Physical Sciences and Mathematics Commons^™

Modeling And Fitting Two-Way Tables Containing Outliers, David L. Farnsworth

Articles

A model is proposed for two-way tables of measurement data containing outliers. The two independent variables are categorical and error free. Neither missing values nor replication are present. The model consists of the sum of a customary additive part that can be fit using least squares and a part that is composed of outliers. Recommendations are made for methods for identifying cells containing outliers and for fitting the model. A graph of the observations is used to determine the outliers’ locations. For all cells containing an outlier, replacement values are determined simultaneously using a classical missing-data tool. The result is …

Statistical Theory For Specialized Linear Regression Adjustment Methods Compared To Multiple Linear Regression In The Presence And Absence Of Interaction Effects, Leon Su

Theses and Dissertations--Statistics

When building models to investigate outcomes and variables of interest, researchers often want to adjust for other variables. There is a variety of ways that these adjustments are performed. In this work, we will consider four approaches to adjustment utilized by researchers in various fields. We will compare the efficacy of these methods to what we call the ”true model method”, fitting a multiple linear regression model in which adjustment variables are model covariates. Our goal is to show that these adjustment methods have inferior performance to the true model method by comparing model parameter estimates, power, type I error, …

Regression Modeling And Prediction By Individual Observations Versus Frequency, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

A regression model built by a dataset could sometimes demonstrate a low quality of fit and poor predictions of individual observations. However, using the frequencies of possible combinations of the predictors and the outcome, the same models with the same parameters may yield a high quality of fit and precise predictions for the frequencies of the outcome occurrence. Linear and logistical regressions are used to make an explicit exposition of the results of regression modeling and prediction.

The Correlation Between Sleep And Lifespan In Drosophila Melanogaster, Joshua Randall Lisse

Masters Theses

”Adequate sleep is associated with an individual’s health. Too little sleep is associated with many health problems, including cardiovascular disease, obesity, and a general increase in all-cause mortality. Yet the molecular changes that link poor sleep and changes in health are still not well understood. Individuals have a unique daily need for sleep, and deviations from the animal’s regular sleeping patterns can be indicative of, or result in, underlying changes in its health. Therefore, we hypothesize that changes in the sleep architecture in Drosophila melanogaster reflect changes in the fly’s health.

We determined sleep architecture in wild-type male flies over …

Essentials Of Structural Equation Modeling, Mustafa Emre Civelek

Zea E-Books Collection

Structural Equation Modeling is a statistical method increasingly used in scientific studies in the fields of Social Sciences. It is currently a preferred analysis method, especially in doctoral dissertations and academic researches. However, since many universities do not include this method in the curriculum of undergraduate and graduate courses, students and scholars try to solve the problems they encounter by using various books and internet resources.

This book aims to guide the researcher who wants to use this method in a way that is free from math expressions. It teaches the steps of a research program using structured equality modeling …

A Realistic Meteorological Assessment Of Perennial Biofuel Crop Deployment: A Southern Great Plains Perspective, Melissa Wagner, Meng Wang, Gonzalo Miguez-Macho, Jesse Miller, Andy Vanloocke, Justin E. Bagley, Carl J. Bernacchi, Matei Georgescu

Andy VanLoocke

Utility of perennial bioenergy crops (e.g., switchgrass and miscanthus) offers unique opportunities to transition toward a more sustainable energy pathway due to their reduced carbon footprint, averted competition with food crops, and ability to grow on abandoned and degraded farmlands. Studies that have examined biogeophysical impacts of these crops noted a positive feedback between near-surface cooling and enhanced evapotranspiration (ET), but also potential unintended consequences of soil moisture and groundwater depletion. To better understand hydrometeorological effects of perennial bioenergy crop expansion, this study conducted high-resolution (2-km grid spacing) simulations with a state-of-the-art atmospheric model (Weather Research and Forecasting system) dynamically …

Automated Sea State Classification From Parameterization Of Survey Observations And Wave-Generated Displacement Data, Jason A. Teichman

University of New Orleans Theses and Dissertations

Sea state is a subjective quantity whose accuracy depends on an observer’s ability to translate local wind waves into numerical scales. It provides an analytical tool for estimating the impact of the sea on data quality and operational safety. Tasks dependent on the characteristics of local sea surface conditions often require accurate and immediate assessment. An attempt to automate sea state classification using eleven years of ship motion and sea state observation data is made using parametric modeling of distribution-based confidence and tolerance intervals and a probabilistic model using sea state frequencies. Models utilizing distribution intervals are not able to …

Beetles, Fungi And Trees: A Story For The Ages? Modeling And Projecting The Multipartite Symbiosis Between The Mountain Pine Beetle, Dendroctonus Ponderosae, And Its Fungal Symbionts, Grosmannia Clavigera And Ophiostoma Montium, Audrey L. Addison

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

As data collection and modeling improve, ecologists increasingly discover that interspecies dynamics greatly affect the success of individual species. Models accounting for the dynamics of multiple species are becoming more important. In this work, we explore the relationship between mountain pine beetle (MPB, Dendroctonus ponderosae Hopkins) and two mutualistic fungi, Grosmannia clavigera and Ophiostoma montium. These species are involved in a multipartite symbiosis, critical to the survival of MPB, in which each species benefits.

Extensive phenological modeling has been done to determine how temperature affects the timing of life events and cold-weather mortality of MPB. The fungi have also …

Modeling Sleep And Wake Bouts In Drosophila Melanogaster, Gayla R. Olbricht, V. A. Samaranayake, Sahitya Injamuri, Luyang Wang, Courtney Fiebelman, Matthew S. Thimgan

Conference on Applied Statistics in Agriculture

Adequate sleep restores vital processes required for health and well-being; but the function and regulation of sleep is not well understood. Unfortunately, a definition of adequate sleep is unclear. On an hours-long timescale, consolidated and cycling sleep results in better health and performance outcomes. At shorter timescales, older studies report conflicting results regarding the relationship between sleep and wake bout durations. One approach to this problem has been to simply analyze the distribution of bout durations. While informative, this method eliminates the time relationship between bouts, which may be important. Here, we develop a model that describes the relationship between …

The Not-So-Quiet Revolution: Cautionary Comments On The Rejection Of Hypothesis Testing In Favor Of A “Causal” Modeling Alternative, Daniel H. Robinson, Joel R. Levin

Journal of Modern Applied Statistical Methods

Rodgers (2010) recently applauded a revolution involving the increased use of statistical modeling techniques. It is argued that such use may have a downside, citing empirical evidence in educational psychology that modeling techniques are often applied in cross-sectional, correlational studies to produce unjustified causal conclusions and prescriptive statements.

Statistical And Mathematical Modeling Versus Nhst? There’S No Competition!, Joseph Lee Rodgers

Journal of Modern Applied Statistical Methods

Some of Robinson & Levin’s critique of Rodgers (2010) is cogent, helpful, and insightful – although limiting. Recent methodology has advanced through the development of structural equation modeling, multi-level modeling, missing data methods, hierarchical linear modeling, categorical data analysis, as well as the development of many dedicated and specific behavioral models. These methodological approaches are based on a revised epistemological system, and have emerged naturally, without the need for task forces, or even much self-conscious discussion. The original goal was neither to develop nor promote a modeling revolution. That has occurred; I documented its development and its status. Two organizing …

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.

Spatial Analysis Of Grasshopper Density As Influenced By Anthropogenic Habitat Changes, Bahman Shafii, William J. Price, Dennis J. Fielding, Merlyn A. Brusven

Conference on Applied Statistics in Agriculture

The rangeland environment in southern Idaho has been heavily impacted by human activities. Invasion by exotic plant species, frequent fires, grazing pressure, and other ecological disturbances have greatly affected the structure and dynamics of grasshopper populations. Quantification of spatial patterns of grasshopper density and species composition is important in order to determine their influence on grassland ecosystems, as well as evaluating managerial decisions concerning vegetation manipulations, grazing practices, and spraying programs. A spatial statistical approach to modeling the heterogeneity of grasshopper populations is presented, and the impact of vegetation and grazing treatments on grasshopper density is investigated. Empirical applications are …

Spatial Statistical Analysis For The Area-Of-Influence Experiments, Bahman Shafii, William J. Price, Don W. Morishita

Conference on Applied Statistics in Agriculture

The area-of-influence (AOI) approach to quantifying crop/weed competition involves measuring the effect of individual weed plants on crop growth and yield at specified distances away from the weed plant. AOI experiments are often analyzed using classical statistical techniques based on the assumption that successive observations on crop response are independent in spite of their distribution in space. However, as the distance varies along the row, the competitive ability will vary spatially so that observations located nearby are expected to be more alike than those separated by large distances. Analyses based on spatial dependencies will therefore provide a more comprehensive understanding …

Forecasting Corn Ear Weights From Daily Weather Data, Fred B. Warren

Conference on Applied Statistics in Agriculture

Statistical models were developed to predict the State average grain weight per ear using daily temperature and precipitation data, recorded from May 1 through late July. The required daily weather data was successfully obtained in an operational test of these models for ten major corn producing States in 1988. Relative forecast errors of ear weight averaged almost one-third smaller than those from a regular survey. Additional refinements of the models to make them more responsive to abnormally early adverse weather, as in 1988, are underway.