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Articles 2101 - 2130 of 2693
Full-Text Articles in Statistics and Probability
Why Study Applied/Agricultural Economics, Matt Bogard
Why Study Applied/Agricultural Economics, Matt Bogard
Agriculture Department Seminar Series
Agricultural Economics is a very applied field covering many topics beyond those stereotypically thought of as pertaining to agriculture. These may include finance and risk management, environmental and natural resource economics, game theory, or public policy analysis to name a few.
A Plotless Density Estimator Based On The Asymptotic Limit Of Ordered Distance Estimation Values, Barry Kronenfeld
A Plotless Density Estimator Based On The Asymptotic Limit Of Ordered Distance Estimation Values, Barry Kronenfeld
Faculty Research and Creative Activity
Estimation of tree density from point-tree distances is an attractive option for quick inventory of new sites, but estimators that are unbiased in clustered and dispersed situations have not been found. Noting that bias of an estimator derived from distances to the kth nearest neighbor from a random point tends to decrease with increasing k, a method is proposed for estimating the limit of an asymptotic function through a set of ordered distance estimators. A standard asymptotic model is derived from the limiting case of a clustered distribution. The proposed estimator is evaluated against 13 types of simulated generating processes, …
A Plotless Density Estimator Based On The Asymptotic Limit Of Ordered Distance Estimation Values, Barry J. Kronenfeld
A Plotless Density Estimator Based On The Asymptotic Limit Of Ordered Distance Estimation Values, Barry J. Kronenfeld
Faculty Research and Creative Activity
Estimation of tree density from point-tree distances is an attractive option for quick inventory of new sites, but estimators that are unbiased in clustered and dispersed situations have not been found. Noting that bias of an estimator derived from distances to the kth nearest neighbor from a random point tends to decrease with increasing k, a method is proposed for estimating the limit of an asymptotic function through a set of ordered distance estimators. A standard asymptotic model is derived from the limiting case of a clustered distribution. The proposed estimator is evaluated against 13 types of simulated generating processes, …
The Validity Of Animal Experiments In Medical Research, Gill Langley
The Validity Of Animal Experiments In Medical Research, Gill Langley
Experimentation Collection
Other animals, such as mice, rats, rabbits, dogs and monkeys, are widely used as surrogates for humans in fundamental medical research. This involves creating disorders in animals by chemical, surgical or genetic means, with the aim of mimicking selected aspects of human illnesses.
It is a truism that any model or surrogate is not identical to the target being modelled. So, in medical research, experiments using animals or cell cultures or even healthy volunteers instead of patients (being the target population with the target illness) will inevitably have limitations, although these will be greater or lesser depending on the model.
The Minimization Of Research Animal Distress And Pain: Conclusions And Recommendations, Kathleen Conlee, Martin Stephens, Andrew N. Rowan
The Minimization Of Research Animal Distress And Pain: Conclusions And Recommendations, Kathleen Conlee, Martin Stephens, Andrew N. Rowan
Laboratory Experiments Collection
While the attention given to preventing, assessing, and alleviating pain in research animals has increased noticeably in recent decades, much remains to be done both in terms of implementing best practices and conducting studies to answer outstanding questions. In contrast, the attention to distress (particularly non-pain induced distress) has shown no comparable increase. There are many reasons for this discrepancy, including the conceptual untidiness of the distress concept, the paucity of pharmacological treatments for distress, and perceived lack of regulatory emphasis on distress. These are challenges that need to be addressed and overcome. This book is intended to help meet …
Addressing Distress And Pain In Animal Research: The Veterinary, Research, Societal, Regulatory And Ethical Contexts For Moving Forward, Kathleen Conlee, Martin Stephens, Andrew N. Rowan
Addressing Distress And Pain In Animal Research: The Veterinary, Research, Societal, Regulatory And Ethical Contexts For Moving Forward, Kathleen Conlee, Martin Stephens, Andrew N. Rowan
Experimentation Collection
While most people recognize that biomedical scientists are searching for knowledge that will improve the health of humans and animals, the image of someone deliberately causing harm to an animal in order to produce data that may lead to some future benefit has always prompted an uncomfortable reaction outside the laboratory. However, proponents of animal research have usually justified the practice by reference to greater benefits (new knowledge and medical treatments) over lesser costs (in animal suffering and death). Given that one of the costs of animal research is the suffering experienced by the animals, the goal of eliminating distress …
The Role Of Clinical Veterinary Medicine In The Assessment And Treatment Of Laboratory Animal Distress, V. Hampshire
The Role Of Clinical Veterinary Medicine In The Assessment And Treatment Of Laboratory Animal Distress, V. Hampshire
Veterinary Science and Medicine Collection
It is doubtful that the scientific community will ever arrive at a consensus definition for distress as it may be attempted for the purposes of improving animal welfare in and across the myriad of research, testing and teaching facilities in the United States and throughout the minuet of protocols that exist for animals. The stakeholders in this attempt can however address most causes of physiologic distress by instituting time-honored veterinary and agrarian approaches to animal surveillance. In this manner, the majority of individuals who participate in responsible and humane animal care might be assuaged in that a condition of maximum …
The Deterrent Effect Of Death Penalty Eligibility: Evidence From The Adoption Of Child Murder Eligibility Factors, Michael D. Frakes, Matthew Harding
The Deterrent Effect Of Death Penalty Eligibility: Evidence From The Adoption Of Child Murder Eligibility Factors, Michael D. Frakes, Matthew Harding
Faculty Scholarship
We draw on within-state variations in the reach of capital punishment statutes between 1977 and 2004 to identify the deterrent effects associated with capital eligibility. Focusing on the most prevalent eligibility expansion, we estimate that the adoption of a child murder factor is associated with an approximately 20% reduction in the homicide rate of youth victims. Eligibility expansions may enhance deterrence by (1) paving the way for more executions and (2) providing prosecutors with greater leverage to secure enhanced non-capital sentences. While executions themselves are rare, this latter channel is likely to be triggered fairly regularly, providing a reasonable basis …
Modeling Peer Influence And Peer Selection As Processes, Bob Edward Vasquez
Modeling Peer Influence And Peer Selection As Processes, Bob Edward Vasquez
Legacy Theses & Dissertations (2009 - 2024)
Behavioral scientists are aware of the strong and persistent correlation between peer and individual behavior. Evidence suggests selection and socialization effects explain the correlation, but the processes, or the details of the ways in which these effects operate in an empirical model, remain relatively unexamined.
Using Decision Analytic Modelling To Simulate Pregnancy, Jeffrey Cannon
Using Decision Analytic Modelling To Simulate Pregnancy, Jeffrey Cannon
Theses : Honours
Decision analytic modelling enables decision makers to assess the cost-effectiveness associated with a proposed change in a cunent system without physically implementing the changes. This can be achieved by formulating a mathematical model that represents all the major events occuning in the system through fmmulas and algorithms, and estimating the likely outcomes along with their costs. This type of modelling has been identified by the State Health Research Advisory Council (SHRAC) of the Western Australian Depmiment of Health as an asset for the plmming of health care investments in the future. One such area in which the Western Australian Department …
The Influence Of Familism On Descriptive And Injunctive Norms In Predicting The Intention To Eat A Vegetarian Diet Among Chinese Seventh-Day Adventists, See Wei Toh
Loma Linda University Electronic Theses, Dissertations & Projects
According to the theory of planned behavior (TpB), one determinant of intention to engage in a behavior is the subjective norm. Various studies have found that subjective norm is often the weaker predictor of intention compared to perceived behavioral control and attitude. This study examined whether familism (emphasis on the family rather than the individual) would contribute positively to the predictive power of the TpB model through interactions with the family portion of descriptive and injunctive norms. Descriptive and injunctive norms are component variables of the subjective norm. A sample of 284 adult Chinese Seventh-day Adventists 18 years and older …
Research Design And Statistical Applications, Grayson Holmbeck, Kathy Zebracki, Katie Mcgoron
Research Design And Statistical Applications, Grayson Holmbeck, Kathy Zebracki, Katie Mcgoron
Psychology: Faculty Publications and Other Works
What is the role of research in the field of pediatric psychology? To answer this question, it is useful to imagine what clinical practice would be like if we had no research foundation for our work. Without such a foundation, practitioners would have no basis for suggesting specific interventions or understanding why some interventions are successful and why others fail. Similarly, without a research foundation, assessments conducted with children would be based on unstandardized assessment methods, and no normative data would be available. Clearly, most of us would agree that scientific research is the foundation of pediatric psychology, including all …
"G" And "H" Control Charts And Risk Analysis In The Banking Industry, James L. Bossert
"G" And "H" Control Charts And Risk Analysis In The Banking Industry, James L. Bossert
All-Inclusive List of Electronic Theses and Dissertations
This research investigates the utilization of a new control chart in the Banking industry to minimize financial risk. There are processes in the banking industry that do not lend themselves to traditional control chart applications. These processes tend to be high volume. High volume meaning over a million transactions a day and a requirement for high levels of accuracy characterize these processes. The research has looked at these processes and applied the "g" control charts to determine if they provide timely feedback to the banking industry. The value of this research will give the banking industry an opportunity to react …
Maximizing Warfighter Capability Using Surveyed Necessity Measurement: Application To The Usaf F-15c Fleet, John M. Colombi, David R. Jacques, Dennis D. Strouble
Maximizing Warfighter Capability Using Surveyed Necessity Measurement: Application To The Usaf F-15c Fleet, John M. Colombi, David R. Jacques, Dennis D. Strouble
Faculty Publications
Within the Department of Defense, with changing missions to counter dynamic and asymmetrical threats, the acquisition workforce strives to maximize capability for joint warfighting. How acquisition professionals measure and select capability improvements for the nation’s weapon systems is a perpetual challenge, made even more complex with constrained defense budgets. This study identifies a method for determining which upgrades should be purchased (production) for which aircraft in the F- 15C fleet by optimizing a capability proxy measure. Each upgrade’s “necessity” for a given mission area was obtained by conducting a survey of over 250 experienced F-15C pilots. The solution presented in …
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.
Correlation Between The Sample Mean And Sample Variance, Ramalingam Shanmugam
Correlation Between The Sample Mean And Sample Variance, Ramalingam Shanmugam
Journal of Modern Applied Statistical Methods
This article obtains a general formula to find the correlation coefficient between the sample mean and variance. Several particular results for major non-normal distributions are extracted to help students in classroom, clients during statistical consulting service.