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Articles 661 - 690 of 1133
Full-Text Articles in Statistical Theory
Nonlinear Parameterization In Bi-Criteria Sample Balancing, Stan Lipovetsky
Nonlinear Parameterization In Bi-Criteria Sample Balancing, Stan Lipovetsky
Journal of Modern Applied Statistical Methods
Sample balancing is widely used in applied research to adjust a sample data to achieve better correspondence to Census statistics. The classic Deming-Stephan iterative proportional approach finds the weights of observations by fitting the cross-tables of sample counts to known margins. This work considers a bi-criteria objective for finding weights with maximum possible effective base size. This approach is presented as a ridge regression with the exponential nonlinear parameterization that produces nonnegative weights for sample balancing.
Jmasm30 Pi-Lca: A Sas Program Computing The Two-Point Mixture Index Of Fit For Two-Class Lca Models With Dichotomous Variables (Sas), Dongquan Zhang, C. Mitchell Dayton
Jmasm30 Pi-Lca: A Sas Program Computing The Two-Point Mixture Index Of Fit For Two-Class Lca Models With Dichotomous Variables (Sas), Dongquan Zhang, C. Mitchell Dayton
Journal of Modern Applied Statistical Methods
The two-point mixture index of fit enjoys some desirable features in model fit assessment and model selection, however, a need exists for efficient computational strategies. Applying an NLP algorithm, a program using the SAS matrix language is presented to estimate the two-point index of fit for two-class LCA models with dichotomous response variables. The program offers a tool to compute π ∗ for twoclass models and it also provides an alternative program for conducting latent class analysis with SAS. This study builds a foundation for further research on computational approaches for M-class models.
Another Look At Resampling: Replenishing Small Samples With Virtual Data Through S-Smart, Haiyan Bai, Wei Pan, Leigh Lihshing Wang, Phillip Neal Ritchey
Another Look At Resampling: Replenishing Small Samples With Virtual Data Through S-Smart, Haiyan Bai, Wei Pan, Leigh Lihshing Wang, Phillip Neal Ritchey
Journal of Modern Applied Statistical Methods
A new resampling method is introduced to generate virtual data through a smoothing technique for replenishing small samples. The replenished analyzable sample retains the statistical properties of the original small sample, has small standard errors and possesses adequate statistical power.
Estimations On The Generalized Exponential Distribution Using Grouped Data, Hassan Pazira, Parviz Nasiri
Estimations On The Generalized Exponential Distribution Using Grouped Data, Hassan Pazira, Parviz Nasiri
Journal of Modern Applied Statistical Methods
Classical and Bayesian estimators are obtained for the shape parameter of the Generalized-Exponential distribution under grouped data. In Bayesian estimation, three types of loss functions are considered: the Squared Error loss function which is classified as a symmetric function, the LINEX and Precautionary loss functions which are asymmetric. These estimators are compared with the corresponding estimators derived from un-grouped data empirically using Monte-Carlo simulation.
Symmetry Plus Quasi Uniform Association Model And Its Orthogonal Decomposition For Square Contingency Tables, Kouji Yamamoto, Sadao Tomizawa
Symmetry Plus Quasi Uniform Association Model And Its Orthogonal Decomposition For Square Contingency Tables, Kouji Yamamoto, Sadao Tomizawa
Journal of Modern Applied Statistical Methods
A model is proposed having the structure of both symmetry and quasi-uniform association (SQU model) and provides a decomposition of the SQU model. It is also shown with examples that the test statistic for goodness-of-fit of the SQU model is asymptotically equivalent to the sum of those for the decomposed models.
Applying Multiple Imputation With Geostatistical Models To Account For Item Nonresponse In Environmental Data, Breda Munoz, Virginia M. Lesser, Ruben A. Smith
Applying Multiple Imputation With Geostatistical Models To Account For Item Nonresponse In Environmental Data, Breda Munoz, Virginia M. Lesser, Ruben A. Smith
Journal of Modern Applied Statistical Methods
Methods proposed to solve the missing data problem in estimation procedures should consider the type of missing data, the missing data mechanism, the sampling design and the availability of auxiliary variables correlated with the process of interest. This article explores the use of geostatistical models with multiple imputation to deal with missing data in environmental surveys. The method is applied to the analysis of data generated from a probability survey to estimate Coho salmon abundance in streams located in western Oregon watersheds.
Beyond Alpha: Lower Bounds For The Reliability Of Tests, Nol Bendermacher
Beyond Alpha: Lower Bounds For The Reliability Of Tests, Nol Bendermacher
Journal of Modern Applied Statistical Methods
The most common lower bound to the reliability of a test is Cronbach’s alpha. However, several lower bounds exist that are definitely better, that is, higher than alpha. An overview is given as well as an algorithm to find the best: the greatest lower bound.
Shrinkage Estimation In The Inverse Rayleigh Distribution, Gyan Prakash
Shrinkage Estimation In The Inverse Rayleigh Distribution, Gyan Prakash
Journal of Modern Applied Statistical Methods
The properties of the shrinkage test–estimators of the parameter were studied for an inverse Rayleigh model under the asymmetric loss function. Both the single and double–stage shrinkage test–estimators are considered.
Combining Independent Tests Of Conditional Shifted Exponential Distribution, Abedel-Qader S. Al-Masri
Combining Independent Tests Of Conditional Shifted Exponential Distribution, Abedel-Qader S. Al-Masri
Journal of Modern Applied Statistical Methods
The problem of combining n independent tests as n→∞ for testing that variables are uniformly distributed over the interval (0, 1) compared to their having a conditional shifted exponential distribution with probability density function f (xθ ) = e−(x−γθ) , x ≥γθ , θ ∈[a,∞), a ≥ 0 was studied. This was examined for the case where θ1, θ2, … are distributed according to the distribution function (DF) F and when the DF is Gamma (1, 2). Six omnibus methods were compared via the Bahadur efficiency. It is shown that, as γ → 0 and …
A Comparative Study For Bandwidth Selection In Kernel Density Estimation, Omar M. Eidous, Mohammad Abd Alrahem Shafeq Marie, Mohammed H. Baker Al-Haj Ebrahem
A Comparative Study For Bandwidth Selection In Kernel Density Estimation, Omar M. Eidous, Mohammad Abd Alrahem Shafeq Marie, Mohammed H. Baker Al-Haj Ebrahem
Journal of Modern Applied Statistical Methods
Nonparametric kernel density estimation method does not make any assumptions regarding the functional form of curves of interest; hence it allows flexible modeling of data. A crucial problem in kernel density estimation method is how to determine the bandwidth (smoothing) parameter. This article examines the most important bandwidth selection methods, in particular, least squares cross-validation, biased crossvalidation, direct plug-in, solve-the-equation rules and contrast methods. Methods are described and expressions are presented. The main practical contribution is a comparative simulation study that aims to isolate the most promising methods. The performance of each method is evaluated on the basis of the …
Application Of The Truncated Skew Laplace Probability Distribution In Maintenance System, Gokarna R. Aryal, Chris P. Tsokos
Application Of The Truncated Skew Laplace Probability Distribution In Maintenance System, Gokarna R. Aryal, Chris P. Tsokos
Journal of Modern Applied Statistical Methods
A random variable X is said to have the skew-Laplace probability distribution if its pdf is given by f(x) = 2g(x)G(λx), where g (.) and G (.), respectively, denote the pdf and the cdf of the Laplace distribution. When the skew Laplace distribution is truncated on the left at 0 it is called it the truncated skew Laplace (TSL) distribution. This article provides a comparison of TSL distribution with twoparameter gamma model and the hypoexponential model, and an application of the subject model in maintenance system is studied.
Examples Of Computing Power For Zero-Inflated And Overdispersed Count Data, Suzanne R. Doyle
Examples Of Computing Power For Zero-Inflated And Overdispersed Count Data, Suzanne R. Doyle
Journal of Modern Applied Statistical Methods
Examples of zero-inflated Poisson and negative binomial regression models were used to demonstrate conditional power estimation, utilizing the method of an expanded data set derived from probability weights based on assumed regression parameter values. SAS code is provided to calculate power for models with a binary or continuous covariate associated with zero-inflation.
An Inductive Approach To Calculate The Mle For The Double Exponential Distribution, W. J. Hurley
An Inductive Approach To Calculate The Mle For The Double Exponential Distribution, W. J. Hurley
Journal of Modern Applied Statistical Methods
Norton (1984) presented a calculation of the MLE for the parameter of the double exponential distribution based on the calculus. An inductive approach is presented here.
New Effect Size Rules Of Thumb, Shlomo S. Sawilowsky
New Effect Size Rules Of Thumb, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
Recommendations to expand Cohen’s (1988) rules of thumb for interpreting effect sizes are given to include very small, very large, and huge effect sizes. The reasons for the expansion, and implications for designing Monte Carlo studies, are discussed.
Generating And Comparing Aggregate Variables For Use Across Datasets In Multilevel Analysis, James Chowhan, Laura Duncan
Generating And Comparing Aggregate Variables For Use Across Datasets In Multilevel Analysis, James Chowhan, Laura Duncan
Journal of Modern Applied Statistical Methods
This article examines the creation of contextual aggregate variables from one dataset for use with another dataset in multilevel analysis. The process of generating aggregate variables and methods of assessing the validity of the constructed aggregates are presented, together with the difficulties that this approach presents.
Detecting Lag-One Autocorrelation In Interrupted Time Series Experiments With Small Datasets, Clare Riviello, S. Natasha Beretvas
Detecting Lag-One Autocorrelation In Interrupted Time Series Experiments With Small Datasets, Clare Riviello, S. Natasha Beretvas
Journal of Modern Applied Statistical Methods
The power and type I error rates of eight indices for lag-one autocorrelation detection were assessed for interrupted time series experiments (ITSEs) with small numbers of data points. Performance of Huitema and McKean’s (2000) zHM statistic was modified and compared with the zHM, five information criteria and the Durbin-Watson statistic.
Relationship Between Internal Consistency And Goodness Of Fit Maximum Likelihood Factor Analysis With Varimax Rotation, Gibbs Y. Kanyongo, James B. Schreiber
Relationship Between Internal Consistency And Goodness Of Fit Maximum Likelihood Factor Analysis With Varimax Rotation, Gibbs Y. Kanyongo, James B. Schreiber
Journal of Modern Applied Statistical Methods
This study investigates how reliability (internal consistency) affects model-fitting in maximum likelihood exploratory factor analysis (EFA). This was accomplished through an examination of goodness of fit indices between the population and the sample matrices. Monte Carlo simulations were performed to create pseudo-populations with known parameters. Results indicated that the higher the internal consistency the worse the fit. It is postulated that the observations are similar to those from structural equation modeling where a good fit with low correlations can be observed and also the reverse with higher item correlations.
Estimating Model Complexity Of Feed-Forward Neural Networks, Douglas Landsittel
Estimating Model Complexity Of Feed-Forward Neural Networks, Douglas Landsittel
Journal of Modern Applied Statistical Methods
In a previous simulation study, the complexity of neural networks for limited cases of binary and normally-distributed variables based the null distribution of the likelihood ratio statistic and the corresponding chi-square distribution was characterized. This study expands on those results and presents a more general formulation for calculating degrees of freedom.
Level Robust Methods Based On The Least Squares Regression Estimator, Marie Ng, Rand R. Wilcox
Level Robust Methods Based On The Least Squares Regression Estimator, Marie Ng, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Heteroscedastic consistent covariance matrix (HCCM) estimators provide ways for testing hypotheses about regression coefficients under heteroscedasticity. Recent studies have found that methods combining the HCCM-based test statistic with the wild bootstrap consistently perform better than non-bootstrap HCCM-based methods (Davidson & Flachaire, 2008; Flachaire, 2005; Godfrey, 2006). This finding is more closely examined by considering a broader range of situations which were not included in any of the previous studies. In addition, the latest version of HCCM, HC5 (Cribari-Neto, et al., 2007), is evaluated.
Least Error Sample Distribution Function, Vassili F. Pastushenko
Least Error Sample Distribution Function, Vassili F. Pastushenko
Journal of Modern Applied Statistical Methods
Email: The empirical distribution function (ecdf) is unbiased in the usual sense, but shows certain order bias. Pyke suggested discrete ecdf using expectations of order statistics. Piecewise constant optimal ecdf saves 200%/N of sample size N. Results are compared with linear interpolation for U(0, 1), which require up to sixfold shorter samples at the same accuracy.
Confidence Interval Estimation For Intraclass Correlation Coefficient Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara
Confidence Interval Estimation For Intraclass Correlation Coefficient Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara
Journal of Modern Applied Statistical Methods
Confidence intervals (based on the χ2 -distribution and (Z) standard normal distribution) for the intraclass correlation coefficient under unequal family sizes based on a single multinormal sample have been proposed. It has been found that the confidence interval based on the χ2 -distribution consistently and reliably produces better results in terms of shorter average interval length than the confidence interval based on the standard normal distribution: especially for larger sample sizes for various intraclass correlation coefficient values. The coverage probability of the interval based on the χ2 -distribution is competitive with the coverage probability of the interval …
On Some Discrete Distributions And Their Applications With Real Life Data, Shipra Banik, B. M. Golam Kibria
On Some Discrete Distributions And Their Applications With Real Life Data, Shipra Banik, B. M. Golam Kibria
Journal of Modern Applied Statistical Methods
This article reviews some useful discrete models and compares their performance in terms of the high frequency of zeroes, which is observed in many discrete data (e.g., motor crash, earthquake, strike data, etc.). A simulation study is conducted to determine how commonly used discrete models (such as the binomial, Poisson, negative binomial, zero-inflated and zero-truncated models) behave if excess zeroes are present in the data. Results indicate that the negative binomial model and the ZIP model are better able to capture the effect of excess zeroes. Some real-life environmental data are used to illustrate the performance of the proposed models.
Closed Form Confidence Intervals For Small Sample Matched Proportions, James F. Reed Iii
Closed Form Confidence Intervals For Small Sample Matched Proportions, James F. Reed Iii
Journal of Modern Applied Statistical Methods
The behavior of the Wald-z, Wald-c, Quesenberry-Hurst, Wald-m and Agresti-Min methods was investigated for matched proportions confidence intervals. It was concluded that given the widespread use of the repeated-measure design, pretest-posttest design, matched-pairs design, and cross-over design, the textbook Wald-z method should be abandoned in favor of the Agresti-Min alternative.
On Type-Ii Progressively Hybrid Censoring, Debasis Kundu, Avijit Joarder, Hare Krishna
On Type-Ii Progressively Hybrid Censoring, Debasis Kundu, Avijit Joarder, Hare Krishna
Journal of Modern Applied Statistical Methods
The progressive Type-II censoring scheme has become quite popular. A drawback of a progressive censoring scheme is that the length of the experiment can be very large if the items are highly reliable. Recently, Kundu and Joarder (2006) introduced the Type-II progressively hybrid censored scheme and analyzed the data assuming that the lifetimes of the items are exponentially distributed. This article presents the analysis of Type-II progressively hybrid censored data when the lifetime distributions of the items follow Weibull distributions. Maximum likelihood estimators and approximate maximum likelihood estimators are developed for estimating the unknown parameters. Asymptotic confidence intervals based on …
Multiple Search Paths And The General-To-Specific Methodology, Paul Turner
Multiple Search Paths And The General-To-Specific Methodology, Paul Turner
Journal of Modern Applied Statistical Methods
Increased interest in computer automation of the general-to-specific methodology has resulted from research by Hoover and Perez (1999) and Krolzig and Hendry (2001). This article presents simulation results for a multiple search path algorithm that has better properties than those generated by a single search path. The most noticeable improvements occur when the data contain unit roots.
Ordinal Regression Analysis: Fitting The Proportional Odds Model Using Stata, Sas And Spss, Xing Liu
Ordinal Regression Analysis: Fitting The Proportional Odds Model Using Stata, Sas And Spss, Xing Liu
Journal of Modern Applied Statistical Methods
Researchers have a variety of options when choosing statistical software packages that can perform ordinal logistic regression analyses. However, statistical software, such as Stata, SAS, and SPSS, may use different techniques to estimate the parameters. The purpose of this article is to (1) illustrate the use of Stata, SAS and SPSS to fit proportional odds models using educational data; and (2) compare the features and results for fitting the proportional odds model using Stata OLOGIT, SAS PROC LOGISTIC (ascending and descending), and SPSS PLUM. The assumption of the proportional odds was tested, and the results of the fitted models were …
Estimation Of The Standardized Mean Difference For Repeated Measures Designs, Lindsey J. Wolff Smith, S. Natasha Beretvas
Estimation Of The Standardized Mean Difference For Repeated Measures Designs, Lindsey J. Wolff Smith, S. Natasha Beretvas
Journal of Modern Applied Statistical Methods
This simulation study modified the repeated measures mean difference effect size, d=RM , for scenarios with unequal pre- and post-test score variances. Relative parameter and SE bias were calculated for dRM ≠ versus dRM = . Results consistently favored d≠RM over d=RM with worse positive parameter and negative SE bias identified for d=RM for increasingly heterogeneous variance conditions.
Estimating The Parameters Of Rayleigh Cumulative Exposure Model In Simple Step-Stress Testing. Natasha Beretvas Is An, Mohammed Al-Haj Ebrahem, Abedel-Qader Al-Masri
Estimating The Parameters Of Rayleigh Cumulative Exposure Model In Simple Step-Stress Testing. Natasha Beretvas Is An, Mohammed Al-Haj Ebrahem, Abedel-Qader Al-Masri
Journal of Modern Applied Statistical Methods
Assumes the life distribution of a test unit for any stress follows a Rayleigh distribution with scale parameterθ , and that Ln(θ ) is a linear function of the stress level. Maximum likelihood estimators of the parameters under a cumulative exposure model are obtained. The approximate variance estimates obtained from the asymptotic normal distribution of the maximum likelihood estimators are used to construct confidence intervals for the model parameters. A simulation study was conducted to study the performance of the estimators. Simulation results showed that in terms of bias, mean squared error, attainment of the nominal confidence level, symmetry …
Test For The Equality Of The Number Of Signals, Madhusudan Bhandary, Debasis Kundu
Test For The Equality Of The Number Of Signals, Madhusudan Bhandary, Debasis Kundu
Journal of Modern Applied Statistical Methods
A likelihood ratio test for testing the equality of the ranks of two non-negative definite covariance matrices arising in the area of signal processing is derived. The asymptotic distribution of the test statistic follows a Chi-square distribution from the general theory of likelihood ratio test.
Jmasm29: Dominance Analysis Of Independent Data (Fortran), Du Feng, Normal Cliff
Jmasm29: Dominance Analysis Of Independent Data (Fortran), Du Feng, Normal Cliff
Journal of Modern Applied Statistical Methods
A Fortran 77 program is provided for an ordinal dominance analysis of independent two-group comparisons. The program calculates the ordinal statistic, d, and statistical inferences about δ. The source codes and an executable file are available at http://www.depts.ttu.edu/hdfs/feng.php.