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Articles 1 - 30 of 64
Full-Text Articles in Physical Sciences and Mathematics
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.
A Comparison Of Procedures For The Analysis Of Multivariate Repeated Measurements, Lisa M. Lix, Anita M. Lloyd
A Comparison Of Procedures For The Analysis Of Multivariate Repeated Measurements, Lisa M. Lix, Anita M. Lloyd
Journal of Modern Applied Statistical Methods
Three procedures for analyzing within-subjects effects in multivariate repeated measures designs are compared when group covariances are heterogeneous: the multiple regression model (MRM) with a structured covariance, Johansen’s (1980) procedure, and the multivariate Brown and Forsythe (1974) procedure. A preliminary likelihood ratio test of a Kronecker product covariance structure is sensitive to sample size and derivational assumption violations. Error rates of the procedures are generally well-controlled except when the distribution is skewed. The MRM procedure displayed few power advantages over the other procedures.
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 …
Bayesian Subset Selection Of Binomial Parameters Using Possibly Misclassified Data, James D. Stamey, Thomas L. Bratcher, Dean M. Young
Bayesian Subset Selection Of Binomial Parameters Using Possibly Misclassified Data, James D. Stamey, Thomas L. Bratcher, Dean M. Young
Journal of Modern Applied Statistical Methods
Three Bayesian approaches are considered for the selection of binomial proportion parameters when data is subject to misclassification. The cases where the misclassification is non-differential and differential were considered, thus extending previous work which considered only non-differential misclassification. In this article, various selection criteria are applied to a simulated data set and a real data set.
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.
Optimal Trimming And Outlier Elimination, Philip H. Ramsey, Patricia P. Ramsey
Optimal Trimming And Outlier Elimination, Philip H. Ramsey, Patricia P. Ramsey
Journal of Modern Applied Statistical Methods
Five data sets with known true values are used to determine the optimal number of pairs that should be trimmed in order to produce the minimum relative error. The optimal trimming in the five data sets is found to be 1%, 5%, 7%, 10% and 28%. The 28% rate is shown to be an outlier among the five data sets. Results of four data sets are used to establish cutoff values for outlier detection in two robust methods of outlier detection.
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 Non-Parametric Difference Score: A Workable Solution For Analyzing Two-Wave Change When The Measures Themselves Change Across Waves, Jennifer E. V. Lloyd, Bruno D. Zumbo
The Non-Parametric Difference Score: A Workable Solution For Analyzing Two-Wave Change When The Measures Themselves Change Across Waves, Jennifer E. V. Lloyd, Bruno D. Zumbo
Journal of Modern Applied Statistical Methods
The non-parametric difference score is introduced. It is a workable solution to the problem of analyzing change over two waves (i.e., a pretest-posttest design) when the measures themselves vary over time. An example highlighting the solution’s implementation is provided, as is a discussion of the solution’s assumptions, strengths, and limitations.
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.
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.
Tests For 2 X 2 Tables In Clinical Trials, Vic Hasselblad, Yulia Lokhnygina
Tests For 2 X 2 Tables In Clinical Trials, Vic Hasselblad, Yulia Lokhnygina
Journal of Modern Applied Statistical Methods
Five standard tests are compared: chi-squared, Fisher's exact, Yates’ correction, Fisher’s exact mid-p, and Barnard’s. Yates’ is always inferior to Fisher’s exact. Fisher’s exact is so conservative that one should look for alternatives. For certain sample sizes, Fisher’s mid-p or Barnard’s test maintain the nominal alpha and have superior power.
Semi Parametric Estimation Of Some Reliability Measures Of Geometric Distribution, Mathachan Pathiyil, E.S. Jeevanand
Semi Parametric Estimation Of Some Reliability Measures Of Geometric Distribution, Mathachan Pathiyil, E.S. Jeevanand
Journal of Modern Applied Statistical Methods
Semi parametric estimators of the survival function, the hazard function, and the mean residual life function of geometric distribution using uncensored and Type II censored samples are obtained. The accuracy of the estimators so obtained is investigated empirically using simulated samples. The results are applied to a real life data set for illustration.
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.
Interference On Overlapping Coefficients In Two Exponential Populations, Mohammad Fraiwan Al-Saleh, Hani M. Samawi
Interference On Overlapping Coefficients In Two Exponential Populations, Mohammad Fraiwan Al-Saleh, Hani M. Samawi
Journal of Modern Applied Statistical Methods
Three measures of overlap, namely Matusita’s measureρ , Morisita’s measure λ and Weitzman’s measure Δ are investigated in this article for two exponential populations with different means. It is well that the estimators of those measures of overlap are biased. The bias is of these estimators depends on the unknown overlap parameters. There are no closed-form, exact formulas, for those estimators variances or their exact sampling distributions. Monte Carlo evaluations are used to study the bias and precision of the proposed overlap measures. Bootstrap method and Taylor series approximation are used to construct confidence intervals for the overlap measures
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.
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.
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 …
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, …
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.
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.
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.
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 …
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 …
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.
An Omnibus Test When Using A Regression Estimator With Multiple Predictors, Rand R. Wilcox
An Omnibus Test When Using A Regression Estimator With Multiple Predictors, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
In quantile regression, the goal is to estimate theγ quantile of Y given values for p predictors. Methods for making inferences about the individual slope parameters have been proposed, some of which have been found to perform very well in simulations. But for an omnibus test that all slope parameters are zero, it appears that little is known about how best to proceed. For the special case γ =.5, a drop-in-dispersion test has been recommended, but it requires a large sample size to control the probability of a Type I error and it assumes that the usual error term is …
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.
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 Weighted Moving Average Process For Forcasting, Shou Hsing Shih, Chris P. Tsokos
A Weighted Moving Average Process For Forcasting, Shou Hsing Shih, Chris P. Tsokos
Journal of Modern Applied Statistical Methods
A forecasting model for a nonstationary stochastic realization is proposed based on modifying a given time series into a new k-time moving average time series. The study is based on the autoregressive integrated moving average process along with its analytical constrains. The analytical procedure of the proposed model is given. A stock XYZ selected from the Fortune 500 list of companies and its daily closing price constitute the time series. Both the classical and proposed forecasting models were developed and a comparison of the accuracy of their responses is given.
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.