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Articles 811 - 840 of 1162
Full-Text Articles in Statistics and Probability
Performance Of Some Correlation Coefficients When Applied To Zero-Clustered Data, L. W. Huson
Performance Of Some Correlation Coefficients When Applied To Zero-Clustered Data, L. W. Huson
Journal of Modern Applied Statistical Methods
Zero-clustered data occur widely in medical research and are characterised by the presence of a group of observations of value zero in a distribution of otherwise continuous non-negative responses. A simulation study was conducted to investigate the properties of a number of correlation coefficients applied to samples of zero-clustered data.
Covariate Dependent Markov Models For Analysis Of Repeated Binary Outcomes, M.A. Islam, R.I. Chowdhury, K.P. Singh
Covariate Dependent Markov Models For Analysis Of Repeated Binary Outcomes, M.A. Islam, R.I. Chowdhury, K.P. Singh
Journal of Modern Applied Statistical Methods
The covariate dependence in a higher order Markov models is examined. First order Markov models with covariate dependence are discussed and are generalized for higher order. A simple alternative is also proposed. The estimation procedure is discussed for higher order with a number of covariates. The proposed model takes into account the past transitions. Transitions are fitted and are tested in order to examine their influence on the most recent transitions. Applications are illustrated using maternal morbidity during pregnancy. The binary outcome at each visit during pregnancy is observed for each subject and then the covariate dependent Markov models are …
The Correlation Coefficients, Rudy A. Gideon
The Correlation Coefficients, Rudy A. Gideon
Journal of Modern Applied Statistical Methods
A generalized method of defining and interpreting correlation coefficients is given. Seven correlation coefficients are defined — three for continuous data and four on the ranks of the data. A quick calculation of the rank based correlation coefficients using a 0-1 graph-matrix is shown. Examples and comparisons are given.
A Simple Method For Finding Emperical Liklihood Type Intervals For The Roc Curve, Ayman Baklizi
A Simple Method For Finding Emperical Liklihood Type Intervals For The Roc Curve, Ayman Baklizi
Journal of Modern Applied Statistical Methods
Interval estimation of the ROC curve is considered using the empirical likelihood techniques. Suggested is a procedure that is very simple computationally and avoids the constrained optimization problems usually faced with empirical likelihood methods. Various modifications are suggested and the performance of the intervals is evaluated in terms of their coverage probability. The results show that some of the suggested intervals compete well with other intervals known in the literature.
The Effect Of Garch (1,1) On The Granger Causality Test In Stable Var Models, Panagiotis Mantalos, Ghazi Shukur, Pär Sjölander
The Effect Of Garch (1,1) On The Granger Causality Test In Stable Var Models, Panagiotis Mantalos, Ghazi Shukur, Pär Sjölander
Journal of Modern Applied Statistical Methods
Using Monte Carlo methods, the properties of Granger causality test in stable VAR models are studied under the presence of different magnitudes of GARCH effects in the error terms. Analysis reveals that substantial GARCH effects influence the size properties of the Granger causality test, especially in small samples. The power functions of the test are usually slightly lower when GARCH effects are imposed among the residuals compared with the case of white noise residuals.
Optimum Choice Of Covariates For A Series Of Sbibds Obtained Through Projective Geometry, Ganesh Dutta, Premadhis Das, Nripes Kumar Mandal
Optimum Choice Of Covariates For A Series Of Sbibds Obtained Through Projective Geometry, Ganesh Dutta, Premadhis Das, Nripes Kumar Mandal
Journal of Modern Applied Statistical Methods
A block design set up is considered in presence of a number of controllable covariates. The problem is that of choosing the values of the covariates so that for a given block design, it is optimum in the sense of attaining minimum variance for the estimation of each of the covariate parameters. In case of incomplete block designs, the choice of the values of the covariates depends heavily on the allocation of treatments to the plots of blocks; more specifically on the method of construction of the incomplete block design. In this paper the situation where the block design is …
Reply (To Ian R. White), Kung-Jong Lui
Reply (To Ian R. White), Kung-Jong Lui
Journal of Modern Applied Statistical Methods
No abstract provided.
A New Generalization Of Negative Ploya-Eggenberger Distribution And Its Applications, Anwar Hassan, Sheikh Nilal Ahmad
A New Generalization Of Negative Ploya-Eggenberger Distribution And Its Applications, Anwar Hassan, Sheikh Nilal Ahmad
Journal of Modern Applied Statistical Methods
A new generalization of negative Polya-Eggenberger distribution (GNPED) has been obtained by mixing the negative binomial distribution with generalized beta distribution-Π defined by Nadarajah and Kotz (2003). Some special cases and properties of GNPED have been studied. Further, the proposed model has been fitted to two data sets (used by Gupta & Ong, 2004) that provide a satisfactory fit and better alternative as compared to negative binomial and some of its mixture models and extensions. Also, the negative Polya-Eggenberger distribution (NPED), obtained by mixing negative binomial with beta distribution of I-kind, has been fitted to the same data sets for …
From Information Lost To Knowledge Gained: The Benefits Of Analyzing All The Research Evidence, Joseph L. Balloun, Hilton Barrett
From Information Lost To Knowledge Gained: The Benefits Of Analyzing All The Research Evidence, Joseph L. Balloun, Hilton Barrett
Journal of Modern Applied Statistical Methods
Data analyses should reveal truths about data. To the extent possible analyses should tell a complete picture. Data analyses should not inadvertently ignore phenomena that might be discovered in sample data sets. However, common univariate or multivariate data analysis methods tend to be based on only the means, standard deviations, and Pearson correlations. The result is that many important truths are discovered, but not the whole truth. This article illustrates in a sample data set that (a) data analyses of other properties of variables and groups are feasible and practical, and (b) such analyses may reveal important information not otherwise …
Time-Series Intervention Analysis Using Itsacorr: Fatal Flaws, Bradley E. Huitema, Joseph W. Mckean, Sean Laraway
Time-Series Intervention Analysis Using Itsacorr: Fatal Flaws, Bradley E. Huitema, Joseph W. Mckean, Sean Laraway
Journal of Modern Applied Statistical Methods
The ITSACORR method (Crosbie, 1993, 1995) is evaluated for the analysis of two-phase interrupted time-series designs. It is shown that each component of the ITSACORR framework (including the structural model, the design matrix, the autocorrelation estimator, the ultimate parameter estimation scheme, and the inferential method) contains fatal flaws.
Multiple Comparison Of Medians Using Permutation Tests, Scott J. Richter, Melinda H. Mccann
Multiple Comparison Of Medians Using Permutation Tests, Scott J. Richter, Melinda H. Mccann
Journal of Modern Applied Statistical Methods
A robust method is proposed for simultaneous pairwise comparison using permutation tests and median differences. The new procedure provides strong control of familywise error rate and has better power properties than the median procedure of Nemenyi/Levy. It can be more powerful than the Tukey-Kramer procedure using mean differences, especially for nonnormal distributions and unequal sample sizes.
The Effect Of Different Degrees Of Freedom Of The Chi-Square Distribution On The Statistical Power Of The T, Permutation T, And Wilcoxon Tests, Michèle Weber
Journal of Modern Applied Statistical Methods
The Chi-square distribution is used quite often in Monte Carlo studies to examine statistical power of competing statistics. The power spectrum of the t-test, Wilcoxon test, and permutation t test are compared under various degrees of freedom for this distribution. The two t tests have similar power, which is generally less than the Wilcoxon.
Sensitivity Curves For Asymmetric Trimming Hinge Estimators, D.B. Stark, J.F. Reed Iii
Sensitivity Curves For Asymmetric Trimming Hinge Estimators, D.B. Stark, J.F. Reed Iii
Journal of Modern Applied Statistical Methods
Robust estimators have been developed and tested for symmetric distributions via simulation studies. The primary objective was to show that they are more efficient than the sample mean when used in conjunction with asymmetric distributions. Little attention has been given to how they perform on data that are from asymmetric distributions, or from distributions that have inherent anomalies (messy data). Thus, the behavior of hinge estimators using sensitivity curve are examined.
Large Deviations Techniques For Error Exponents To Multiple Hypothesis Lao Testing, Leader Navaei
Large Deviations Techniques For Error Exponents To Multiple Hypothesis Lao Testing, Leader Navaei
Journal of Modern Applied Statistical Methods
In this article the problem of multiple hypotheses testing using a theory of large deviations is studied. The reliability matrix of Logarithmically Asymptotically Optimal (LAO) tests is introduced and described, and the conditions for the positive of all its elements are indicated.
Longitudinal Evaluation Of Estimates In An Esablishment Survey After Ration Imputation, Adriana Pérez
Longitudinal Evaluation Of Estimates In An Esablishment Survey After Ration Imputation, Adriana Pérez
Journal of Modern Applied Statistical Methods
Researchers evaluated a ratio imputation technique used at the US Survey of Graduate Students and Postdoctorates in Science and Engineering, which is an annually conducted cross-sectional establishment survey. Standardized bias was used, mean square error and relative bias to appraise this imputation method on point and variance estimates via simulations.
A Note On Probability Trees, W. J. Hurley
A Note On Probability Trees, W. J. Hurley
Journal of Modern Applied Statistical Methods
Not many introductory probability and statistics textbooks emphasize the use of probability trees to make complex probability calculations. This is puzzling in view of the power that trees bring to organizing such calculations for students. An effective classroom technique is discussed is this note.
Regarding Lui K. J. (2006). Interval Estimation Of Risk Difference In Simple Compliance Randomized Trials. Jmasm, 5, 395-407., Ian R. White
Regarding Lui K. J. (2006). Interval Estimation Of Risk Difference In Simple Compliance Randomized Trials. Jmasm, 5, 395-407., Ian R. White
Journal of Modern Applied Statistical Methods
No abstract provided.
Probability Coverage And Interval Length For Welch’S And Yuen’S Techniques: Shift In Location, Change In Scale, And (Un)Equal Sizes, S. Jonathan Mends-Cole
Probability Coverage And Interval Length For Welch’S And Yuen’S Techniques: Shift In Location, Change In Scale, And (Un)Equal Sizes, S. Jonathan Mends-Cole
Journal of Modern Applied Statistical Methods
Coverage for Welch’s technique was less than the confidence-level when size was inversely proportional to variance and skewness was extreme. Under negative kurtosis, coverage for Yuen’s technique was attenuated. Under skewness and heteroscedasticity, coverage for Yuen’s technique was more accurate than Welch’s technique.
Global Measure Of The Deviation Of A Wavelet Density Estimator, Kussiy K. Alyass
Global Measure Of The Deviation Of A Wavelet Density Estimator, Kussiy K. Alyass
Journal of Modern Applied Statistical Methods
A wavelet estimator f*(x) of an unknown probability density function f(x)∈L2(R) is considered. A conditional central limit theorem for martingales is used to show that ∫([f *(x) − f (x)]^2)dx is asymptotically normally distributed. Results obtained can be used in a test of goodness-of-fit.
A Modified X̄ Control Chart For Samples Drawn From Finite Populations, Michael B. C. Khoo
A Modified X̄ Control Chart For Samples Drawn From Finite Populations, Michael B. C. Khoo
Journal of Modern Applied Statistical Methods
The X̄ chart works well under the assumption of random sampling from infinite populations. However, many process monitoring scenarios may consist of random sampling from finite populations. A modified X̄ chart is proposed in this article to solve the problems encountered by the standard X̄ chart when samples are drawn from finite populations.
Generalized Linear Mixed-Effects Models For The Analysis Of Odor Detection Data, Sandra Hall, Matthew S. Mayo, Xu-Feng Niu, James C. Walker
Generalized Linear Mixed-Effects Models For The Analysis Of Odor Detection Data, Sandra Hall, Matthew S. Mayo, Xu-Feng Niu, James C. Walker
Journal of Modern Applied Statistical Methods
Olfactory detection has become a science of interest. Seven individuals’ odor detection abilities are explored and an attempt is made to characterize all subjects with one generalized linear mixed effects model. Two methods of fitting the models were used and simulations were conducted to discover which method yielded the best results.
Operating Characteristics Of The Dif Mimic Approach Using Jöreskog’S Covariance Matrix With Ml And Wls Estimation For Short Scales, Michaela N. Gelin, Bruno D. Zumbo
Operating Characteristics Of The Dif Mimic Approach Using Jöreskog’S Covariance Matrix With Ml And Wls Estimation For Short Scales, Michaela N. Gelin, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
Type I error rate of a structural equation modeling (SEM) approach for investigating differential item functioning (DIF) in short scales was studied. Muthén’s SEM model for DIF was examined using a covariance matrix (Jöreskog, 2002). It is conditioned on the latent variable, while testing the effect of the grouping variable over-and-above the underlying latent variable. Thus, it is a multiple-indicators, multiple-causes (MIMIC) DIF model. Type I error rates were determined using data reflective of short scales with ordinal item response formats typically found in the social and behavioral sciences. Results indicate Type I error rates for the DIF MIMIC model, …
Image Reconstruction In Multi-Channel Model Under Gaussian Noise, Veera Holdai, Alexander Korostelev
Image Reconstruction In Multi-Channel Model Under Gaussian Noise, Veera Holdai, Alexander Korostelev
Mathematics Research Reports
The image reconstruction from noisy data is studied. A nonparametric boundary function is estimated from observations in N independent channels in Gaussian white noise. In each channel the image and the background intensities are unknown. They define a non-identifiable nuisance "parameter" that slows down the typical minimax rate of convergence. The large sample asymptotics of the minimax risk is found and an asymptotically optimal estimator for boundary function is suggested.
Ordinal Versions Of Coefficients Alpha And Theta For Likert Rating Scales, Bruno D. Zumbo, Anne M. Gadermann, Cornelia Zeisser
Ordinal Versions Of Coefficients Alpha And Theta For Likert Rating Scales, Bruno D. Zumbo, Anne M. Gadermann, Cornelia Zeisser
Journal of Modern Applied Statistical Methods
Two new reliability indices, ordinal coefficient alpha and ordinal coefficient theta, are introduced. A simulation study was conducted in order to compare the new ordinal reliability estimates to each other and to coefficient alpha with Likert data. Results indicate that ordinal coefficients alpha and theta are consistently suitable estimates of the theoretical reliability, regardless of the magnitude of the theoretical reliability, the number of scale points, and the skewness of the scale point distributions. In contrast, coefficient alpha is in general a negatively biased estimate of reliability. The use of ordinal coefficients alpha and theta as alternatives to coefficient alpha …
Lq-Moments For Statistical Analysis Of Extreme Events, Ani Shabri, Abdul Aziz Jemain
Lq-Moments For Statistical Analysis Of Extreme Events, Ani Shabri, Abdul Aziz Jemain
Journal of Modern Applied Statistical Methods
Statistical analysis of extremes is conducted for predicting large return periods events. LQ-moments that are based on linear combinations are reviewed for characterizing the upper quantiles of distributions and larger events in data. The LQ-moments method is presented based on a new quick estimator using five points quantiles and the weighted kernel estimator to estimate the parameters of the generalized extreme value (GEV) distribution. Monte Carlo methods illustrate the performance of LQ-moments in fitting the GEV distribution to both GEV and non-GEV samples. The proposed estimators of the GEV distribution were compared with conventional L-moments and LQ-moments based on linear …
Jmasm 26: Hettmansperger And Mckean Linear Model Aligned Rank Test For The Single Covariate And One-Way Ancova Case (Sas), Paul A. Nakonezny, Robert D. Shull
Jmasm 26: Hettmansperger And Mckean Linear Model Aligned Rank Test For The Single Covariate And One-Way Ancova Case (Sas), Paul A. Nakonezny, Robert D. Shull
Journal of Modern Applied Statistical Methods
A SAS program (SAS 9.1.3 release, SAS Institute, Cary, N.C.) is presented to implement the Hettmansperger and McKean (1983) linear model aligned rank test (nonparametric ANCOVA) for the single covariate and one-way ANCOVA case. As part of this program, SAS code is also provided to derive the residuals from the regression of Y on X (which is step 1 in the Hettmansperger and McKean procedure) using either ordinary least squares regression (proc reg in SAS) or robust regression with MM estimation (proc robustreg in SAS).
Reliability And Statistical Power: How Measurement Fallibility Affects Power And Required Sample Sizes For Several Parametric And Nonparametric Statistics, Gibbs Y. Kanyongo, Gordon P. Brook, Lydia Kyei-Blankson, Gulsah Gocmen
Reliability And Statistical Power: How Measurement Fallibility Affects Power And Required Sample Sizes For Several Parametric And Nonparametric Statistics, Gibbs Y. Kanyongo, Gordon P. Brook, Lydia Kyei-Blankson, Gulsah Gocmen
Journal of Modern Applied Statistical Methods
The relationship between reliability and statistical power is considered, and tables that account for reduced reliability are presented. A series of Monte Carlo experiments were conducted to determine the effect of changes in reliability on parametric and nonparametric statistical methods, including the paired samples dependent t test, pooled-variance independent t test, one-way analysis of variance with three levels, Wilcoxon signed-rank test for paired samples, and Mann-Whitney-Wilcoxon test for independent groups. Power tables were created that illustrate the reduction in statistical power from decreased reliability for given sample sizes. Sample size tables were created to provide the approximate sample sizes required …
On Flexible Tests Of Independence And Homoscedasticity, Rand R. Wilcox
On Flexible Tests Of Independence And Homoscedasticity, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Consider the nonparametric regression model Y = m(X) + τ(X)ε , where X and ε are independent random variables, ε has a mean of zero and variance σ2, τ is some unknown function used to model heteroscedasticity, and m(X) is an unknown function reflecting some conditional measure of location associated with Y, given X. Detecting dependence, by testing the hypothesis that m(X) does not vary with X, has the potential of being more sensitive to a wider range of associations compared to using Pearson's correlation. This note has two goals. The first is to point …
Using The Fractional Imputation Methodology To Evaluate Variance Due To Hot Deck Imputation In Survey Data, Adriana Pérez
Using The Fractional Imputation Methodology To Evaluate Variance Due To Hot Deck Imputation In Survey Data, Adriana Pérez
Journal of Modern Applied Statistical Methods
This article examines empirically the effect on the variance estimate due to the use of hot deck imputation with a nearest neighbor donor in comparison with the pairwise fractional hot deck imputation methodology in the 1999 Survey of Doctorate Recipients.
A Comparison Of Eight Shrinkage Formulas Under Extreme Conditions, David A. Walker
A Comparison Of Eight Shrinkage Formulas Under Extreme Conditions, David A. Walker
Journal of Modern Applied Statistical Methods
The performance of various shrinkage formulas for estimating the population squared multiple correlation coefficient (ρ2) were compared under extreme conditions often found in educational research with small sample sizes of 10, 15, 20, 25, 30 and regressor variates ranging from 2 to 4. A new formula for estimating ρ2, Adj R2 DW, was examined in terms of its performance under various conditions of N, p, ρ2, along with its bias properties and standard error estimates. The two shrinkage formulas that performed most consistently were the Claudy (Adj R2 C) and Walker (Adj R2 DW)