Collecting, Analyzing And Interpreting Bivariate Data From Leaky Buckets: A Project-Based Learning Unit,
2011
Utah State University
Collecting, Analyzing And Interpreting Bivariate Data From Leaky Buckets: A Project-Based Learning Unit, Florence Funmilayo Obielodan
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Despite the significance and the emphasis placed on mathematics as a subject and field of study, achieving the right attitude to improve students‟ understanding and performance is still a challenge. Previous studies have shown that the problem cuts across nations around the world, both developing countries and developed alike. Teachers and educators of the subject have responsibilities to continuously develop innovative pedagogical approaches that will enhance students‟ interests and performance. Teaching approaches that emphasize real life applications of the subject have become imperative. It is believed that this will stimulate learners‟ interest in the subject as they will be able …
Climate Change And Community Dynamics: A Hierarchical Bayesian Model Of Resource-Driven Changes In A Desert Rodent Community,
2011
Utah State University
Climate Change And Community Dynamics: A Hierarchical Bayesian Model Of Resource-Driven Changes In A Desert Rodent Community, Glenda M. Yenni
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
Predicting effects of climate change on species persistence often assumes that those species are responding to abiotic effects alone. However, biotic interactions between community members may affect species’ ability to respond to abiotic changes. Latent Gaussian models of resource availability using precipitation and NDVI and accounting for spatial autocorrelation and rodent group-level uncertainty in the process are developed to detect differences in seasons, groups, and the experimental removal of one group. Precipitation and NDVI have overall positive effects on rodent energy use as expected, but meaningful differences were detected. Differences in the importance of seasonality when the dominant group was …
Estimation Of Beta In A Simple Functional Capital Asset Pricing Model For High Frequency Us Stock Data,
2011
Utah State University
Estimation Of Beta In A Simple Functional Capital Asset Pricing Model For High Frequency Us Stock Data, Yan Zhang
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
This project applies the methods of functional data analysis (FDA) to intra-daily returns of US corporations. It focuses on an extension of the Capital Asset Pricing Model (CAPM) to such returns. The CAPM is essentially a linear regression with the slope coefficient β. Returns of an asset are regressed on index return. We compare the estimates of β obtained for the daily and intra-daily returns. The variability of these estimates is assessed by two bootstrap methods. All computations are performed using statistical software R. Customized functions are developed to process the raw data, estimate the parameters and assess their variability. …
Controlling Error Rates With Multiple Positively-Dependent Tests,
2011
Utah State University
Controlling Error Rates With Multiple Positively-Dependent Tests, Abdullah Al Masud
All Graduate Plan B and other Reports, Spring 1920 to Spring 2023
It is a typical feature of high dimensional data analysis, for example a microarray study, that a researcher allows thousands of statistical tests at a time. All inferences for the tests are determined using the p-values; a smaller p-value than the α-level of the test signifies a statistically significant test. As the number of tests increases, the chance of observing some small p-values is very high even when all null hypotheses are true. Consequently, we make wrong conclusions on the hypotheses. This type of potential problem frequently happens when we test several hypotheses simultaneously, i.e., the multiple testing problem. …
Comparing The Strength Of Association Of Two Predictors Via Smoothers Or Robust Regression Estimators,
2011
University of Southern California
Comparing The Strength Of Association Of Two Predictors Via Smoothers Or Robust Regression Estimators, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Consider three random variables, Y , X1 and X2, having some unknown trivariate distribution and let n2j (j = 1, 2) be some measure of the strength of association between Y and Xj. When n2j is taken to be Pearson’s correlation numerous methods for testing Ho : n21 = n22 have been proposed. However, Pearson’s correlation is not robust and the methods for testing H0 are not level robust in general. This article examines methods for testing H0 based on a robust fit. The …
A Test That Combines Frequency And Quantitative Information,
2011
University of Southern California
A Test That Combines Frequency And Quantitative Information, Norman Cliff
Journal of Modern Applied Statistical Methods
In many simple designs, observed frequencies in subclasses defined by a qualitative variable are compared to the frequencies expected on the basis of population proportions, design parameters or models. Often there is a quantitative variable which may be affected in the same way as the frequencies. Its differences among the groups may also be analyzed. A simple test is described that combines the effects on the frequencies and on the quantitative variable based on comparing the sums of the values for the quantitative value within each group to the random expectation. The sampling variance of the difference is derived and …
Matched-Pair Studies With Misclassified Ordinal Data,
2011
Western Illinois University
Matched-Pair Studies With Misclassified Ordinal Data, Tze-San Lee
Journal of Modern Applied Statistical Methods
The problem of matched-pair studies with misclassified ordinal data is considered. Misclassification is assumed to occur only between the adjacent columns/rows. Bias-adjusted generalized odds ratio and a test for marginal homogeneity are presented to account for misclassification bias. Data from lambing records of 227 Merino ewes are used to illustrate how to calculate these bias-adjusted estimators and – because validation data are not available – a sensitivity analysis is conducted.
Sample Size Considerations For Multiple Comparison Procedures In Anova,
2011
Ohio University
Sample Size Considerations For Multiple Comparison Procedures In Anova, Gordon P. Brooks, George A. Johanson
Journal of Modern Applied Statistical Methods
Adequate sample sizes for omnibus ANOVA tests do not necessarily provide sufficient statistical power for post hoc multiple comparisons typically performed following a significant omnibus F test. Results reported support a comparison-of-most-interest approach for sample size determination in ANOVA based on effect sizes for multiple comparisons.
Weighting Large Datasets With Complex Sampling Designs: Choosing The Appropriate Variance Estimation Method,
2011
University of Guelph
Weighting Large Datasets With Complex Sampling Designs: Choosing The Appropriate Variance Estimation Method, Sara Mann, James Chowhan
Journal of Modern Applied Statistical Methods
Using the Canadian Workplace and Employee Survey (WES), three variance estimation methods for weighting large datasets with complex sampling designs are compared: simple final weighting, standard bootstrapping and mean bootstrapping. Using a logit analysis, it is shown - depending on which weighting method is used - different predictor variables are significant. The potential lack of independence inherent in a multi-stage cluster sample design, as in the WES, results in a downward bias in the variance when conducting statistical inference (using the simple final weight), which in turn results in increased Type I errors. Bootstrap methods can account for the survey’s …
Model Diagnostics For Proportional And Partial Proportional Odds Models,
2011
The Ohio State University
Model Diagnostics For Proportional And Partial Proportional Odds Models, Ann A. O'Connell, Xing Liu
Journal of Modern Applied Statistical Methods
Although widely used to assist in evaluating the prediction quality of linear and logistic regression models, residual diagnostic techniques are not well developed for regression analyses where the outcome is treated as ordinal. The purpose of this article is to review methods of model diagnosis that may be useful in investigating model assumptions and in identifying unusual cases for PO and PPO models, and provide a corresponding application of these diagnostic methods to the prediction of proficiency in early literacy for children drawn from the kindergarten cohort of the Early Childhood Longitudinal Study (ECLS-K; NCES, 2000).
Using Finite Mixture Modeling To Deal With Systematic Measurement Error: A Case Study,
2011
University of Hawaii
Using Finite Mixture Modeling To Deal With Systematic Measurement Error: A Case Study, Min Liu, Gregory R. Hancock, Jeffrey R. Harring
Journal of Modern Applied Statistical Methods
Conventional methods and analyses view measurement error as random. A scenario is presented where a variable was measured with systematic error. Mixture models with systematic parameter constraints were used to test hypotheses in the context of general linear models; this accommodated the heterogeneity arising due to systematic measurement error.
Logistic Regression Models For Higher Order Transition Probabilities Of Markov Chain For Analyzing The Occurrences Of Daily Rainfall Data,
2011
Ministry of Finance, Dhaka, Bangladesh
Logistic Regression Models For Higher Order Transition Probabilities Of Markov Chain For Analyzing The Occurrences Of Daily Rainfall Data, Narayan Chanra Sinha, M. Ataharul Islam, Kazi Saleh Ahamed
Journal of Modern Applied Statistical Methods
Logistic regression models for transition probabilities of higher order Markov models are developed for the sequence of chain dependent repeated observations. To identify the significance of these models and their parameters a test procedure for a likelihood ratio criterion is developed. A method of model selection is suggested on the basis of AIC and BIC procedures. The proposed models and test procedures are applied to analyze the occurrences of daily rainfall data for selected stations in Bangladesh. Based on results from these models, the transition probabilities of first order Markov model for temperature and humidity provided the most suitable option …
Type I Error Inflation Of The Separate-Variances Welch T Test With Very Small Sample Sizes When Assumptions Are Met,
2011
Ohio University
Type I Error Inflation Of The Separate-Variances Welch T Test With Very Small Sample Sizes When Assumptions Are Met, Albert K. Adusah, Gordon P. Brooks
Journal of Modern Applied Statistical Methods
This Monte Carlo study shows that the separate-variances Welch t test has inflated Type I error rates at very small sample sizes, especially when sample sizes are very small in one group and larger in the second group – even when all assumptions for the statistical test are met.
Nonparametric Methods In Varying Coefficient Models And Quantile Regression Models,
2011
Clemson University
Nonparametric Methods In Varying Coefficient Models And Quantile Regression Models, Chinthaka Kuruwita
All Dissertations
This dissertation aims to address two problems in nonparametric regression models. An estimation issue in generalized varying coefficient models and a hypothesis testing issue in nonparametric quantile regression models is discussed.
We propose a new estimation method for generalized varying coefficient models where the link function is specified up to some smoothness conditions. Consistency and asymptotic normality of the estimated varying coefficient functions are established. Simulation results and a real data application demonstrate the usefulness of the new method.
A new approach for testing the equality of nonparametric quantile regression functions is also presented. Based on marked empirical processes, we …
A Stochastic Model For Wind Turbine Power Quality Using A Levy Index Analysis Of Wind Velocity Data,
2011
Technological University Dublin
A Stochastic Model For Wind Turbine Power Quality Using A Levy Index Analysis Of Wind Velocity Data, Jonathan Blackledge, Eugene Coyle, Derek Kearney
Conference papers
The power quality of a wind turbine is determined by many factors but time-dependent variation in the wind velocity are arguably the most important. After a brief review of the statistics of typical wind speed data, a non- Gaussian model for the wind velocity is introduced that is based on a Levy distribution. It is shown how this distribution can be used to derive a stochastic fractional diusion equation for the wind velocity as a function of time whose solution is characterised by the Levy index. A Levy index numerical analysis is then performed on wind velocity data for both …
Bias In Monte Carlo Simulations Due To Pseudo-Random Number Generator Initial Seed Selection,
2011
Beaumont Health System
Bias In Monte Carlo Simulations Due To Pseudo-Random Number Generator Initial Seed Selection, Jack C. Hill, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
Pseudo-random number generators can bias Monte Carlo simulations of the standard normal probability distribution function with initial seeds selection. Five generator designs were initial-seeded with values from 10000HEX to 1FFFFHEX, estimates of the mean were calculated for each seed, the distribution of mean estimates was determined for each generator and simulation histories were graphed for selected seeds.
One Is Not Enough: The Need For Multiple Respondents In Survey Research Of Organizations,
2011
Mercer University
One Is Not Enough: The Need For Multiple Respondents In Survey Research Of Organizations, Joseph L. Balloun, Hilton Barrett, Art Weinstein
Journal of Modern Applied Statistical Methods
The need for multiple respondents per organization in organizational survey research is supported. Leadership teams’ ratings of their implementations of market orientation are examined, along with learning orientation, entrepreneurial management, and organizational flexibility. Sixty diverse organizations, including not-for-profit organizations in education and healthcare as well as manufacturing and service businesses, were included. The major finding was the large rating variance within the leadership teams of each organization. The results are enlightening and have definite implications for improved design of survey research on organizations.
Maximum Likelihood Solution For The Linear Structural Relationship With Three Parameters Known,
2011
Middlesex University Business School
Maximum Likelihood Solution For The Linear Structural Relationship With Three Parameters Known, Androulla Michaeloudis
Journal of Modern Applied Statistical Methods
A maximum likelihood solution is obtained for the simple linear structural relation model where the underlying incidental distribution and one error variance are assumed known. Expressions for the asymptotic standard errors of the maximum likelihood estimates are obtained and these are verified using a simulation study.
Is Next Twelve Months Period Tumor Recurrence Free Under Restricted Rate Due To Medication? A Probabilistic Warning,
2011
Texas State University
Is Next Twelve Months Period Tumor Recurrence Free Under Restricted Rate Due To Medication? A Probabilistic Warning, Ramalingam Shanmugam
Journal of Modern Applied Statistical Methods
A methodology is formulated to analyze tumor recurrence data when its incidence rate is restricted due to medication. Analytic results are derived to make a probabilistic early warning of tumor recurrence free period of length τ; that is, the chance for a safe period of lengthτ is estimated. The captured data are length biased. Expressions are developed to extract and relate to counterparts of the non-length biased data. Three data sets are considered as illustrations: (1) patients who are given a placebo, (2) patients who are given the medicine pyridoxine and (3) patients who are given the medicine thiotepa.
The Likelihood Of Choosing The Borda-Winner With Partial Preference Rankings Of The Electorate,
2011
University of California, Santa Barbara, CA
The Likelihood Of Choosing The Borda-Winner With Partial Preference Rankings Of The Electorate, Ömer Eğecioğlu, Ayça Ebru Giritligil
Journal of Modern Applied Statistical Methods
Given that n voters report only the first r (1 ≤ r < m) ranks of their linear preference rankings over m alternatives, the likelihood of implementing Borda outcome is investigated. The information contained in the first r ranks is aggregated through a Borda-like method, namely the r-Borda rule. Monte-Carlo simulations are run to detect changes in the likelihood of r-Borda winner(s) to coincide with the original Borda winner(s) as a function of m, n and r. The voters’ preferences are generated through the Impartial Anonymous and Neutral Culture Model, where both the names of the …
