Open Access. Powered by Scholars. Published by Universities.®
Social and Behavioral Sciences Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Institution
-
- Wayne State University (1088)
- Selected Works (28)
- University of Denver (4)
- Florida International University (2)
- Georgetown University Law Center (1)
-
- Universitas Indonesia (1)
- University of Arkansas, Fayetteville (1)
- University of Connecticut (1)
- University of Nebraska - Lincoln (1)
- University of Nebraska at Omaha (1)
- University of Pennsylvania Carey Law School (1)
- University of Washington Tacoma (1)
- Western Kentucky University (1)
- Western University (1)
- Keyword
-
- Bias (28)
- Monte Carlo simulation (27)
- Bootstrap (26)
- Simulation (25)
- Confidence interval (23)
-
- Power (23)
- Mean squared error (20)
- Effect size (19)
- Robustness (19)
- Type I error (19)
- Monte Carlo (18)
- Sample size (18)
- Multicollinearity (17)
- Permutation test (17)
- Maximum likelihood estimation (16)
- Missing data (16)
- Confidence intervals (15)
- Reliability (14)
- Econometric Methods (13)
- Efficiency (13)
- Heteroscedasticity (13)
- Logistic regression (13)
- SPSS (13)
- P-value (12)
- Simple random sampling (12)
- Estimation (11)
- Meta-analysis (11)
- Nonnormality (11)
- ANOVA (10)
- Autocorrelation (10)
- Publication Year
- Publication
-
- Journal of Modern Applied Statistical Methods (1088)
- Douglas G. Steigerwald (23)
- Electronic Theses and Dissertations (2)
- Human Rights & Human Welfare (2)
- Maher Qumsiyeh (2)
-
- Access*: Interdisciplinary Journal of Student Research and Scholarship (1)
- All Faculty Scholarship (1)
- CHIP Documents (1)
- Department of Management: Faculty Publications (1)
- Electronic Thesis and Dissertation Repository (1)
- FIU Electronic Theses and Dissertations (1)
- Georgetown Law Faculty Publications and Other Works (1)
- Hospitality Review (1)
- Information Systems Undergraduate Honors Theses (1)
- Jurnal Administrasi Bisnis Terapan (1)
- Masters Theses & Specialist Projects (1)
- Payam Mokhtarian (1)
- Publications (1)
- Shimin Zheng (1)
- Srinivasa Rao Gadde Dr. (1)
- Publication Type
- File Type
Articles 1051 - 1080 of 1132
Full-Text Articles in Social and Behavioral Sciences
The Trouble With Interpreting Statistically Nonsignificant Effect Sizes In Single-Study Investigations, Joel R. Levin, Daniel H. Robinson
The Trouble With Interpreting Statistically Nonsignificant Effect Sizes In Single-Study Investigations, Joel R. Levin, Daniel H. Robinson
Journal of Modern Applied Statistical Methods
In this commentary, we offer a perspective on the problem of authors reporting and interpreting effect sizes in the absence of formal statistical tests of their chanceness. The perspective reinforces our previous distinction between single-study investigations and multiple-study syntheses.
A Different Future For Social And Behavioral Science Research, Shlomo S. Sawilowsky
A Different Future For Social And Behavioral Science Research, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
The dissemination of intervention and treatment outcomes as effect sizes bounded by conf idence intervals in order to think meta-analytically was promoted in a recent article in Educational Researcher. I raise concerns with unfettered reporting of effect sizes, point out the con in confidence interval, and caution against thinking meta-analytically. Instead, cataloging effect sizes is recommended for sample size estimation and power analysis to improve social and behavioral science research.
Jmasm6: An Algorithm For Generating Exact Critical Values For The Kruskal-Wallis One-Way Anova, Todd C. Headrick
Jmasm6: An Algorithm For Generating Exact Critical Values For The Kruskal-Wallis One-Way Anova, Todd C. Headrick
Journal of Modern Applied Statistical Methods
A Fortran 77 subroutine is provided for computing exact critical values for the Kruskal-Wallis test on k independent groups with equal or unequal samples sizes. The subroutine requires the user to provide sorting and ranking routines and a uniform pseudo-random number generator. The program is available from the author on request.
A Recursive Algorithm For Fractionally Differencing Long Data Series, Joseph Mccarthy, Robert Disario, Hakan Saraoglu
A Recursive Algorithm For Fractionally Differencing Long Data Series, Joseph Mccarthy, Robert Disario, Hakan Saraoglu
Journal of Modern Applied Statistical Methods
We propose a recursive algorithm to fractionally difference time series data. The algorithm eliminates the need to evaluate the gamma function directly, and hence avoids the overflow problem that arises when fractionally differencing a long data series. The proposed algorithm can be implemented using any general matrix programming language. An implementation using SAS is presented. The algorithm and the code provide a practical approach to including fractional differencing as part of a time series data analysis.
Modeling Correlated Time-Varying Covariate Effects In A Cox-Type Regression Model, Mourad Tighiouart
Modeling Correlated Time-Varying Covariate Effects In A Cox-Type Regression Model, Mourad Tighiouart
Journal of Modern Applied Statistical Methods
In this paper, I extend the proposed model by McKeague and Tighiouart (2000) to handle time-varying correlated covariate effects for the analysis of survival data. I use the conditional predictive ordinates (CPO’s) for model comparison and the methodology is illustrated by an application to nasopharynx cancer survival data. A reversible jump MCMC sampler to estimate the CPO’s will be presented.
Incorporating Sampling Weights Into The Generalizability Theory For Large-Scale Analyses, Christopher W. T. Chiu, Ronald S. Fesco
Incorporating Sampling Weights Into The Generalizability Theory For Large-Scale Analyses, Christopher W. T. Chiu, Ronald S. Fesco
Journal of Modern Applied Statistical Methods
Large scale studies frequently use complex sampling procedures, disproportionate sampling weights, and adjustment techniques to account for potential bias due to nonresponses and to ensure that results from the sample can be generalized to a larger population. Survey researchers are concerned about measurement error and the use of weights in developing models. Consequently, multiple weighting factors are used and these weighting factors are manifested as a final survey (composite) weight available for analysis. We developed a method to incorporate an external weighting factor like this for analyses of measurement errors in the theory of generalizability to provide researchers with a …
A More Efficient Way Of Obtaining A Unique Median Estimate For Circular Data, B. Sango Otieno, Christine M. Anderson-Cook
A More Efficient Way Of Obtaining A Unique Median Estimate For Circular Data, B. Sango Otieno, Christine M. Anderson-Cook
Journal of Modern Applied Statistical Methods
The procedure for computing the sample circular median occasionally leads to a non-unique estimate of the population circular median, since there can sometimes be two or more diameters that divide data equally and have the same circular mean deviation. A modification in the computation of the sample median is suggested, which not only eliminates this non-uniqueness problem, but is computationally easier and faster to work with than the existing alternative.
A Semiparametric Regression Model For Oligonucleotide Arrays, Jianhua Hu, Guosheng Yin
A Semiparametric Regression Model For Oligonucleotide Arrays, Jianhua Hu, Guosheng Yin
Journal of Modern Applied Statistical Methods
A semiparametric model incorporating the spline smoothing technique is proposed to study oligonucleotide gene expression data. No specific parametric functional form is assumed for mismatch probe intensities, which allows much more flexibility in the fitted model. The new approach improves the model fitting, hence the estimation of expression indexes. The method is applied to a data set of 18 HuGeneFL arrays.
The Way Ahead In Qualitative Computing, Tom Richards, Lyn Richards
The Way Ahead In Qualitative Computing, Tom Richards, Lyn Richards
Journal of Modern Applied Statistical Methods
Specialized computer programs for Qualitative Research in social sciences have greatly changed ways of doing QR, the reliability and comprehensiveness of results, the ability to inspect and challenge a researcher’s working, and the relationship with quantitative methods in social research. This article explores these claims in the context of N6 (NUD*IST) and NVivo, the two programs designed by the authors; and considers possible future developments in the field.
Homogeneous Markov Processes For Breast Cancer Analysis, Ricardo Ocaña-Rilola, Emilio Sanchez-Cantalejo, Carmen Martinez-Garcia
Homogeneous Markov Processes For Breast Cancer Analysis, Ricardo Ocaña-Rilola, Emilio Sanchez-Cantalejo, Carmen Martinez-Garcia
Journal of Modern Applied Statistical Methods
Sometimes, the introduction of covariates in stochastic processes is required to study their effect on disease history events. However these types of models increase the complexity of analysis, even for simpler processes, and standard software to analyse stochastic processes is limited. In this paper, a method for fitting homogeneous Markov models with covariates is proposed for analysing breast cancer data. Specific software for this purpose has been implemented.
Jmasm4: Critical Values For Four Nonparametric And/Or Distribution-Free Tests Of Location For Two Independent Samples, Bruce R. Fay
Jmasm4: Critical Values For Four Nonparametric And/Or Distribution-Free Tests Of Location For Two Independent Samples, Bruce R. Fay
Journal of Modern Applied Statistical Methods
Researchers engaged in computer-intensive studies may need exact critical values, especially for sample sizes and alpha levels not normally found in published tables, as well as the ability to control ‘best-fit’ criteria. They may also benefit from the ability to directly generate these values rather than having to create lookup tables. Fortran 90 programs generate ‘best-conservative’ (bc) and ‘best-fit’ (bf) critical values with associated probabilities for the Kolmogorov-Smirnov test of general differences (bc), Rosenbaum’s test of location (bc), Tukey’s quick test (bc and bf)) and the Wilcoxon rank-sum test (bc).
Constructive Criticism, Ronald C. Serlin
Constructive Criticism, Ronald C. Serlin
Journal of Modern Applied Statistical Methods
Attempts to attain knowledge as certified true belief have failed to circumvent Hume’s injunction against induction. Theories must be viewed as unprovable, improbable, and undisprovable. The empirical basis is fallible, and yet the method of conjectures and refutations is untouched by Hume’s insights. The implications for statistical methodology is that the requisite severity of testing is achieved through the use of robust procedures, whose assumptions have not been shown to be substantially violated, to test predesignated range null hypotheses. Nonparametric range null hypothesis tests need to be developed to examine whether or not effect sizes or measures of association, as …
Extensions Of The Concept Of Exchangeability And Their Applications, Phillip I. Good
Extensions Of The Concept Of Exchangeability And Their Applications, Phillip I. Good
Journal of Modern Applied Statistical Methods
Permutation tests provide exact p-values in a wide variety of practical testing situations. But permutation tests rely on the assumption of exchangeability, that is, under the hypothesis, the joint distribution of the observations is invariant under permutations of the subscripts. Observations are exchangeable if they are independent, identically distributed (i.i.d.), or if they are jointly normal with identical covariances. The range of applications of these exact, powerful, distribution-free tests can be enlarged through exchangeability- preserving transforms, asymptotic exchangeability, partial exchangeability, and weak exchangeability. Original exact tests for comparing the slopes of two regression lines and for the analysis of …
Within Groups Multiple Comparisons Based On Robust Measures Of Location, Rand R. Wilcox, H. J. Keselman
Within Groups Multiple Comparisons Based On Robust Measures Of Location, Rand R. Wilcox, H. J. Keselman
Journal of Modern Applied Statistical Methods
Consider the problem of performing all pair-wise comparisons among J dependent groups based on measures of location associated with the marginal distributions. It is well known that the standard error of the sample mean can be large relative to other estimators when outliers are common. Two general strategies for addressing this problem are to trim a fixed proportion of observations or empirically check for outliers and remove (or down-weight) any that are found. However, simply applying conventional methods for means to the data that remain results in using the wrong standard error. Methods that address this problem have been proposed, …
A Comparison Of The D’Agostino S_U Test To The Triples Test For Testing Of Symmetry Versus Asymmetry As A Preliminary Test To Testing The Equality Of Means, Kimberly T. Perry, Michael R. Stoline
A Comparison Of The D’Agostino S_U Test To The Triples Test For Testing Of Symmetry Versus Asymmetry As A Preliminary Test To Testing The Equality Of Means, Kimberly T. Perry, Michael R. Stoline
Journal of Modern Applied Statistical Methods
This paper evaluates the D’Agostino SU test and the Triples test for testing symmetry versus asymmetry. These procedures are evaluated as preliminary tests in the selection of the most appropriate procedure for testing the equality of means with two independent samples under a variety of symmetric and asymmetric sampling situations. Key words: symmetry; asymmetry; preliminary testing.
Adaptive Tests For Ordered Categorical Data, Vance W. Berger, Anastasia Ivanova
Adaptive Tests For Ordered Categorical Data, Vance W. Berger, Anastasia Ivanova
Journal of Modern Applied Statistical Methods
Consider testing for independence against stochastic order in an ordered 2xJ contingency table, under product multinomial sampling. In applications one may wish to exploit prior information concerning the direction of the treatment effect, yet ultimately end up with a testing procedure with good frequentist properties. As such, a reasonable objective may be to simultaneously maximize power at a specified alternative and ensure reasonable power for all other alternatives of interest. For this objective, none of the available testing approaches are completely satisfactory. A new class of admissible adaptive tests is derived. Each test in this class strictly preserves the Type …
Determining Predictor Importance In Multiple Regression Under Varied Correlational And Distributional Conditions, Tiffany A. Whittaker, Rachel T. Fouladi, Natasha J. Williams
Determining Predictor Importance In Multiple Regression Under Varied Correlational And Distributional Conditions, Tiffany A. Whittaker, Rachel T. Fouladi, Natasha J. Williams
Journal of Modern Applied Statistical Methods
This study examines the performance of eight methods of predictor importance under varied correlational and distributional conditions. The proportion of times a method correctly identified the dominant predictor was recorded. Results indicated that the new methods of importance proposed by Budescu (1993) and Johnson (2000) outperformed commonly used importance methods.
Simulation Study Of Chemical Inhibition Modeling, Pali Sen, Mary Anderson
Simulation Study Of Chemical Inhibition Modeling, Pali Sen, Mary Anderson
Journal of Modern Applied Statistical Methods
The combined effects of the activities of different chemicals are of interest of this study. We simulate for the synthetic data, and fit experimental data for three models and estimate the parameters. We assess the fit of the synthetic data and the experimental data by comparing the coefficients of variation for the parameter estimates and identify the best model for the inhibition process.
A Longitudinal Follow-Up Of Discrete Mass At Zero With Gap, Joseph L. Musial, Patrick D. Bridge, Nicol R. Shamey
A Longitudinal Follow-Up Of Discrete Mass At Zero With Gap, Joseph L. Musial, Patrick D. Bridge, Nicol R. Shamey
Journal of Modern Applied Statistical Methods
The first part of this paper discusses a five-year systematic review of the Journal of Consulting and Clinical Psychology following the landmark power study conducted by Sawilowsky and Hillman (1992). The second part discusses a five-year longitudinal follow-up of a radically nonnormal population distribution: discrete mass at zero with gap. This distribution was based upon a real dataset.
Some Reflections On Significance Testing, Thomas R. Knapp
Some Reflections On Significance Testing, Thomas R. Knapp
Journal of Modern Applied Statistical Methods
This essay presents a variation on a theme from my article “The use of tests of statistical significance”, which appeared in the Spring, 1999, issue of Mid-Western Educational Researcher.
Twenty Nonparametric Statistics And Their Large Sample Approximations, Gail F. Fahoome
Twenty Nonparametric Statistics And Their Large Sample Approximations, Gail F. Fahoome
Journal of Modern Applied Statistical Methods
Nonparametric procedures are often more powerful than classical tests for real world data which are rarely normally distributed. However, there are difficulties in using these tests. Computational formulas are scattered throughout the literature, and there is a lack of availability of tables and critical values. The computational formulas for twenty commonly employed nonparametric tests that have large-sample approximations for the critical value are brought together. Because there is no generally agreed upon lower limit for the sample size, Monte Carlo methods were used to determine the smallest sample size that can be used with the respective large-sample approximation. The statistics …
A Test Of Symmetry, Abdul R. Othman, H. J. Keselman, Rand R. Wilcox, Katherine Fradette, A. R. Padmanabhan
A Test Of Symmetry, Abdul R. Othman, H. J. Keselman, Rand R. Wilcox, Katherine Fradette, A. R. Padmanabhan
Journal of Modern Applied Statistical Methods
When data are nonnormal in form classical procedures for assessing treatment group equality are prone to distortions in rates of Type I error and power to detect effects. Replacing the usual means with trimmed means reduces rates of Type I error and increases sensitivity to detect effects. If data are skewed, say to the right, then it has been postulated that asymmetric trimming, to the right, should be better at controlling rates of Type I error and power to detect effects than symmetric trimming from both tails of the data distribution. Keselman, Wilcox, Othman and Fradette (2002) found that Babu, …
Trimming, Transforming Statistics, And Bootstrapping: Circumventing The Biasing Effects Of Heterescedasticity And Nonnormality, H. J. Keselman, Rand R. Wilcox, Abdul R. Othman, Katherine Fradette
Trimming, Transforming Statistics, And Bootstrapping: Circumventing The Biasing Effects Of Heterescedasticity And Nonnormality, H. J. Keselman, Rand R. Wilcox, Abdul R. Othman, Katherine Fradette
Journal of Modern Applied Statistical Methods
Researchers can adopt different measures of central tendency and test statistics to examine the effect of a treatment variable across groups (e.g., means, trimmed means, M-estimators, & medians. Recently developed statistics are compared with respect to their ability to control Type I errors when data were nonnormal, heterogeneous, and the design was unbalanced: (1) a preliminary test for symmetry which determines whether data should be trimmed symmetrically or asymmetrically, (2) two different transformations to eliminate skewness, (3) the accuracy of assessing statistical significance with a bootstrap methodology was examined, and (4) statistics that use a robust measure of the typical …
The Statistical Modeling Of The Fertility Of Chinese Women, Dudley L. Poston Jr.
The Statistical Modeling Of The Fertility Of Chinese Women, Dudley L. Poston Jr.
Journal of Modern Applied Statistical Methods
This article is concerned with the statistical modeling of children ever born (CEB) fertility data. It is shown that in a low fertility population, such as China, the use of linear regression approaches to model CEB is statistically inappropriate because the distribution of the CEB variable is often heavily skewed with a long right tail. For five sub-groups of Chinese women, their fertility is modeled using Poisson, negative binomial, and ordinary least squares (OLS) regression models. It is shown that in almost all instances there would have been major errors of statistical inference had the interpretations of the results been …
Robust Estimation Of Multivariate Failure Data With Time-Modulated Frailty, Pingfu Fu, J. Sunil Rao, Jiming Jiang
Robust Estimation Of Multivariate Failure Data With Time-Modulated Frailty, Pingfu Fu, J. Sunil Rao, Jiming Jiang
Journal of Modern Applied Statistical Methods
A time-modulated frailty model is proposed for analyzing multivariate failure data. The effect of frailties, which may not be constant over time, is discussed. We assume a parametric model for the baseline hazard, but avoid the parametric assumption for the frailty distribution. The well-known connection between survival times and Poisson regression model is used. The parameters of interest are estimated by generalized estimating equations (GEE) or by penalized GEE. Simulation studies show that the procedure is successful to detect the effect of time-modulated frailty. The method is also applied to a placebo controlled randomized clinical trial of gamma interferon, a …
Double Median Ranked Set Sample: Comparing To Other Double Ranked Samples For Mean And Ratio Estimators, Hani M. Samawi, Eman M. Tawalbeh
Double Median Ranked Set Sample: Comparing To Other Double Ranked Samples For Mean And Ratio Estimators, Hani M. Samawi, Eman M. Tawalbeh
Journal of Modern Applied Statistical Methods
Double median ranked set sample (DMRSS) and its properties for estimating the population mean, when the underlying distribution is assumed to be symmetric about its mean, are introduced. Also, the performance of DMRSS with respect to other ranked set samples and double ranked set samples, for estimating the population mean and ratio, is considered. Real data that consist of heights and diameters of 399 trees are used to illustrate the procedure. The analysis and simulation indicate that using DMRSS for estimating the population mean is more efficient than using the other ranked samples and double ranked samples schemes except in …
On The Misuse Of Confidence Intervals For Two Means In Testing For The Significance Of The Difference Between The Means, George W. Ryan, Steven D. Leadbetter
On The Misuse Of Confidence Intervals For Two Means In Testing For The Significance Of The Difference Between The Means, George W. Ryan, Steven D. Leadbetter
Journal of Modern Applied Statistical Methods
Comparing individual confidence intervals of two population means is an incorrect procedure for determining the statistical significance of the difference between the means. We show conditions where confidence intervals for the means from two independent samples overlap and the difference between the means is in fact significant.
Fermat, Schubert, Einstein, And Behrens-Fisher: The Probable Difference Between Two Means When Σ_1^2≠Σ_2^2, Shlomo S. Sawilowsky
Fermat, Schubert, Einstein, And Behrens-Fisher: The Probable Difference Between Two Means When Σ_1^2≠Σ_2^2, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
The history of the Behrens-Fisher problem and some approximate solutions are reviewed. In outlining relevant statistical hypotheses on the probable difference between two means, the importance of the Behrens- Fisher problem from a theoretical perspective is acknowledged, but it is concluded that this problem is irrelevant for applied research in psychology, education, and related disciplines. The focus is better placed on “shift in location” and, more importantly, “shift in location and change in scale” treatment alternatives.
Best Regression Model Using Information Criteria, Phill Gagné, C. Mitchell Dayton
Best Regression Model Using Information Criteria, Phill Gagné, C. Mitchell Dayton
Journal of Modern Applied Statistical Methods
The accuracy of AIC and BIC is evaluated under simulated multiple regression conditions, varying number of total and valid predictors, R2, and n. AIC and BIC were increasingly accurate as n increased and as total predictors decreased. Interactions of the ratio of valid/total predictors affected accuracy.
On The Estimation Of Binomial Success Probability With Zero Occurrence In Sample, Mehdi Razzaghi
On The Estimation Of Binomial Success Probability With Zero Occurrence In Sample, Mehdi Razzaghi
Journal of Modern Applied Statistical Methods
The problem of estimating the probability of a rare event when the sample shows no incidence of the event is considered. Several methodologies based on various statistical techniques are described and their relative performances are investigated. A decision theoretic approach for estimation of response probability when the sample contains zero responses is examined in depth. The properties of each method are discussed and an example from teratology is used to provide illustration and to demonstrate the results.