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Articles 1  30 of 167
FullText Articles in Social and Behavioral Sciences
Food Waste In The United States: Issues, Ethics, And Solutions, Patrick Erickson
Food Waste In The United States: Issues, Ethics, And Solutions, Patrick Erickson
Honors College Theses
Onethird of all food produced for human consumption is lost or wasted globally. In North America and Europe, 280300 kg of food is wasted per capita each year, with more than 40% of the losses occurring at the retail and consumer level. In this paper, I compare the amount of food wasted in the United States to the amounts wasted by different societies around the world, and discuss the reasons for the food waste, and the consequences that the waste has on our society, in terms of resource consumption and production of pollution. The pragmatic philosophy of Richard Rorty states ...
The Effects Of Exercise On Mental Health: A Research Review, Kaylani Benson
The Effects Of Exercise On Mental Health: A Research Review, Kaylani Benson
Honors College Theses
This research review looks at the effects exercise and physical activity have on mental health. The results of this review are based upon the results of the formal studies that have been included. These studies are Benefits of Exercise on Physical and Mental Health in Rheumatoid Arthritis Patients, Exercise Effects on Mental Health of Preschool Children, The Effect of Morning Exercise on Mental Health of Female Police Employees, Exercise and Mental Health of People Living with HIV: A Systemic Review, Exercise Improves Physical Function and Mental Health of Brain Cancer Survivors: Two Exploratory Case Studies, Effect of Yogic and Physical ...
Front Matter, Jmasm Editors
Experimental Design And Data Analysis In Computer Simulation Studies In The Behavioral Sciences, Michael Harwell, Nidhi Kohli, Yadira Peralta
Experimental Design And Data Analysis In Computer Simulation Studies In The Behavioral Sciences, Michael Harwell, Nidhi Kohli, Yadira Peralta
Journal of Modern Applied Statistical Methods
Treating computer simulation studies as statistical sampling experiments subject to established principles of experimental design and data analysis should further enhance their ability to inform statistical practice and a program of statistical research. Latin hypercube designs to enhance generalizability and metaanalytic methods to analyze simulation results are presented.
Missing Data In Longitudinal Surveys: A Comparison Of Performance Of Modern Techniques, Paola Zaninotto, Amanda Sacker
Missing Data In Longitudinal Surveys: A Comparison Of Performance Of Modern Techniques, Paola Zaninotto, Amanda Sacker
Journal of Modern Applied Statistical Methods
Using a simulation study, the performance of complete case analysis, full information maximum likelihood, multivariate normal imputation, multiple imputation by chained equations and twofold fully conditional specification to handle missing data were compared in longitudinal surveys with continuous and binary outcomes, missing covariates, and an interaction term.
On Poisson QuasiLindley Distribution And Its Applications, Razika Grine, Halim Zeghdoudi
On Poisson QuasiLindley Distribution And Its Applications, Razika Grine, Halim Zeghdoudi
Journal of Modern Applied Statistical Methods
This paper proposes a recent version of compound Poisson distributions named the Poisson quasiLindley (PQL) distribution by compounding Poisson and quasiLindley distributions. Some properties of the distributions are given with estimation and some illustrative examples.
A Remark For The Admissibility Of Rao’S UTest, Z. D. Bai, C. R. Rao, M. T. Tsai
A Remark For The Admissibility Of Rao’S UTest, Z. D. Bai, C. R. Rao, M. T. Tsai
Journal of Modern Applied Statistical Methods
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Jmasm 47: Anova_Hov: A Sas Macro For Testing Homogeneity Of Variance In OneFactor Anova Models (Sas), Isaac Li, YiHsin Chen, Yan Wang, Patricia RodríGuez De Gil, Thanh Pham, Diep Nguyen, Eun Sook Kim, Jeffrey D. Kromrey
Jmasm 47: Anova_Hov: A Sas Macro For Testing Homogeneity Of Variance In OneFactor Anova Models (Sas), Isaac Li, YiHsin Chen, Yan Wang, Patricia RodríGuez De Gil, Thanh Pham, Diep Nguyen, Eun Sook Kim, Jeffrey D. Kromrey
Journal of Modern Applied Statistical Methods
Variance homogeneity (HOV) is a critical assumption for ANOVA whose violation may lead to perturbations in Type I error rates. Minimal consensus exists on selecting an appropriate test. This SAS macro implements 14 different HOV approaches in oneway ANOVA. Examples are given and practical issues discussed.
Jmasm 48: The Pearson ProductMoment Correlation Coefficient And Adjustment Indices: The Fisher Approximate Unbiased Estimator And The OlkinPratt Adjustment (Spss), David A. Walker
Journal of Modern Applied Statistical Methods
This syntax program is intended to provide an application, not readily available, for users in SPSS who are interested in the Pearson product–moment correlation coefficient (r) and r biased adjustment indices such as the Fisher Approximate Unbiased estimator and the Olkin and Pratt adjustment.
Jmasm 50: A WebBased Shiny Application For Conducting A Two Dependent Samples Maximum Test (R), Saverpierre Maggio, Gokul Bhandari, Shlomo S. Sawilowsky
Jmasm 50: A WebBased Shiny Application For Conducting A Two Dependent Samples Maximum Test (R), Saverpierre Maggio, Gokul Bhandari, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
A webbased Shiny application written in R statistical language was developed and deployed online to calculate a new two dependent samples maximum test as presented in Maggio and Sawilowsky (2014b). The maximum test allows researchers to conduct both the dependent samples ttest and Wilcoxon signedranks tests on same data without raising concerns associated with Type I error inflation and choice of statistical tests (Maggio and Sawilowsky, 2014a). The maximum test in R statistical language provides a friendly user interface.
Study Evaluating The Alterations Caused In An Exploratory Factor Analysis When Multivariate Normal Data Is Dichotomized, Rosilei S. Novak, Jair M. Marques
Study Evaluating The Alterations Caused In An Exploratory Factor Analysis When Multivariate Normal Data Is Dichotomized, Rosilei S. Novak, Jair M. Marques
Journal of Modern Applied Statistical Methods
The relationships resulting from the dichotomization of multivariate normal data is a question that causes concern when using exploratory factor analysis. The relationships in an exploratory factor analysis are examined when multivariate normal data, generated by Monte Carlo methods, is dichotomized.
Robust Measures Of Variable Importance For Multivariate Group Designs, Tolulope T. Sajobi, Lisa M. Lix
Robust Measures Of Variable Importance For Multivariate Group Designs, Tolulope T. Sajobi, Lisa M. Lix
Journal of Modern Applied Statistical Methods
Variable importance measures based on discriminant analysis and multivariate analysis of variance are useful for identifying variables that discriminate between two groups in multivariate group designs. Variable importance measures are developed based on trimmed and Winsorized estimators for describing group differences in multivariate nonnormal populations.
Characterizations Of Distributions By Expected Values Of Lower Record Statistics With Spacing, M. Faizan, Ziaul Haque, M. A. Ansari
Characterizations Of Distributions By Expected Values Of Lower Record Statistics With Spacing, M. Faizan, Ziaul Haque, M. A. Ansari
Journal of Modern Applied Statistical Methods
The characterizations of a certain class of probability distributions are established through conditional expectation of lower record values when the conditioned record value may not be the adjacent one. Some of its important deductions are also discussed.
A Double Ewma Control Chart For The Individuals Based On A Linear Prediction, Rafael Perez Abreu, Jay R. Schaffer
A Double Ewma Control Chart For The Individuals Based On A Linear Prediction, Rafael Perez Abreu, Jay R. Schaffer
Journal of Modern Applied Statistical Methods
Industrial process use single and double Exponential Weighted Moving Average control charts to detect small shifts in it. Occasionally there is a need to detect small trends instead of shifts, but the effectiveness to detect small trends. A new control chart is proposed to detect a small drift.
Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data, Yue Fang Loh, Jayanthi Arasan, Habshah Midi, M. R. Abu Bakar
Inferential Procedures For Log Logistic Distribution With Doubly Interval Censored Data, Yue Fang Loh, Jayanthi Arasan, Habshah Midi, M. R. Abu Bakar
Journal of Modern Applied Statistical Methods
The log logistic model with doubly interval censored data is examined. Three methods of constructing confidence interval estimates for the parameter of the model were compared and discussed. The results of the coverage probability study indicated that the Wald outperformed the likelihood ratio and jackknife inferential procedures.
Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya
Bayesian Hypothesis Testing Of Two Normal Samples Using Bootstrap Prior Technique, Oyebayo Ridwan Olaniran, Waheed Babatunde Yahya
Journal of Modern Applied Statistical Methods
The most important ingredient in Bayesian analysis is prior or prior distribution. A new prior determination method was developed under the framework of parametric empirical Bayes using bootstrap technique. By way of example, Bayesian estimations of the parameters of a normal distribution with unknown mean and unknown variance conditions were considered, as well as its application in comparing the means of two independent normal samples with several scenarios. A Monte Carlo study was conducted to illustrate the proposed procedure in estimation and hypothesis testing. Results from Monte Carlo studies showed that the bootstrap prior proposed is more efficient than the ...
Citizens For Peace Activities & Accomplishments 2017, Ann Abdoo
Citizens For Peace Activities & Accomplishments 2017, Ann Abdoo
Citizens for Peace
No abstract provided.
The Regression Smoother Lowess: A Confidence Band That Allows Heteroscedasticity And Has Some Specified Simultaneous Probability Coverage, Rand Wilcox
Journal of Modern Applied Statistical Methods
Many nonparametric regression estimators (smoothers) have been proposed that provide a more flexible method for estimating the true regression line compared to using some of the more obvious parametric models. A basic goal when using any smoother is computing a confidence band for the true regression line. Let M(YX) be some conditional measure of location associated with the random variable Y, given X and let x be some specific value of the covariate. When using the LOWESS estimator, an extant method that assumes homoscedasticity can be used to compute a confidence interval for M(YX = x). A ...
The Impact Of Predictor Variable(S) With Skewed Cell Probabilities On Wald Tests In Binary Logistic Regression, Arwa Alkhalaf, Bruno D. Zumbo
The Impact Of Predictor Variable(S) With Skewed Cell Probabilities On Wald Tests In Binary Logistic Regression, Arwa Alkhalaf, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
A series of simulation studies are reported that investigated the impact of a skewed predictor(s) on the Type I error rate and power of the Wald test in a logistic regression model. Five simulations were conducted for three different regression models. A detailed description of the impact of skewed cell predictor probabilities and sample size provide guidelines for practitioners wherein to expect the greatest problems.
Using Pratt's Importance Measures In Confirmatory Factor Analyses, Amrey D. Wu, Bruno D. Zumbo
Using Pratt's Importance Measures In Confirmatory Factor Analyses, Amrey D. Wu, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
When running a confirmatory factor analysis (CFA), users specify and interpret the pattern (loading) matrix. It has been recommended that the structure coefficients, indicating the factors’ correlation with the observed indicators, should also be reported when the factors are correlated (Graham, Guthrie, & Thompson, 2003; Thompson, 1997). The aims of this article are: (1) to note the structure coefficient should be interpreted with caution if the factors are specified to correlate. Because the structure coefficient is a zeroorder correlation, it may be partially or entirely a reflection of factor correlations. This is elucidated by the matrix algebra of the structure coefficients based on ...
On Variance Balanced Designs, Dilip Kumar Ghosh, Sangeeta Ahuja
On Variance Balanced Designs, Dilip Kumar Ghosh, Sangeeta Ahuja
Journal of Modern Applied Statistical Methods
Balanced incomplete block designs are not always possible to construct because of their parametric relations. In such a situation another balanced design, the variance balanced design, is required. This construction of binary, equal replicated variance balanced designs are discussed using the half fraction of the 2n factorial designs with smaller block sizes. This method was also extended to construct another variance balanced design by deleting the last block of the resulting variance balanced designs. Its efficiency factor compared with randomized block designs was compared and found to be highly efficient.
Unit Root Test For Panel Data Ar(1) Time Series Model With Linear Time Trend And Augmentation Term: A Bayesian Approach, Jitendra Kumar, Anoop Chaturvedi, Umme Afifa, Shafat Yousuf, Saurabh Kumar
Unit Root Test For Panel Data Ar(1) Time Series Model With Linear Time Trend And Augmentation Term: A Bayesian Approach, Jitendra Kumar, Anoop Chaturvedi, Umme Afifa, Shafat Yousuf, Saurabh Kumar
Journal of Modern Applied Statistical Methods
The univariate time series models, in the case of unit root hypothesis, are more biased towards the acceptance of the Unit Root Hypothesis especially in a short time span. However, the panel data time series model is more appropriate in such situation. The Bayesian analysis of unit root testing for a panel data time series model is considered. An autoregressive panel data AR(1) model with linear time trend and augmentation term has been considered and derived the posterior odds ratio for testing the presence of unit root hypothesis under appropriate prior assumptions. A simulation study and real data analysis ...
Performance Evaluation Of Confidence Intervals For Ordinal Coefficient Alpha, Heather J. Turner, Prathiba Natesan, Robin K. Henson
Performance Evaluation Of Confidence Intervals For Ordinal Coefficient Alpha, Heather J. Turner, Prathiba Natesan, Robin K. Henson
Journal of Modern Applied Statistical Methods
The aim of this study was to investigate the performance of the Fisher, Feldt, Bonner, and Hakstian and Whalen (HW) confidence intervals methods for the nonparametric reliability estimate, ordinal alpha. All methods yielded unacceptably low coverage rates and potentially increased TypeI error rates.
Effectively Comparing Differences In Proportions, Lonnie Turpin Jr.
Effectively Comparing Differences In Proportions, Lonnie Turpin Jr.
Journal of Modern Applied Statistical Methods
A single framework of developing and implementing tests about proportions is outlined. It avoids some of the pitfalls of methods commonly put forward in an introductory data analysis course.
'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means TTest Interpretations, Anthony M. Gould, JeanEtienne Joullié
'Parallel Universe' Or 'Proven Future'? The Language Of Dependent Means TTest Interpretations, Anthony M. Gould, JeanEtienne Joullié
Journal of Modern Applied Statistical Methods
Of the three kinds of twomean comparisons which judge a test statistic against a critical value taken from a Student tdistribution, one – the repeated measures or dependentmeans application – is distinctive because it is meant to assess the value of a parameter which is not part of the natural order. This absence forces a choice between two interpretations of a significant test result and the meaning of the test hypothesis. The parallel universe view advances a conditional, backwardlooking conclusion. The more practical proven future interpretation is a nonconditional proposition about what will happen if an intervention is (now) applied to each ...
Power And Sample Size Estimation For Nonparametric Composite Endpoints: Practical Implementation Using Data Simulations, Paul M. Brown, Justin A. Ezekowitz
Power And Sample Size Estimation For Nonparametric Composite Endpoints: Practical Implementation Using Data Simulations, Paul M. Brown, Justin A. Ezekowitz
Journal of Modern Applied Statistical Methods
Composite endpoints are a popular outcome in controlled studies. However, the required sample size is not easily obtained due to the assortment of outcomes, correlations between them and the way in which the composite is constructed. Data simulations are required. A macro is developed that enables sample size and power estimation.
A Monte Carlo Study Of The Effects Of Variability And Outliers On The Linear Correlation Coefficient, Hussein Yousif Eledum
A Monte Carlo Study Of The Effects Of Variability And Outliers On The Linear Correlation Coefficient, Hussein Yousif Eledum
Journal of Modern Applied Statistical Methods
Monte Carlo simulations are used to investigate the effect of two factors, the amount of variability and an outlier, on the size of the Pearson correlation coefficient. Some simulation algorithms are developed, and two theorems for increasing or decreasing the amount of variability are suggested.
Parameter Estimation In Weighted Rayleigh Distribution, M. Ajami, S. M. A. Jahanshahi
Parameter Estimation In Weighted Rayleigh Distribution, M. Ajami, S. M. A. Jahanshahi
Journal of Modern Applied Statistical Methods
A weighted model based on the Rayleigh distribution is proposed and the statistical and reliability properties of this model are presented. Some nonBayesian and Bayesian methods are used to estimate the β parameter of proposed model. The Bayes estimators are obtained under the symmetric (squared error) and the asymmetric (linear exponential) loss functions using noninformative and reciprocal gamma priors. The performance of the estimators is assessed on the basis of their biases and relative risks under the two abovementioned loss functions. A simulation study is constructed to evaluate the ability of considered estimation methods. The suitability of the proposed model ...
Modeling Agreement Between Binary Classifications Of Multiple Raters In R And Sas, Aya A. Mitani, Kerrie P. Nelson
Modeling Agreement Between Binary Classifications Of Multiple Raters In R And Sas, Aya A. Mitani, Kerrie P. Nelson
Journal of Modern Applied Statistical Methods
Cancer screening and diagnostic tests often are classified using a binary outcome such as diseased or not diseased. Recently largescale studies have been conducted to assess agreement between many raters. Measures of agreement using the class of generalized linear mixed models were implemented efficiently in four recently introduced R and SAS packages in largescale agreement studies incorporating binary classifications. Simulation studies were conducted to compare the performance across the packages and apply the agreement methods to two cancer studies.
SemiParametric Method To Estimate The TimeToFailure Distribution And Its Percentiles For Simple Linear Degradation Model, Laila Naji Ba Dakhn, Mohammed AlHaj Ebrahem, Omar Eidous
SemiParametric Method To Estimate The TimeToFailure Distribution And Its Percentiles For Simple Linear Degradation Model, Laila Naji Ba Dakhn, Mohammed AlHaj Ebrahem, Omar Eidous
Journal of Modern Applied Statistical Methods
Most reliability studies obtained reliability information by using degradation measurements over time, which contains useful data about the product reliability. Parametric methods like the maximum likelihood (ML) estimator and the ordinary least square (OLS) estimator are used widely to estimate the timetofailure distribution and its percentiles. In this article, we estimate the timetofailure distribution and its percentiles by using a semiparametric estimator that assumes the parametric function to have a half normal distribution or an exponential distribution. The performance of the semiparametric estimator is compared via simulation study with the ML and OLS estimators by using the mean square error ...