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Articles 61 - 78 of 78
Full-Text Articles in Statistical Theory
Population Mean Estimation With Sub Sampling The Non-Respondents Using Two Phase Sampling, Sunil Kumar, M Viswanathaiah
Population Mean Estimation With Sub Sampling The Non-Respondents Using Two Phase Sampling, Sunil Kumar, M Viswanathaiah
Journal of Modern Applied Statistical Methods
The problem of non-response in double (or two phase) sampling is dealt with combined ratio, product and regression estimators. Expressions of bias and MSE for these estimators are obtained. Comparisons of a proposed strategy with a usual unbiased estimator and other estimators are carried out and results obtained are illustrated numerically using an empirical sample.
Estimation And Testing In Type-Ii Generalized Half Logistic Distribution, R R. L. Kantam, V Ramakrishna, M S. Ravikumar
Estimation And Testing In Type-Ii Generalized Half Logistic Distribution, R R. L. Kantam, V Ramakrishna, M S. Ravikumar
Journal of Modern Applied Statistical Methods
A generalization of the Half Logistic Distribution is developed through exponentiation of its survival function and named the Type II Generalized Half Logistic Distribution (GHLD). The distributional characteristics are presented and estimation of its parameters using maximum likelihood and modified maximum likelihood methods is studied with comparisons. Discrimination between Type II GHLD and exponential distribution in pairs is conducted via likelihood ratio criterion.
A Compound Of Geeta Distribution With Generalized Beta Distribution, Adil Rashid, T R. Jan
A Compound Of Geeta Distribution With Generalized Beta Distribution, Adil Rashid, T R. Jan
Journal of Modern Applied Statistical Methods
A compound of Geeta distribution with Generalized Beta distribution (GBD) is obtained and the compound is specialized for different values of β. The first order factorial moments of some special compound distributions are also obtained. A chronological overview of recent developments in the compounding of distributions is provided in the introduction.
Hierarchical Clustering With Simple Matching And Joint Entropy Dissimilarity Measure, A Mete ÇilingtüRk, ÖZlem ErgüT
Hierarchical Clustering With Simple Matching And Joint Entropy Dissimilarity Measure, A Mete ÇilingtüRk, ÖZlem ErgüT
Journal of Modern Applied Statistical Methods
Conventional clustering algorithms are restricted for use with data containing ratio or interval scale variables; hence, distances are used. As social studies require merely categorical data, the literature is enriched with more complicated clustering techniques and algorithms of categorical data. These techniques are based on similarity or dissimilarity matrices. The algorithms are using density based or pattern based approaches. A probabilistic nature to similarity structure is proposed. The entropy dissimilarity measure has comparable results with simple matching dissimilarity at hierarchical clustering. It overcomes dimension increase through binarization of the categorical data. This approach is also functional with the clustering methods, …
An Exploratory Graphical Method For Identifying Associations In R X C Contingency Tables, Martin L. Lesser, Meredith B. Akerman
An Exploratory Graphical Method For Identifying Associations In R X C Contingency Tables, Martin L. Lesser, Meredith B. Akerman
Journal of Modern Applied Statistical Methods
On finding a significant association between rows and columns of an r x c contingency table, the next step is to study the nature of the association in more detail. The use of a scree plot to visualize the largest contributions to Χ2 among all cells in the table in order to determine the nature of the association in more detail is proposed.
Separate Ratio-Type Estimators Of Population Mean In Stratified Random Sampling, Rajesh Tailor, Hilal A. Lone
Separate Ratio-Type Estimators Of Population Mean In Stratified Random Sampling, Rajesh Tailor, Hilal A. Lone
Journal of Modern Applied Statistical Methods
Separate ratio-type estimators for population mean with their properties are considered. Some separate ratio-type estimators for population mean using known parameters of auxiliary variate are proposed. The bias and mean squared error of the proposed estimators are obtained up to the first degree of approximation. It is shown that the proposed estimators are more efficient than unbiased estimators in stratified random sampling and usual separate ratio estimators under certain obtained conditions. To judge the merits of the proposed estimators, an empirical study was conducted.
Evaluation Of Area Under The Constant Shape Bi-Weibull Roc Curve, Sudesh Pundir, R Amala
Evaluation Of Area Under The Constant Shape Bi-Weibull Roc Curve, Sudesh Pundir, R Amala
Journal of Modern Applied Statistical Methods
The Receiver Operating Characteristic (ROC) curve generated based on assuming a constant shape Bi-Weibull distribution is studied. In the context of ROC curve analysis, it is assumed that biomarker values from controls and cases follow some specific distribution and the accuracy is evaluated by using the ROC model developed from that specified distribution. This article assumes that the biomarker values from the two groups follow Weibull distributions with equal shape parameter and different scale parameters. The ROC model, area under the ROC curve (AUC), asymptotic and bootstrap confidence intervals for the AUC are derived. Theoretical results are validated by simulation …
Investigating The Feasibility Of Using Mplus In The Estimation Of Growth Mixture Models, Ming Li, Jeffrey R. Harring, George B. Macready
Investigating The Feasibility Of Using Mplus In The Estimation Of Growth Mixture Models, Ming Li, Jeffrey R. Harring, George B. Macready
Journal of Modern Applied Statistical Methods
Hipp and Bauer (2006) investigated the issues of singularities and local maximum solutions within growth mixture models (GMMs) and made recommendations regarding the use of multiple starting values. Building on their work, this simulation study investigates the feasibility of estimating GMMs within Mplus as measured by convergence to proper, but local solutions.
A Reduced Bias Method Of Estimating Variance Components In Generalized Linear Mixed Models, Elizabeth A. Claassen
A Reduced Bias Method Of Estimating Variance Components In Generalized Linear Mixed Models, Elizabeth A. Claassen
Department of Statistics: Dissertations, Theses, and Student Research
In small samples it is well known that the standard methods for estimating variance components in a generalized linear mixed model (GLMM), pseudo-likelihood and maximum likelihood, yield estimates that are biased downward. An important consequence of this is that inferences on fixed effects will have inflated Type I error rates because their precision is overstated. We introduce a new method for estimating parameters in GLMMs that applies a Firth bias adjustment to the maximum likelihood-based GLMM estimating algorithm. We apply this technique to one- and two-treatment logistic regression models with a single random effect. We show simulation results that demonstrate …
Comparison Of Different Methods For Estimating Log-Normal Means, Qi Tang
Comparison Of Different Methods For Estimating Log-Normal Means, Qi Tang
Electronic Theses and Dissertations
The log-normal distribution is a popular model in many areas, especially in biostatistics and survival analysis where the data tend to be right skewed. In our research, a total of ten different estimators of log-normal means are compared theoretically. Simulations are done using different values of parameters and sample size. As a result of comparison, ``A degree of freedom adjusted" maximum likelihood estimator and Bayesian estimator under quadratic loss are the best when using the mean square error (MSE) as a criterion. The ten estimators are applied to a real dataset, an environmental study from Naval Construction Battalion Center (NCBC), …
Nonparametric Identifiability Of Finite Mixture Models With Covariates For Estimating Error Rate Without A Gold Standard, Zheyu Wang, Xiao-Hua Zhou
Nonparametric Identifiability Of Finite Mixture Models With Covariates For Estimating Error Rate Without A Gold Standard, Zheyu Wang, Xiao-Hua Zhou
UW Biostatistics Working Paper Series
Finite mixture models provide a flexible framework to study unobserved entities and have arisen in many statistical applications. The flexibility of these models in adapting various complicated structures makes it crucial to establish model identifiability when applying them in practice to ensure study validity and interpretation. However, researches to establish the identifiability of finite mixture model are limited and are usually restricted to a few specific model configurations. Conditions for model identifiability in the general case have not been established. In this paper, we provide conditions for both local identifiability and global identifiability of a finite mixture model. The former …
Asymmetric Empirical Similarity, Joshua C. Teitelbaum
Asymmetric Empirical Similarity, Joshua C. Teitelbaum
Georgetown Law Faculty Publications and Other Works
The paper offers a formal model of analogical legal reasoning and takes the model to data. Under the model, the outcome of a new case is a weighted average of the outcomes of prior cases. The weights capture precedential influence and depend on fact similarity (distance in fact space) and precedential authority (position in the judicial hierarchy). The empirical analysis suggests that the model is a plausible model for the time series of U.S. maritime salvage cases. Moreover, the results evince that prior cases decided by inferior courts have less influence than prior cases decided by superior courts.
Adaptive Pair-Matching In The Search Trial And Estimation Of The Intervention Effect, Laura Balzer, Maya L. Petersen, Mark J. Van Der Laan
Adaptive Pair-Matching In The Search Trial And Estimation Of The Intervention Effect, Laura Balzer, Maya L. Petersen, Mark J. Van Der Laan
U.C. Berkeley Division of Biostatistics Working Paper Series
In randomized trials, pair-matching is an intuitive design strategy to protect study validity and to potentially increase study power. In a common design, candidate units are identified, and their baseline characteristics used to create the best n/2 matched pairs. Within the resulting pairs, the intervention is randomized, and the outcomes measured at the end of follow-up. We consider this design to be adaptive, because the construction of the matched pairs depends on the baseline covariates of all candidate units. As consequence, the observed data cannot be considered as n/2 independent, identically distributed (i.i.d.) pairs of units, as current practice assumes. …
Adaptive Randomized Trial Designs That Cannot Be Dominated By Any Standard Design At The Same Total Sample Size, Michael Rosenblum
Adaptive Randomized Trial Designs That Cannot Be Dominated By Any Standard Design At The Same Total Sample Size, Michael Rosenblum
Johns Hopkins University, Dept. of Biostatistics Working Papers
Prior work has shown that certain types of adaptive designs can always be dominated by a suitably chosen, standard, group sequential design. This applies to adaptive designs with rules for modifying the total sample size. A natural question is whether analogous results hold for other types of adaptive designs. We focus on adaptive enrichment designs, which involve preplanned rules for modifying enrollment criteria based on accrued data in a randomized trial. Such designs often involve multiple hypotheses, e.g., one for the total population and one for a predefined subpopulation, such as those with high disease severity at baseline. We fix …
Meta-Analysis Of Social-Personality Psychological Research, Blair T. Johnson, Alice H. Eagly
Meta-Analysis Of Social-Personality Psychological Research, Blair T. Johnson, Alice H. Eagly
CHIP Documents
This publication provides a contemporary treatment of the subject of meta-analysis in relation to social-personality psychology. Meta-analysis literally refers to the statistical pooling of the results of independent studies on a given subject, although in practice it refers as well to other steps of research synthesis, including defining the question under investigation, gathering all available research reports, coding of information about the studies and their effects, and interpretation/dissemination of results. Discussed as well are the hallmarks of high-quality meta-analyses.
Comparing K Population Means With No Assumption About The Variances, Tony Yaacoub
Comparing K Population Means With No Assumption About The Variances, Tony Yaacoub
College of Graduate Studies: Theses & Dissertations
In the analysis of most statistically designed experiments, it is common to assume equal variances along with the assumptions that the sample measurements are independent and normally distributed. Under these three assumptions, a likelihood ratio test is used to test for the difference in population means. Typically, the assumption of independence can be justified based on the sampling method used by the researcher. The likelihood ratio test is robust to the assumption of normality. However, the equality of variances is often difficult to justify. It has been found that the assumption of equal variances cannot be made even after transforming …
Generalized Weibull And Inverse Weibull Distributions With Applications, Valeriia Sherina
Generalized Weibull And Inverse Weibull Distributions With Applications, Valeriia Sherina
College of Graduate Studies: Theses & Dissertations
In this thesis, new classes of Weibull and inverse Weibull distributions including the generalized new modified Weibull (GNMW), gamma-generalized inverse Weibull (GGIW), the weighted proportional inverse Weibull (WPIW) and inverse new modified Weibull (INMW) distributions are introduced. The GNMW contains several sub-models including the new modified Weibull (NMW), generalized modified Weibull (GMW), modified Weibull (MW), Weibull (W) and exponential (E) distributions, just to mention a few. The class of WPIW distributions contains several models such as: length-biased, hazard and reverse hazard proportional inverse Weibull, proportional inverse Weibull, inverse Weibull, inverse exponential, inverse Rayleigh, and Frechet distributions as special cases. Included …
A General Procedure Of Estimating Population Mean Using Information On Auxiliary Attribute, Sachin Malik, Rajesh Singh, Florentin Smarandache
A General Procedure Of Estimating Population Mean Using Information On Auxiliary Attribute, Sachin Malik, Rajesh Singh, Florentin Smarandache
Branch Mathematics and Statistics Faculty and Staff Publications
This paper deals with the problem of estimating the finite population mean when some information on auxiliary attribute is available. It is shown that the proposed estimator is more efficient than the usual mean estimator and other existing estimators. The results have been illustrated numerically by taking empirical population considered in the literature.