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Applied Statistics

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Articles 751 - 780 of 1191

Full-Text Articles in Statistical Theory

Semi-Parametric Of Sample Selection Model Using Fuzzy Concepts, L. Muhamad Safiih, A. A. Kamil, M. T. Abu Osman Nov 2009

Semi-Parametric Of Sample Selection Model Using Fuzzy Concepts, L. Muhamad Safiih, A. A. Kamil, M. T. Abu Osman

Journal of Modern Applied Statistical Methods

The sample selection model has been studied in the context of semi-parametric methods. With the deficiencies of the parametric model, such as inconsistent estimators, semi-parametric estimation methods provide better alternatives. This article focuses on the context of fuzzy concepts as a hybrid to the semiparametric sample selection model. The better approach when confronted with uncertainty and ambiguity is to use the tools provided by the theory of fuzzy sets, which are appropriate for modeling vague concepts. A fuzzy membership function for solving uncertainty data of a semi-parametric sample selection model is introduced as a solution to the problem.

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Performance Ratings Of An Autocovariance Base Estimator (Abe) In The Estimation Of Garch Model Parameters When The Normality Assumption Is Invalid, Daniel Eni Nov 2009

Performance Ratings Of An Autocovariance Base Estimator (Abe) In The Estimation Of Garch Model Parameters When The Normality Assumption Is Invalid, Daniel Eni

Journal of Modern Applied Statistical Methods

The performance of an autocovariance base estimator (ABE) for GARCH models against that of the maximum likelihood estimator (MLE) if a distribution assumption is wrongly specified as normal was studied. This was accomplished by simulating time series data that fits a GARCH model using the Log normal and t-distributions with degrees of freedom of 5, 10 and 15. The simulated time series was considered as the true probability distribution, but normality was assumed in the process of parameter estimations. To track consistency, sample sizes of 200, 500, 1,000 and 1,200 were employed. The two methods were then used to analyze …

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A Linear B-Spline Threshold Dose-Response Model With Dose-Specific Response Variation Applied To Developmental Toxicity Studies, Chin-Shang Li, Daniel L. Hunt Nov 2009

A Linear B-Spline Threshold Dose-Response Model With Dose-Specific Response Variation Applied To Developmental Toxicity Studies, Chin-Shang Li, Daniel L. Hunt

Journal of Modern Applied Statistical Methods

A linear B-spline function was modified to model dose-specific response variation in developmental toxicity studies. In this new model, response variation is assumed to differ across dose groups. The model was applied to a developmental toxicity study and proved to be significant over the previous model of singular response variation.

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Jmasm28: Gibbs Sampling For 2pno Multi-Unidimensional Item Response Theory Models (Fortran), Yanyan Sheng, Todd C. Headrick Nov 2009

Jmasm28: Gibbs Sampling For 2pno Multi-Unidimensional Item Response Theory Models (Fortran), Yanyan Sheng, Todd C. Headrick

Journal of Modern Applied Statistical Methods

A Fortran 77 subroutine is provided for implementing the Gibbs sampling procedure to a multiunidimensional IRT model for binary item response data with the choice of uniform and normal prior distributions for item parameters. In addition to posterior estimates of the model parameters and their Monte Carlo standard errors, the algorithm also estimates the correlations between distinct latent traits. The subroutine requires the user to have access to the IMSL library. The source code is available at http://www.siuc.edu/~epse1/sheng/Fortran/MUIRT/GSMU2.FOR. An executable file is also provided for download at http://www.siuc.edu/~epse1/sheng/Fortran/MUIRT/EXAMPLE.zip to demonstrate the implementation of the algorithm on simulated data.

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Markov Modeling Of Breast Cancer, Chunling Cong, Chris P. Tsokos Nov 2009

Markov Modeling Of Breast Cancer, Chunling Cong, Chris P. Tsokos

Journal of Modern Applied Statistical Methods

Previous work with respect to the treatments and relapse time for breast cancer patients is extended by applying a Markov chain to model three different types of breast cancer patients: alive without ever having relapse, alive with relapse, and deceased. It is shown that combined treatment of tamoxifen and radiation is more effective than single treatment of tamoxifen in preventing the recurrence of breast cancer. However, if the patient has already relapsed from breast cancer, single treatment of tamoxifen would be more appropriate with respect to survival time after relapse. Transition probabilities between three stages during different time periods, 2-year, …

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Impact Of Rank-Based Normalizing Transformations On The Accuracy Of Test Scores, Shira R. Soloman, Shlomo S. Sawilowsky Nov 2009

Impact Of Rank-Based Normalizing Transformations On The Accuracy Of Test Scores, Shira R. Soloman, Shlomo S. Sawilowsky

Journal of Modern Applied Statistical Methods

The purpose of this article is to provide an empirical comparison of rank-based normalization methods for standardized test scores. A series of Monte Carlo simulations were performed to compare the Blom, Tukey, Van der Waerden and Rankit approximations in terms of achieving the T score’s specified mean and standard deviation and unit normal skewness and kurtosis. All four normalization methods were accurate on the mean but were variably inaccurate on the standard deviation. Overall, deviation from the target moments was pronounced for the even moments but slight for the odd moments. Rankit emerged as the most accurate method among all …

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Bayesian Analysis Of Evidence From Studies Of Warfarin V Aspirin For Symptomatic Intracranial Stenosis, Vicki Hertzberg, Barney Stern, Karen Johnston Nov 2009

Bayesian Analysis Of Evidence From Studies Of Warfarin V Aspirin For Symptomatic Intracranial Stenosis, Vicki Hertzberg, Barney Stern, Karen Johnston

Journal of Modern Applied Statistical Methods

Bayesian analyses of symptomatic intracranial stenosis studies were conducted to compare the benefits of long-term therapy with warfarin to aspirin. The synthesis of evidence of effect from previous nonrandomized studies in monitoring a randomized clinical trial was of particular interest. Sequential Bayesian learning analysis was conducted and Bayesian hierarchical random effects models were used to incorporate variability between studies. The posterior point estimates for the risk rate ratio (RRR) were similar between analyses, although the interval estimates resulting from the hierarchical analyses are larger than the corresponding Bayesian learning analyses. This demonstrated the difference between these methods in accounting for …

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A Maximum Test For The Analysis Of Ordered Categorical Data, Markus Neuhäeuser Nov 2009

A Maximum Test For The Analysis Of Ordered Categorical Data, Markus Neuhäeuser

Journal of Modern Applied Statistical Methods

Different scoring schemes are possible when performing exact tests using scores on ordered categorical data. The standard scheme is based on integer scores, but non-integer scores were proposed to increase power (Ivanova & Berger, 2001). However, different non-integer scores exist and the question arises as to which of the non-integer schemes should be chosen. To solve this problem, a maximum test is proposed. To be precise, the maximum of the competing statistics is used as the new test statistic, rather than arbitrarily choosing one single test statistic.

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Intermediate R Values For Use In The Fleishman Power Method, Julie M. Smith Nov 2009

Intermediate R Values For Use In The Fleishman Power Method, Julie M. Smith

Journal of Modern Applied Statistical Methods

Several intermediate r values are calculated at three different correlations for use in the Fleishman Power Method for generating correlated data from normal and non-normal populations.

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Sequence Comparison And Stochastic Model Based On Multi-Order Markov Models, Xiang Fang Nov 2009

Sequence Comparison And Stochastic Model Based On Multi-Order Markov Models, Xiang Fang

Department of Statistics: Dissertations, Theses, and Student Research

This dissertation presents two statistical methodologies developed on multi-order Markov models. First, we introduce an alignment-free sequence comparison method, which represents a sequence using a multi-order transition matrix (MTM). The MTM contains information of multi-order dependencies and provides a comprehensive representation of the heterogeneous composition within a sequence. Based on the MTM, a distance measure is developed for pair-wise comparison of sequences. The new method is compared with the traditional maximum likelihood (ML) method, the complete composition vector (CCV) method and the improved version of the complete composition vector (ICCV) method using simulated sequences. We further illustrate the application of …

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On The Blue Of The Population Mean For Location And Scale Parameters Of Distributions Based On Moving Extreme Ranked Set Sampling, Walid A. Abu-Dayyeh, Lana Al-Rousan May 2009

On The Blue Of The Population Mean For Location And Scale Parameters Of Distributions Based On Moving Extreme Ranked Set Sampling, Walid A. Abu-Dayyeh, Lana Al-Rousan

Journal of Modern Applied Statistical Methods

The best linear unbiased estimator (BLUE) for the population mean under moving extreme ranked set sampling (MERSS) is derived for general location and scale parameters of distributions which generalizes Al-Odat and Al-Saleh (2001). It is compared with the sample mean of simple random sampling (SRS). The efficient sample size under the MERSS for which the BLUE estimator dominates the usual sample mean under SRS for estimating the population mean is also computed for several distributions.

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Robustness To Non-Independence And Power Of The I Test For Trend In Construct Validity, John L. Cuzzocrea, Shlomo Sawilowsky May 2009

Robustness To Non-Independence And Power Of The I Test For Trend In Construct Validity, John L. Cuzzocrea, Shlomo Sawilowsky

Journal of Modern Applied Statistical Methods

The Multitrait-Multimethod Matrix is used to evaluate construct validity; Sawilowsky (2002) created the I test to analyze the matrix. This article examined the robustness and power of the Sawilowsky I test. Ad hoc critical values were determined to improve the statistical power of the technique for analyzing the Multitrait-Multimethod Matrix.

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Least Absolute Value Vs. Least Squares Estimation And Inference Procedures In Regression Models With Asymmetric Error Distributions, Terry E. Dielman May 2009

Least Absolute Value Vs. Least Squares Estimation And Inference Procedures In Regression Models With Asymmetric Error Distributions, Terry E. Dielman

Journal of Modern Applied Statistical Methods

A Monte Carlo simulation is used to compare estimation and inference procedures in least absolute value (LAV) and least squares (LS) regression models with asymmetric error distributions. Mean square errors (MSE) of coefficient estimates are used to assess the relative efficiency of the estimators. Hypothesis tests for coefficients are compared on the basis of empirical level of significance and power.

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Covariate-Adjusted Constrained Bayes Predictions Of Random Intercepts And Slopes. Sujit Ghosh Is A, Robert H. Lyles, Reneé H. Moore, Amita K. Manatunga, Kirk A. Easley May 2009

Covariate-Adjusted Constrained Bayes Predictions Of Random Intercepts And Slopes. Sujit Ghosh Is A, Robert H. Lyles, Reneé H. Moore, Amita K. Manatunga, Kirk A. Easley

Journal of Modern Applied Statistical Methods

No abstract provided.

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On The Expected Values Of Distribution Of The Sample Range Of Order Statistics From The Geometric Distribution, Sinan Calik, Cemil Colak, Ayse Turan May 2009

On The Expected Values Of Distribution Of The Sample Range Of Order Statistics From The Geometric Distribution, Sinan Calik, Cemil Colak, Ayse Turan

Journal of Modern Applied Statistical Methods

The expected values of the distribution of the sample range of order statistics from the geometric distribution are presented. For n up to 10, algebraic expressions for the expected values are obtained. Using the algebraic expressions, expected values based on the p and n values can be easily computed.

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Approximations To Power When Comparing Two Small Independent Proportions, Michael Vorburger, Breda Munoz May 2009

Approximations To Power When Comparing Two Small Independent Proportions, Michael Vorburger, Breda Munoz

Journal of Modern Applied Statistical Methods

No abstract provided.

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The Bootstrap Method For The Selection Of A Shrinkage Factor In Two-Stage Estimation Of The Reliability Function Of An Exponential Distribution, Makarand V. Ratnaparkhi, Vasant B. Waikar, Fredrick J. Schuurmann May 2009

The Bootstrap Method For The Selection Of A Shrinkage Factor In Two-Stage Estimation Of The Reliability Function Of An Exponential Distribution, Makarand V. Ratnaparkhi, Vasant B. Waikar, Fredrick J. Schuurmann

Journal of Modern Applied Statistical Methods

An application of a bootstrap method for selecting a suitable shrinkage factor for the two-stage shrinkage estimator of a reliability function for the exponential distribution is discussed. The estimator obtained here has higher efficiency as compared to the one where the shrinkage factor is not subjected to bootstrapping.

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Effects Of Population Distribution, Sample Size And Correlation Structure On Huberty’S Effect Size R, James B. Hittner May 2009

Effects Of Population Distribution, Sample Size And Correlation Structure On Huberty’S Effect Size R, James B. Hittner

Journal of Modern Applied Statistical Methods

Huberty’s (1994) R2 is derived by subtracting the expected value of R2 from an adjusted R2, and the square root of Huberty’s R2 is Huberty’s effect size R. The present study examined the effects of population distribution, sample size and population correlation structure on the statistical power of Huberty’s R.

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Estimating Task Duration In Pert Using The Weibull Probability Distribution, Edward L. Mccombs, Matthew E. Elam, David B. Pratt May 2009

Estimating Task Duration In Pert Using The Weibull Probability Distribution, Edward L. Mccombs, Matthew E. Elam, David B. Pratt

Journal of Modern Applied Statistical Methods

The Weibull probability distribution can be used as an alternative model for task time estimates in the PERT estimating methodology. It has the same advantages as the traditional beta distribution for this application. It has additional benefits, however, that make it a preferred option.

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Beyond Kappa: Estimating Inter-Rater Agreement With Nominal Classifications, Nol Bendermacher, Pierre Souren May 2009

Beyond Kappa: Estimating Inter-Rater Agreement With Nominal Classifications, Nol Bendermacher, Pierre Souren

Journal of Modern Applied Statistical Methods

Cohen’s Kappa and a number of related measures can all be criticized for their definition of correction for chance agreement. A measure is introduced that derives the corrected proportion of agreement directly from the data, thereby overcoming objections to Kappa and its related measures.

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Some Estimators For The Population Mean Using Auxiliary Information Under Ranked Set Sampling, Walid A. Abu-Dayyeh, M. S. Ahmed, R. A. Ahmed, Hassen A. Muttlak May 2009

Some Estimators For The Population Mean Using Auxiliary Information Under Ranked Set Sampling, Walid A. Abu-Dayyeh, M. S. Ahmed, R. A. Ahmed, Hassen A. Muttlak

Journal of Modern Applied Statistical Methods

Auxiliary information is used along with ranking information to derive several classes of estimators to estimate the population mean of a variable of interest based on RSS (ranked set sample). The properties of these newly suggested estimators were examined. Comparisons between special cases of these estimators and other known estimators are made using a real data set. Some of the new estimators are superior to the old ones in terms of bias and mean square error.

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A Heteroscedastic, Rank-Based Approach For Analyzing 2 X 2 Independent Groups Designs, Laura Mills, Robert A. Cribbie, Wei-Ming Luh May 2009

A Heteroscedastic, Rank-Based Approach For Analyzing 2 X 2 Independent Groups Designs, Laura Mills, Robert A. Cribbie, Wei-Ming Luh

Journal of Modern Applied Statistical Methods

The ANOVA F is a widely used statistic in psychological research despite its shortcomings when the assumptions of normality and variance heterogeneity are violated. A Monte Carlo investigation compared Type I error and power rates of the ANOVA F, Alexander-Govern with trimmed means and Johnson transformation, Welch-James with trimmed means and Johnson Transformation, Welch with trimmed means, and Welch on ranked data using Johansen’s interaction procedure. Results suggest that the ANOVA F is not appropriate when assumptions of normality and variance homogeneity are violated, and that the Welch/Johansen on ranks offers the best balance of empirical Type I error …

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Efficiency Of Canonical Discriminant Function Versus Mahalanobis Distance In Differentiating Groups: Screening Ovarian Cancer In A Multivariate System Analysis Using Enzyme Markers, Chinmoy K. Bose May 2009

Efficiency Of Canonical Discriminant Function Versus Mahalanobis Distance In Differentiating Groups: Screening Ovarian Cancer In A Multivariate System Analysis Using Enzyme Markers, Chinmoy K. Bose

Journal of Modern Applied Statistical Methods

Due to its low prevalence, high mortality and uniquely hidden intrapelvic position, ovarian cancer remains a subject of intense interest to researchers. Statistical calculation and new technology both have major roles to play in the effort to screen this cancer at an early stage. Advanced statistics, such as multivariate analysis, remain at the root of screening endeavors. Multivariate analysis has the power to combine many tests and to produce better results in terms high specificity and positive predictive value. Multivariate analysis techniques include Mahalanobis distance (D2), canonical stepwise discriminant function (Z) and Posterior Probability. These may have varied …

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Applying Census Data For Small Area Estimation In Community And Social Service Planning, Michael Wolf-Branigin, Hyon-Sook Suh, Star Muir, Emily S. Ihara May 2009

Applying Census Data For Small Area Estimation In Community And Social Service Planning, Michael Wolf-Branigin, Hyon-Sook Suh, Star Muir, Emily S. Ihara

Journal of Modern Applied Statistical Methods

Small area estimation provides a tool for community analysis. A procedure for accessing, selecting, joining and analyzing US Census data is provided. Skills acquired while completing the procedure include accessing census data, downloading boundary files and displaying themes. Such skills are valuable tools for students to possess as they enter the workforce.

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A Comparative Study Of Bayesian Model Selection Criteria For Capture-Recapture Models For Closed Populations, Ross M. Gosky, Sujit K. Ghosh May 2009

A Comparative Study Of Bayesian Model Selection Criteria For Capture-Recapture Models For Closed Populations, Ross M. Gosky, Sujit K. Ghosh

Journal of Modern Applied Statistical Methods

Capture-Recapture models estimate unknown population sizes. Eight standard closed population models exist, allowing for time, behavioral, and heterogeneity effects. Bayesian versions of these models are presented and use of Akaike's Information Criterion (AIC) and the Deviance Information Criterion (DIC) are explored as model selection tools, through simulation and real dataset analysis.

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Quantile Regression: On Inferences About The Slopes Corresponding To One, Two Or Three Quantiles, Rand R. Wilcox, Kathleen Costa May 2009

Quantile Regression: On Inferences About The Slopes Corresponding To One, Two Or Three Quantiles, Rand R. Wilcox, Kathleen Costa

Journal of Modern Applied Statistical Methods

The problem of testing hypotheses about the slope of a quantile regression line when the sample size is small is considered. A modified bootstrap method is suggested that is found to have certain advantages over the inverse rank method recommended by Koenker (1994). A method is suggested that simultaneously controls the probability of at least one Type I error when performing two or three tests corresponding to two or three specific quantiles. Using data from actual studies, it is illustrated that the new method can yield substantially shorter confidence intervals than the rank inverse method and, even with a large …

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A Monte Carlo Comparison Of Regression Estimators When The Error Distribution Is Long-Tailed Symmetric, Oya Can Mutan, Birdal Şenoğlu May 2009

A Monte Carlo Comparison Of Regression Estimators When The Error Distribution Is Long-Tailed Symmetric, Oya Can Mutan, Birdal Şenoğlu

Journal of Modern Applied Statistical Methods

The performances of the ordinary least squares (OLS), modified maximum likelihood (MML), least absolute deviations (LAD), Winsorized least squares (WIN), trimmed least squares (TLS), Theil’s (Theil) and weighted Theil’s (Weighted Theil) estimators are compared under the simple linear regression model in terms of their bias and efficiency when the distribution of error terms is long-tailed symmetric.

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Improved Confidence Intervals For The Difference Between Two Proportions, James F. Reed Iii May 2009

Improved Confidence Intervals For The Difference Between Two Proportions, James F. Reed Iii

Journal of Modern Applied Statistical Methods

Wald-z asymptotic methods, with and without a continuity correction, have less than nominal coverage probability characteristics but continue to be used. Newcombe's hybrid method and the Agresti-Caffo methods have coverage probabilities that are near nominal for either equal or unequal samples. Newcombe's hybrid and Agresti-Caffo methods demonstrate superior coverage properties.

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Multiple Regression In Pair Correlation Solution, Stan Lipovetsky May 2009

Multiple Regression In Pair Correlation Solution, Stan Lipovetsky

Journal of Modern Applied Statistical Methods

Behavior of the coefficients of ordinary least squares (OLS) regression with the coefficients regularized by the one-parameter ridge (Ridge-1) and two-parameter ridge (Ridge-2) regressions are compared. The ridge models are not prone to multicollinearity. The fit quality of Ridge-2 does not decrease with the profile parameter increase, but the Ridge-2 model converges to a solution proportional to the coefficients of pair correlation between the dependent variable and predictors. The Correlation-Regression (CORE) model suggests meaningful coefficients and net effects for the individual impact of the predictors, high quality model fit, and convenient analysis and interpretation of the regression. Simulation with three …

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Bayesian Inference On The Variance Of Normal Distribution Using Moving Extremes Ranked Set Sampling, Said Ali Al-Hadhrami, Amer Ibrahim Al-Omari May 2009

Bayesian Inference On The Variance Of Normal Distribution Using Moving Extremes Ranked Set Sampling, Said Ali Al-Hadhrami, Amer Ibrahim Al-Omari

Journal of Modern Applied Statistical Methods

Bayesian inference of the variance of the normal distribution is considered using moving extremes ranked set sampling (MERSS) and is compared with the simple random sampling (SRS) method. Generalized maximum likelihood estimators (GMLE), confidence intervals (CI), and different testing hypotheses are considered using simple hypothesis versus simple hypothesis, simple hypothesis versus composite alternative, and composite hypothesis versus composite alternative based on MERSS and compared with SRS. It is shown that modified inferences using MERSS are more efficient than their counterparts based on SRS.

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