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Articles 1621 - 1650 of 1672

Full-Text Articles in Statistics and Probability

Exact Level And Power Of Permutation, Bootstrap, And Asymptotic Tests Of Trend, Christopher D. Corcoran, Cyrus R. Mehta May 2002

Exact Level And Power Of Permutation, Bootstrap, And Asymptotic Tests Of Trend, Christopher D. Corcoran, Cyrus R. Mehta

Journal of Modern Applied Statistical Methods

We develop computational tools that can evaluate the exact size and power of three tests of trend (e.g., permutation, bootstrap and asymptotic) without resorting to large-sample theory or simulations. We then use these tools to compare the operating characteristics of the three tests. It is seen that the bootstrap test is ultra-conservative relative to the other two tests and as a result suffers from a severe deterioration in power. The power of the asymptotic test is uniformly larger than that of the other two tests, but it fails to preserve the Type I error for most of the range of …

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An Adaptive Inference Strategy: The Case Of Auditory Data, Bruno D. Zumbo May 2002

An Adaptive Inference Strategy: The Case Of Auditory Data, Bruno D. Zumbo

Journal of Modern Applied Statistical Methods

By way of an example some of the basic features in the derivation and use of adaptive inferential methods are demonstrated. The focus of this paper is dyadic (coupled) data in auditory and perceptual research. We present: (a) why one should not use the conventional methods, (b) a derivation of an adaptive method, and (c) how the new adaptive method works with the example data. In the concluding remarks we draw attention to the work of Professor George Barnard who provided the adaptive inference strategy in the context of the Behrens-Fisher problem -- testing the equality of means when one …

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Hotelling's T2 Vs. The Rank Transform With Real Likert Data, Michael J. Nanna May 2002

Hotelling's T2 Vs. The Rank Transform With Real Likert Data, Michael J. Nanna

Journal of Modern Applied Statistical Methods

Monte Carlo research has demonstrated that there are many applications of the rank transformation that result in an invalid procedure. Examples include the two dependent samples, the factorial analysis of variance, and the factorial analysis of covariance layouts. However, the rank transformation has been shown to be a valid and powerful test in the two independent samples layout. This study demonstrates that the rank transformation is also a robust and powerful alternative to the Hotellings T2 test when the data are on a Likert scale.

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Six Modifications Of The Aligned Rank Transform Test For Interaction, Kathleen Peterson May 2002

Six Modifications Of The Aligned Rank Transform Test For Interaction, Kathleen Peterson

Journal of Modern Applied Statistical Methods

Testing for interactions in multivariate experiments is an important function. Studies indicate that much data from social studies research is not normally distributed, thus violating that assumption of the AN OVA procedure. The aligned rank transformation test (ART), aligning using the means of columns and rows, has been found, in limited situations, to be robust to Type I error rates and to have greater power than the ANOVA. This study explored a variety of alignments, including the median, Winsorized trimmed means (10%) and (20%), the Huber1.28 M-estimator, and the Harrell-Davis estimator of the median. Results are reported for Type …

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Applying Spatial Randomness To Community Inclusion, Michael Wolf-Branigin May 2002

Applying Spatial Randomness To Community Inclusion, Michael Wolf-Branigin

Journal of Modern Applied Statistical Methods

A spatial analytic methodology incorporating true locations is demonstrated using Monte Carlo simulations as a complement to current psychometric and quality of life indices for measuring community inclusion. Moran's I, a measure of spatial autocorrelation, is used to determine spatial dependencies in housing patterns for multiple variables, including family/friends involvement in future planning, home size, and earned income. Simulations revealed no significant spatial autocorrelation, which is a socially desirable result for housing locations for people with disabilities. Assessing the absence of clustering provides a promising methodology for measuring community inclusion.

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Parametric Analyses In Randomized Clinical Trials, Vance W. Berger, Clifford E. Lunneborg, Michael D. Ernst, Jonathan G. Levine May 2002

Parametric Analyses In Randomized Clinical Trials, Vance W. Berger, Clifford E. Lunneborg, Michael D. Ernst, Jonathan G. Levine

Journal of Modern Applied Statistical Methods

One salient feature of randomized clinical trials is that patients are randomly allocated to treatment groups, but not randomly sampled from any target population. Without random sampling parametric analyses are inexact, yet they are still often used in clinical trials. Given the availability of an exact test, it would still be conceivable to argue convincingly that for technical reasons (upon which we elaborate) a parametric test might be preferable in some situations. Having acknowledged this possibility, we point out that such an argument cannot be convincing without supporting facts concerning the specifics of the problem at hand. Moreover, we have …

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Two Methods To Estimate Homogenous Markov Processes, Ricardo Ocaña-Rilola May 2002

Two Methods To Estimate Homogenous Markov Processes, Ricardo Ocaña-Rilola

Journal of Modern Applied Statistical Methods

Multi-state Markov processes have been introduced recently in Health Sciences in order to study disease history events. This sort of model have some advantages respect to traditional survival analysis, therefore they are an important line of research into stochastic processes applied to Epidemiology. However these types of models increase the complexity of analysis, even for simpler processes, and standard software is limited. In this paper, two methods for fitting homogeneous Markov models are proposed and compared.

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An Error In Statistical Logic In The Application Of Genetic Paternity Testing, Ernest P. Chiodo, Joseph L. Musial, J. Sia Robinson May 2002

An Error In Statistical Logic In The Application Of Genetic Paternity Testing, Ernest P. Chiodo, Joseph L. Musial, J. Sia Robinson

Journal of Modern Applied Statistical Methods

A Bayes probability computer program was written in Fortran to examine issues related to genetic paternity testing. An application was given to demonstrate the effects improper assumptions of prior probability of culpability. The seriousness of such errors include the potential of assigning paternity to wrongly accused men, or wrongly refuting paternity.

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The Trouble With Trivials (P > .05), Shlomo S. Sawilowsky, Jina S. Yoon May 2002

The Trouble With Trivials (P > .05), Shlomo S. Sawilowsky, Jina S. Yoon

Journal of Modern Applied Statistical Methods

Trivials are effect sizes associated with statistically non-significant results. Trivials are like Tribbles in the Star Trek television show. They are cute and loveable. They proliferate without limit. They probably growl at Bayesians. But they are troublesome. This brief report discusses the trouble with trivials.

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Using The T Test With Uncommon Sample Sizes, Shlomo S. Sawilowsky, Barry S. Markman May 2002

Using The T Test With Uncommon Sample Sizes, Shlomo S. Sawilowsky, Barry S. Markman

Journal of Modern Applied Statistical Methods

Monte Carlo techniques were used to determine the effect of using common critical values as an approximation for uncommon sample sizes. Results indicate there can be a significant loss in statistical power. Therefore, even though many instructors now rely on computer statistics packages, the recommendation is made to provide more specificity (i.e., values between 30 and 60) in tables of critical values published in textbooks.

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Quantifying Bimodality Part I: An Easily Implemented Method Using Spss, B. W. Frankland, Bruno D. Zumbo May 2002

Quantifying Bimodality Part I: An Easily Implemented Method Using Spss, B. W. Frankland, Bruno D. Zumbo

Journal of Modern Applied Statistical Methods

Scientists in a variety of fields are faced with the question of whether or not a particular sample of data are best described as unimodal or bimodal. We provide a simple and convenient method for assessing bimodality. The use of the non-linear algorithms in SPSS for modeling complex mixture distributions is demonstrated on a unimodal normal distribution (with 2 free parameters) and on bimodal mixture of two normal distributions (with 5 free parameters).

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Alternatives To SW In The Bracketed Interval Of The Trimmed Mean, Jennifer Bunner, Shlomo S. Sawilowsky May 2002

Alternatives To SW In The Bracketed Interval Of The Trimmed Mean, Jennifer Bunner, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

The aim of this Monte Carlo study is to examine alternatives to estimated variability in building bracketed intervals about the trimmed mean.

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Generation Of Combinations Using Excel, Constantine Stamatopoulos May 2002

Generation Of Combinations Using Excel, Constantine Stamatopoulos

Journal of Modern Applied Statistical Methods

Theoretical development of combinations via enumeration methods are considered. An Excel macro is provided.

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Asymptotic And Exact Tests In 2 X C Ordered Categorical Contingency Tables With Statxact 2.0 - 4.0, Margaret Posch May 2002

Asymptotic And Exact Tests In 2 X C Ordered Categorical Contingency Tables With Statxact 2.0 - 4.0, Margaret Posch

Journal of Modern Applied Statistical Methods

The purpose of this study was to compare the statistical power of a variety of exact tests in the 2 x C ordered categorical contingency table using StatXact software. The Wilcoxon Rank Sum, Expected Nonnal Scores, Savage Scores (or its Log Rank equivalent), and Permutation tests were studied. Results indicated that the procedures were nearly the same in terms of comparative statistical power.

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Jmasm1: Rangen 2.0 (Fortran 90/95), Gail F. Fahoome May 2002

Jmasm1: Rangen 2.0 (Fortran 90/95), Gail F. Fahoome

Journal of Modern Applied Statistical Methods

Rangen 2.0 is Fortran 90 module of subroutines used to generate uniform and nonuniform pseudo-random deviates. It includes uni1, an uniform pseudo-random number generator, and non-uniform generators based on unil. The subroutines in Rangen 2.0 were written using Essential Lahey Fortran 90, a proper subset of Fortran 90. It includes both source code for the subroutines and a short description of each subroutine, its purpose, and the arguments including data type and usage.

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An Unconditional Exact Test For Small Samples Matched Binary Pairs, Robert A. Malkin May 2002

An Unconditional Exact Test For Small Samples Matched Binary Pairs, Robert A. Malkin

Journal of Modern Applied Statistical Methods

When investigators have N pairs of binary data, a common test for an increased rate of response is McNemar's test. However, McNemar's is an approximate, conditional test. An exact, unconditional test exists, but requires restrictive assumptions. Critical values and power tables are presented for an exact, unconditional test free of these assumptions.

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Inference For Proportional Mean Residual Life Model In The Presence Of Censoring, Ying Q. Chen, Nicholas P. Jewell May 2002

Inference For Proportional Mean Residual Life Model In The Presence Of Censoring, Ying Q. Chen, Nicholas P. Jewell

U.C. Berkeley Division of Biostatistics Working Paper Series

As a function of time t, mean residual life is defined as remaining life expectancy of a subject given its survival to t. It plays an important role in many research areas to characterise stochastic behavior of survival over time. Similar to the Cox proportional hazard model, the proportional mean residual life model were proposed in statistical literature to study association between the mean residual life and individual subject's explanatory covariates. In this article, we will study this model and develop appropriate inference procedures in presence of censoring. Numerical studies including simulation and real data analysis are presented as well.

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A Measure Of Relative Efficiency For Location Of A Single Sample, Shlomo S. Sawilowsky May 2002

A Measure Of Relative Efficiency For Location Of A Single Sample, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

The question of how much to trim or which weighting constant to use are practical considerations in applying robust methods such as trimmed means (L-estimators) and Huber statistics (M-estimators). An index oflocation relative efficiency (LRE), which is a ratio of the narrowness of resulting confidence intervals, was applied to various trimmed means and Huber M-estimators calculated on seven representative data sets from applied education and psychology research. On the basis of LREs, lightly trimmed means were found to be more efficient than heavily trimmed means, but Huber M-estimators systematically produced narrower confidence intervals. The weighting constant of ψ = 1.28 …

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The Q-Sort Method: Assessing Reliability And Construct Validity Of Questionnaire Items At A Pre-Testing Stage, Abraham Y. Nahm, S. Subba Rao, Luis E. Solis-Galvan, T. S. Ragu-Nathan May 2002

The Q-Sort Method: Assessing Reliability And Construct Validity Of Questionnaire Items At A Pre-Testing Stage, Abraham Y. Nahm, S. Subba Rao, Luis E. Solis-Galvan, T. S. Ragu-Nathan

Journal of Modern Applied Statistical Methods

This paper describes the Q-sort, which is a method of assessing reliability and construct validity of questionnaire items at a pre-testing stage. The method uses Cohen's Kappa and Moore and Benbasat's Hit Ratio in assessing the questionnaire.

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Two-Sided Equivalence Testing Of The Difference Between Two Means, R. Clifford Blair, Stephen R. Cole May 2002

Two-Sided Equivalence Testing Of The Difference Between Two Means, R. Clifford Blair, Stephen R. Cole

Journal of Modern Applied Statistical Methods

Studies designed to examine the equivalence of treatments are increasingly common in social and biomedical research. Herein, we outline the rationale and some nuances underlying equivalence testing of the difference between two means. Specifically, we note the odd relation between tests of hypothesis and confidence intervals in the equivalence setting.

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Modeling Strategies In Logistic Regression With Sas, Spss, Systat, Bmdp, Minitab, And Stata, Chao-Ying Joanne Peng, Tak-Shing Harry So May 2002

Modeling Strategies In Logistic Regression With Sas, Spss, Systat, Bmdp, Minitab, And Stata, Chao-Ying Joanne Peng, Tak-Shing Harry So

Journal of Modern Applied Statistical Methods

This paper addresses modeling strategies in logistic regression within the context of a real-world data set. Six commercially available statistical packages were evaluated in how they addressed modeling issues and in the accuracy of their regression results. Recommendations are offered for data analysts in terms of each package's strengths and weaknesses.

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Jmasm3: A Method For Simulating Systems Of Correlated Binary Data, Todd C. Headrick May 2002

Jmasm3: A Method For Simulating Systems Of Correlated Binary Data, Todd C. Headrick

Journal of Modern Applied Statistical Methods

An efficient algorithm is derived for generating systems of correlated binary data. The procedure allows for the specification of all pairwise correlations within each system. Intercorrelations between systems can be specified qualitatively. The procedure requires the simultaneous solution of a system of equations for obtaining the threshold probabilities to generate each system of binary data. A numerical example is provided to demonstrate that the procedure generates correlated binary variables that yield correlations in close agreement with the specified population correlations.

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Rank-Based Procedures For Mixed Paired And Two-Sample Designs, Suzanne R. Dubnicka, R. Clifford Blair, Thomas P. Hettmansperger May 2002

Rank-Based Procedures For Mixed Paired And Two-Sample Designs, Suzanne R. Dubnicka, R. Clifford Blair, Thomas P. Hettmansperger

Journal of Modern Applied Statistical Methods

This paper presents a rank-based procedure for parameter estimation and hypothesis testing when the data are a mixture of paired observations and independent samples. Such a situation may arise when comparing two treatments. When both treatments can be applied to a subject, paired data will be generated. When it is not possible to apply both treatments, the subject will be randomly assigned to one of the treatment groups. Our rank-based procedure allows us to use the data from the paired sample and the independent samples to make inferences about the difference in the mean responses. The rank-based procedure uses both …

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A Method To Identify Significant Clusters In Gene Expression Data, Katherine S. Pollard, Mark J. Van Der Laan Apr 2002

A Method To Identify Significant Clusters In Gene Expression Data, Katherine S. Pollard, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Clustering algorithms have been widely applied to gene expression data. For both hierarchical and partitioning clustering algorithms, selecting the number of significant clusters is an important problem and many methods have been proposed. Existing methods for selecting the number of clusters tend to find only the global patterns in the data (e.g.: the over and under expressed genes). We have noted the need for a better method in the gene expression context, where small, biologically meaningful clusters can be difficult to identify. In this paper, we define a new criteria, Mean Split Silhouette (MSS), which is a measure of cluster …

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A New Partitioning Around Medoids Algorithm, Mark J. Van Der Laan, Katherine S. Pollard, Jennifer Bryan Feb 2002

A New Partitioning Around Medoids Algorithm, Mark J. Van Der Laan, Katherine S. Pollard, Jennifer Bryan

U.C. Berkeley Division of Biostatistics Working Paper Series

Kaufman & Rousseeuw (1990) proposed a clustering algorithm Partitioning Around Medoids (PAM) which maps a distance matrix into a specified number of clusters. A particularly nice property is that PAM allows clustering with respect to any specified distance metric. In addition, the medoids are robust representations of the cluster centers, which is particularly important in the common context that many elements do not belong well to any cluster. Based on our experience in clustering gene expression data, we have noticed that PAM does have problems recognizing relatively small clusters in situations where good partitions around medoids clearly exist. In this …

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Optimal Policies For Investment With Time-Varying Return Distributions, Douglas Steigerwald, Doncho Donchev, Svetlozar Rachev Dec 2001

Optimal Policies For Investment With Time-Varying Return Distributions, Douglas Steigerwald, Doncho Donchev, Svetlozar Rachev

Douglas G. Steigerwald

We develop a model in which investors must learn the distribution of asset returns over time. The process of learning is made more difficult by the fact that the distributions are not constant through time. We consider risk-neutral investors who have quadratic utility and are selecting between two risky assets. We determine the time at which it is optimal to update the distribution estimate and, hence, alter portfolio weights. Our results deliver an optimal policy for asset allocation, that is, the sequence of time intervals at which it is optimal to switch between assets, based on stochastic optimal control theory. …

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Marginal Regression Of Gaps Between Recurrent Events, Yijian Huang, Ying Qing Chen Nov 2001

Marginal Regression Of Gaps Between Recurrent Events, Yijian Huang, Ying Qing Chen

U.C. Berkeley Division of Biostatistics Working Paper Series

Recurrent event data typically exhibit the phenomenon of intra-individual correlation, owing to not only observed covariates but also random effects. In many applications, the population can be reasonably postulated as a heterogeneous mixture of individual renewal processes, and the inference of interest is the effect of individual-level covariates. In this article, we suggest and investigate a marginal proportional hazards model for gaps between recurrent events. A connection is established between observed gap times and clustered survival data, however, with informative cluster size. We then derive a novel and general inference procedure for the latter, based on a functional formulation of …

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Maximum Likelihood Estimation Of Ordered Multinomial Parameters, Nicholas P. Jewell, John D. Kalbfleisch Oct 2001

Maximum Likelihood Estimation Of Ordered Multinomial Parameters, Nicholas P. Jewell, John D. Kalbfleisch

U.C. Berkeley Division of Biostatistics Working Paper Series

The pool-adjacent violator-algorithm (Ayer, et al., 1955) has long been known to give the maximum likelihood estimator of a series of ordered binomial parameters, based on an independent observation from each distribution (see Barlow et al., 1972). This result has immediate application to estimation of a survival distribution based on current survival status at a set of monitoring times. This paper considers an extended problem of maximum likelihood estimation of a series of ‘ordered’ multinomial parameters. By making use of variants of the pool adjacent violator algorithm, we obtain a simple algorithm to compute the maximum likelihood estimator and demonstrate …

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Statistical Inference For Simultaneous Clustering Of Gene Expression Data, Katherine S. Pollard, Mark J. Van Der Laan Jul 2001

Statistical Inference For Simultaneous Clustering Of Gene Expression Data, Katherine S. Pollard, Mark J. Van Der Laan

U.C. Berkeley Division of Biostatistics Working Paper Series

Current methods for analysis of gene expression data are mostly based on clustering and classification of either genes or samples. We offer support for the idea that more complex patterns can be identified in the data if genes and samples are considered simultaneously. We formalize the approach and propose a statistical framework for two-way clustering. A simultaneous clustering parameter is defined as a function of the true data generating distribution, and an estimate is obtained by applying this function to the empirical distribution. We illustrate that a wide range of clustering procedures, including generalized hierarchical methods, can be defined as …

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Incentives To Settle Under Joint And Several Liability: An Empirical Analysis Of Superfund Litigation, Howard F. Chang, Hilary Sigman Jan 2000

Incentives To Settle Under Joint And Several Liability: An Empirical Analysis Of Superfund Litigation, Howard F. Chang, Hilary Sigman

All Faculty Scholarship

Congress may soon restrict joint and several liability for cleanup of contaminated sites under Superfund. We explore whether this change would discourage settlements and is therefore likely to increase the program 's already high litigation costs per site. Recent theoretical research by Kornhauser and Revesz finds that joint and several liability may either encourage or discourage settlement, depending on the correlation of outcomes at trial across defendants. We extend their two-defendant model to a richer framework with N defendants. This extension allows us to test the theoretical model empirically using data on Superfund litigation. We find that joint and several …

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