration is provided to show how MARS can be used for both purposes.
Least Squares Percentage Regression, Chris Tofallis
Least Squares Percentage Regression, Chris Tofallis
Journal of Modern Applied Statistical Methods
In prediction, the percentage error is often felt to be more meaningful than the absolute error. We therefore extend the method of least squares to deal with percentage errors, for both simple and multiple regression. Exact expressions are derived for the coefficients, and we show how such models can be estimated using standard software. When the relative error is normally distributed, least squares percentage regression is shown to provide maximum likelihood estimates. The multiplicative error model is linked to least squares percentage regression in the same way that the standard additive error model is linked to ordinary least squares regression.
Application Of Dynamic Poisson Models To Japanese Cancer Mortality Data, Shuichi Midorikawa, Etsuo Miyaoka, Bruce Smith
Application Of Dynamic Poisson Models To Japanese Cancer Mortality Data, Shuichi Midorikawa, Etsuo Miyaoka, Bruce Smith
Journal of Modern Applied Statistical Methods
A dynamic Poisson model is used with a Bayesian approach to modeling to predict cancer mortality. The complexity of the posterior distribution prohibits direct evaluation of the posterior, and so parameters are estimated by using a Markov Chain Monte Carlo method. The model is applied to analyze lung and stomach cancer data which have been collected in Japan.
A Randomization Method To Control The Type I Error Rates In Best Subset Regression, Yasser A. Shehata, Paul White
A Randomization Method To Control The Type I Error Rates In Best Subset Regression, Yasser A. Shehata, Paul White
Journal of Modern Applied Statistical Methods
A randomization method for the assessment of statistical significance for best subsets regression is given. The procedure takes into account the number of potential predictors and the inter-dependence between predictors. The approach corrects a non-trivial problem with Type I errors and can be used to assess individual variable significance.
Comparing Factor Loadings In Exploratory Factor Analysis: A New Randomization Test, W. Holmes Finch, Brian F. French
Comparing Factor Loadings In Exploratory Factor Analysis: A New Randomization Test, W. Holmes Finch, Brian F. French
Journal of Modern Applied Statistical Methods
Factorial invariance testing requires a referent loading to be constrained equal across groups. This study introduces a randomization test for comparing group exploratory factor analysis loadings so as to identify an invariant referent. Results show that it maintains the Type I error rate while providing adequate power under most conditions.
Variance Estimation In Time Series Regression Models, Samir Safi
Variance Estimation In Time Series Regression Models, Samir Safi
Journal of Modern Applied Statistical Methods
The effect of variance estimation of regression coefficients when disturbances are serially correlated in time series regression models is studied. Variance estimation enters into confidence interval estimation, hypotheses testing, spectrum estimation, and expressions for the estimated standard error of prediction. Using computer simulations, the robustness of various estimators, including Estimated Generalized Least Squares (EGLS) was considered. The estimates of variance of the coefficient estimators produced by computer packages were considered. Models were generated with a second order auto-correlated error structure, considering the robustness of estimators based upon misspecified order. Ordinary Least Squares (OLS) (order zero) estimates outperformed first order EGLS. …
Two Dimension Marginal Distributions Of Crossing Time And Renewal Numbers Related To Two-Stage Erlang Processes, Mir Ghulam Hyder Talpur, Iffat Zamir, M. Masoom Ali
Two Dimension Marginal Distributions Of Crossing Time And Renewal Numbers Related To Two-Stage Erlang Processes, Mir Ghulam Hyder Talpur, Iffat Zamir, M. Masoom Ali
Journal of Modern Applied Statistical Methods
The two dimensional marginal transform, probability density and cumulative probability distribution functions for the random variables TξN (time taken by servers during vacations), ξN (number of vacations taken by servers) and Nη (number of customers or units arriving in the system) are derived by taking combinations of these random variables. One random variable is controlled at one time to determine the effect of the other two random variables simultaneously.
Bootstrap Confidence Intervals And Coverage Probabilities Of Regression Parameter Estimates Using Trimmed Elemental Estimation, Matthew Hall, Matthew S. Mayo
Bootstrap Confidence Intervals And Coverage Probabilities Of Regression Parameter Estimates Using Trimmed Elemental Estimation, Matthew Hall, Matthew S. Mayo
Journal of Modern Applied Statistical Methods
Mayo and Gray introduced the leverage residual-weighted elemental (LRWE) classification of regression estimators and a new method of estimation called trimmed elemental estimation (TEE), showing the efficiency and robustness of TEE point estimates. Using bootstrap methods, properties of various trimmed elemental estimator interval estimates to allow for inference are examined and estimates with ordinary least squares (OLS) and least sum of absolute values (LAV) are compared. Confidence intervals and coverage probabilities for the estimators using a variety of error distributions, sample sizes, and number of parameters are examined. To reduce computational intensity, randomly selecting elemental subsets to calculate the parameter …
Robust Predictive Inference For Multivariate Linear Models With Elliptically Contoured Distribution Using Bayesian, Classical And Structural Approaches, B. M. Golam Kibria
Robust Predictive Inference For Multivariate Linear Models With Elliptically Contoured Distribution Using Bayesian, Classical And Structural Approaches, B. M. Golam Kibria
Journal of Modern Applied Statistical Methods
Predictive distributions of future response and future regression matrices under multivariate elliptically contoured distributions are discussed. Under the elliptically contoured response assumptions, these are identical to those obtained under matric normal or matric-t errors using structural, Bayesian with improper prior, or classical approaches. This gives inference robustness with respect to departure from the reference case of independent sampling from the matric normal or matric t to multivariate elliptically contoured distributions. The importance of the predictive distribution for skewed elliptical models is indicated; the elliptically contoured distribution, as well as matric t distribution, have significant applications in statistical practices.
Delete And Revise Procedures For Two-Stage Short-Run Control Charts, Matthew E. Elam
Delete And Revise Procedures For Two-Stage Short-Run Control Charts, Matthew E. Elam
Journal of Modern Applied Statistical Methods
This article investigates the effect different delete and revise procedures have on the performance of twostage short-run control charting methodology in the second stage of its two stage procedure. Five variables control chart combinations, six delete and revise procedures, and various out-of-control situations in both stages are considered.
A Methodology To Improve Pci Use In Industry, Milind A. Phadnis, Matthew E. Elam
A Methodology To Improve Pci Use In Industry, Milind A. Phadnis, Matthew E. Elam
Journal of Modern Applied Statistical Methods
This article presents the development of a methodology using decision trees to resolve issues in industry with using process capability indices (PCIs). The methodology forms the structure of a prototype decision support system (PDSS) for PCI selection, calculation, and interpretation. Download instructions for the PDSS are available at http://program.20m.com.
The Multinomial Regression Modeling Of The Cause-Of-Death Mortality Of The Oldest Old In The U.S., Dudley L. Poston Jr., Hosik Min
The Multinomial Regression Modeling Of The Cause-Of-Death Mortality Of The Oldest Old In The U.S., Dudley L. Poston Jr., Hosik Min
Journal of Modern Applied Statistical Methods
The statistical modeling of the causes of death of the oldest old (persons aged 80 and over) in the U.S. in 2001 was conducted in this article. Data were analyzed using a multinomial logistic regression model (MNLM) because multiple causes of death are coded on death certificates and the codes are nominal. The percentage distribution of the 10 major causes of death among the oldest old was first examined; we next estimated a multinomial logistic regression equation to predict the likelihood of elders dying of one of the causes of death compared to dying of an “other cause.” The independent …
Frequency Domain Modeling With Piecewise Constant Spectra, Erhard Reschenhofer
Frequency Domain Modeling With Piecewise Constant Spectra, Erhard Reschenhofer
Journal of Modern Applied Statistical Methods
Using piecewise constant functions as models for the spectral density of the differenced log real U.S. GDP it was found that these models have the capacity to compete with the spectral densities implied by ARMA models. According to AIC and BIC the piecewise constant spectral densities are superior to ARMA.
Cees Newsletter, No. 8, Nov. 2008, University Of Colorado Boulder. Center For Energy & Environmental Security
Cees Newsletter, No. 8, Nov. 2008, University Of Colorado Boulder. Center For Energy & Environmental Security
CEES: The Center for Energy & Environmental Security [Newsletter] (2008)
No abstract provided.
The Occupations And Earnings Of Young Australians : The Role Of Education And Training, Gary Marks
The Occupations And Earnings Of Young Australians : The Role Of Education And Training, Gary Marks
LSAY Research Reports
This report investigates the effect of post-secondary education and training on the occupation and earnings of young people. The majority of young Australians undertake further education and training after leaving school, and it is important to better understand the pathways that they follow, and the impact of different types of experience on the early career. Such analyses can help young people in choosing appropriate programs as well as assist policy makers in identifying resource priorities. They can also contribute to debates about the role of education in promoting social mobility and economic development. The data analysed are from a sample …
The Retiree Center Newsletter - Winter 2008, Retiree Center-Winona State University
The Retiree Center Newsletter - Winter 2008, Retiree Center-Winona State University
WSU Retiree Newsletter
No abstract provided.
Acer Enews 11 November 2008, Acer
Proposition 11: Redistricting. Initiative Constitutional Amendment And Statute., Jeffery Grant, Luke Vanderwagen
Proposition 11: Redistricting. Initiative Constitutional Amendment And Statute., Jeffery Grant, Luke Vanderwagen
California Initiative Review (CIR)
No abstract provided.