Ranked Set Sampling Using Auxiliary Variables Of A Randomized Response Procedure For Estimating The Mean Of A Sensitive Quantitative Character,
2010
Universidad de la Habana, Havana, Cuba
Ranked Set Sampling Using Auxiliary Variables Of A Randomized Response Procedure For Estimating The Mean Of A Sensitive Quantitative Character, Carlos N. Bouza
Journal of Modern Applied Statistical Methods
The analysis of the behavior of estimators of the mean of a sensitive variable is considered when a randomized response procedure is used. The results deal with the inference based on simple random sampling with replacement study design. A study of the behavior of the procedures for a ranked set sampling design is developed. A gain in accuracy is generally associated with the proposed alternative model.
An Equivalence Test Based On N And P,
2010
Koblenz University of Applied Sciences, Remagen, Germany
An Equivalence Test Based On N And P, Markus Neuhäeuser
Journal of Modern Applied Statistical Methods
An equivalence test is proposed which is based on the P-value of a test for a difference and the sample size. This test may be especially appropriate for an exploratory re-analysis if only a non-significant test for a difference was reported. Thus, neither a confidence interval is available, nor is there access to the raw data. The test is illustrated using two examples; for both applications the smallest equivalence range for which equivalence could be demonstrated is calculated.
The Effectiveness Of Stepwise Discriminant Analysis As A Post Hoc Procedure To A Significant Manova,
2010
Utah Valley University
The Effectiveness Of Stepwise Discriminant Analysis As A Post Hoc Procedure To A Significant Manova, Erik L. Heiny, Daniel J. Mundform
Journal of Modern Applied Statistical Methods
The effectiveness of SWDA as a post hoc procedure in a two-way MANOVA was examined using various numbers of dependent variables, sample sizes, effect sizes, correlation structures, and significance levels. The procedure did not work well in general except with small numbers of variables, larger samples and low correlations between variables.
Model Based Vs. Model Independent Tests For Cross-Correlation,
2010
Jönköping International Business School, Sweden
Model Based Vs. Model Independent Tests For Cross-Correlation, H.E.T. Holgersson, Peter S. Karlsson
Journal of Modern Applied Statistical Methods
This article discusses the issue of whether cross correlation should be tested by model dependent or model independent methods. Several different tests are proposed and their main properties are investigated analytically and with simulations. It is argued that model independent tests should be used in applied work.
On Exact 100(1-Α)% Confidence Interval Of Autocorrelation Coefficient In Multivariate Data When The Errors Are Autocorrelated,
2010
Columbus State University
On Exact 100(1-Α)% Confidence Interval Of Autocorrelation Coefficient In Multivariate Data When The Errors Are Autocorrelated, Madhusudan Bhandary
Journal of Modern Applied Statistical Methods
An exact 100(1−α)% confidence interval for the autocorrelation coefficient ρ is derived based on a single multinormal sample. The confidence interval is the interval between the two roots of a quadratic equation in ρ . A real life example is also presented.
The Performance Of Multiple Imputation For Likert-Type Items With Missing Data,
2010
University of Florida
The Performance Of Multiple Imputation For Likert-Type Items With Missing Data, Walter Leite, S. Natasha Beretvas
Journal of Modern Applied Statistical Methods
The performance of multiple imputation (MI) for missing data in Likert-type items assuming multivariate normality was assessed using simulation methods. MI was robust to violations of continuity and normality. With 30% of missing data, MAR conditions resulted in negatively biased correlations. With 50% missingness, all results were negatively biased.
Median-Unbiased Optimal Smoothing And Trend Extraction,
2010
University of Peloponnese, Tripolis, Greece
Median-Unbiased Optimal Smoothing And Trend Extraction, Dimitrios D. Thomakos
Journal of Modern Applied Statistical Methods
The problem of smoothing a time series for extracting its low frequency characteristics, collectively called its trend, is considered. A competitive approach is proposed and compared with existing methods in choosing the optimal degree of smoothing based on the distribution of the residuals from the smooth trend.
On A Comparison Between Two Measures Of Spatial Association,
2010
Al-Zaytoonah University of Jordan
On A Comparison Between Two Measures Of Spatial Association, Faisal G. Khamis, Abdul Aziz Jemain, Kamarulzaman Ibrahim
Journal of Modern Applied Statistical Methods
Two measures of spatial association between two variables were used by many researchers. These are the Wartenberg (1985) and Lee (2001) measures. Based on simulation for lattice data, the sensitivity of both measures was studied and compared with different choices of spatial structures, spatial weights and sample sizes using bias and mean square error. Different scenarios are used in terms of assumed numbers and sample sizes. Moran’s I is used to examine the spatial autocorrelation of such a variable with itself. Both the Wartenberg and Lee measures are found to be sensitive, however, Wartenberg’s measure is found to be somewhat …
An Evaluation Of Multiple Imputation For Meta-Analytic Structural Equation Modeling,
2010
Georgia State University
An Evaluation Of Multiple Imputation For Meta-Analytic Structural Equation Modeling, Carolyn F. Furlow, S. Natasha Beretvas
Journal of Modern Applied Statistical Methods
A simulation study was used to evaluate multiple imputation (MI) to handle MCAR correlations in the first step of meta-analytic structural equation modeling: the synthesis of the correlation matrix and the test of homogeneity. No substantial parameter bias resulted from using MI. Although some SE bias was found for meta-analyses involving smaller numbers of studies, the homogeneity test was never rejected when using MI.
Impact Of Measurement Model Modification On Structural Parameter Integrity When Measurement Model Is Misspecified,
2010
University of Houston
Impact Of Measurement Model Modification On Structural Parameter Integrity When Measurement Model Is Misspecified, Weihua Fan
Journal of Modern Applied Statistical Methods
In the process of model modification, parameters of residual covariances are often treated as free parameters to improve model fit. However, the effect of such measurement model modifications on the important structural parameter estimates under various measurement model misspecifications has not been systematically studied. Monte Carlo simulation was conducted to compare structural estimates before and after measurement model modifications of adding residual covariances under varying sample sizes and model misspecifications. Results showed that researchers should pay attention when such measurement model modifications are made to initially misspecified model with missing path(s).
Can Specification Searches Be Useful For Hypothesis Generation?,
2010
Arizona State University
Can Specification Searches Be Useful For Hypothesis Generation?, Samuel B. Green, Marilyn S. Thompson
Journal of Modern Applied Statistical Methods
Previous studies suggest that results from specification searches, as typically employed in structural equation modeling, should not be used to reach strong research conclusions due to their poor reliability. Analyses of computer generated data indicate that search results can be sufficiently reliable for exploratory purposes with properly designed and analyzed studies.
Measuring Openness,
2010
Studi Interdisciplinari, Italy
Measuring Openness, Gaetano Ferrieri
Journal of Modern Applied Statistical Methods
A method for measuring international openness is elaborated. This synthetic indicator measures the capacity of countries for a given phenomenon adjusted for their weight in the same phenomenon. The method implemented and applied to international trade and illustrated here as a case study in merchandise exports, has a wide range of applications in the socio-economic field.
On The Appropriate Transformation Technique And Model Selection In Forecasting Economic Time Series: An Application To Botswana Gdp Data,
2010
University of Botswana
On The Appropriate Transformation Technique And Model Selection In Forecasting Economic Time Series: An Application To Botswana Gdp Data, D. K. Shangodoyin, K. Setlhare, K. K. Moseki, K. Sediakgotla
Journal of Modern Applied Statistical Methods
Selected data transformation techniques in time series modeling are evaluated using real-life data on Botswana Gross Domestic Product (GDP). The transformation techniques considered were modified, although reasonable estimates of the original with no significant difference at α = 0.05 level were obtained: minimizing square of first difference (MFD) and minimizing square of second difference (MSD) provided the best transformation for GDP, whereas the Goldstein and Khan (GKM) method had a deficiency of losing data points. The Box-Jenkins procedure was adapted to fit suitable ARIMA (p, d, q) models to both the original and transformed series, with AIC and SIC as …
A New Biased Estimator Derived From Principal Component Regression Estimator,
2010
Universiti Teknologi MARA, Malaysia
A New Biased Estimator Derived From Principal Component Regression Estimator, Set Foong Ng, Heng Chin Low, Soon Hoe Quah
Journal of Modern Applied Statistical Methods
A new biased estimator obtained by combining the Principal Component Regression Estimator and the special case of Liu-type estimator is proposed. The properties of the new estimator are derived and comparisons between the new estimator and other estimators in terms of mean squared error are presented.
Optimal Meter Placement By Reconciliation Conventional Measurements And Phasor Measurement Units (Pmus),
2010
Shiraz University, Iran
Optimal Meter Placement By Reconciliation Conventional Measurements And Phasor Measurement Units (Pmus), Reza Kaihani, Ali Reza Seifi
Journal of Modern Applied Statistical Methods
The success of state estimation depends on the number, type and location of the established meters and RTUs on the system. A new method by incorporating conventional measurements and New Technology of Phasor Measurement Units (PMU) is proposed. Conventional meters (power injection and power flow measurements) are allocated in order to reduce the number of meters, RTUs, critical measurements, critical sets and leverage points, and also to improve the numerical stability of equations; a genetic algorithm is used for optimization. A second step involves adding PMUs in areas in which it is expected that the accuracy of state estimation will …
Fisher Was Right,
2010
University of Wisconsin - Madison
Fisher Was Right, Ronald C. Serlin
Journal of Modern Applied Statistical Methods
Invited address presented to the Educational Statistician’s Special Interest Group at the annual meeting of the American Educational Research Association, Denver, May 1, 2010.
Inferences About The Population Mean: Empirical Likelihood Versus Bootstrap-T,
2010
University of Southern California
Inferences About The Population Mean: Empirical Likelihood Versus Bootstrap-T, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
The problem of making inferences about the population mean, μ, is considered. Known theoretical results suggest that a Bartlett corrected empirical likelihood method is preferable to two basic bootstrap techniques: a symmetric two-sided bootstrap-t and an equal-tailed bootstrap-t. However, simulations in this study indicate that, when the sample size is small, these two bootstrap methods are generally better in terms of Type I errors and probability coverage. As the sample size increases, situations are found where the Bartlett corrected empirical likelihood method performs better than the equal-tailed bootstrap-t, but the symmetric bootstrap-t gives the best results. None of the four …
The Influence Of Data Generation On Simulation Study Results: Tests Of Mean Differences,
2010
Educational Testing Service, Princeton, NJ
The Influence Of Data Generation On Simulation Study Results: Tests Of Mean Differences, Tim Moses, Alan Klockars
Journal of Modern Applied Statistical Methods
Type I error and power of the standard independent samples t-test were compared with the trimmed and Winsorized t-test with respect to continuous distributions and various discrete distributions known to occur in applied data. The continuous and discrete distributions were generated with similar levels of skew and kurtosis but the discrete distributions had a variety of structural features not reflected in the continuous distributions. The results showed that the Type I error rates of the t-tests were not seriously affected, but the power rate of the trimmed and Winsorized t-test varied greatly across the considered distributions.
The Small-Sample Efficiency Of Some Recently Proposed Multivariate Measures Of Location,
2010
University of Hong Kong
The Small-Sample Efficiency Of Some Recently Proposed Multivariate Measures Of Location, Marie Ng, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Numerous multivariate robust measures of location have been proposed and many have been found to be unsatisfactory in terms of their small-sample efficiency. Several new measures of location have recently been derived, however, nothing is known about their small-sample efficiency or how they compare to the sample mean under normality. This research compared the efficiency for p = 2, 5, and 8 with sample sizes n = 20 and 50 for p-variate data. Although previous studies indicate that so-called skipped estimators are efficient, this study found that variations of this approach can perform poorly when n is small and p …
Assessing Classification Bias In Latent Class Analysis: Comparing Resubstitution And Leave-One-Out Methods,
2010
Association of American Medical Colleges
Assessing Classification Bias In Latent Class Analysis: Comparing Resubstitution And Leave-One-Out Methods, Marc H. Kroopnick, Jinsong Chen, Jaehwa Choi, C. Mitchell Dayton
Journal of Modern Applied Statistical Methods
This Monte Carlo simulation study assessed the degree of classification success associated with resubstitution methods in latent class analysis (LCA) and compared those results to those of the leaveone- out (L-O-O) method for computing classification success. Specifically, this study considered a latent class model with two classes, dichotomous manifest variables, restricted conditional probabilities for each latent class and relatively small sample sizes. The performance of resubstitution and L-O-O methods on the lambda classification index was assessed by examining the degree of bias.
