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Articles 1921 - 1950 of 2693

Full-Text Articles in Statistics and Probability

Factors, Preventions And Correction Methods For Non-Response In Sample Surveys, Godwin Nwanzu Amahi Dec 2010

Factors, Preventions And Correction Methods For Non-Response In Sample Surveys, Godwin Nwanzu Amahi

CBN Journal of Applied Statistics (JAS)

Missing survey data occur because of unit and item non-response. This is practically independent of the method of data collection. As a result of the bias that non-response sometimes introduces in survey estimates, identifying factors that promote it, and taking measures of prevention and correction methods are clearly necessary. The standard method to compensate for unit non-response is by weighting adjustment, while item non-responses are handled by some form of imputation. This paper reviews factors that give rise to nonresponse and the corresponding methods used for its prevention and control. It also discusses their properties.

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Addressing The Problem Of Non-Response And Response Bias, Fabian C. Okafor Dec 2010

Addressing The Problem Of Non-Response And Response Bias, Fabian C. Okafor

CBN Journal of Applied Statistics (JAS)

Survey planners and analysts in Nigeria have devoted much more attention to sampling errors at the expense of nonsampling errors (non-response and response errors). Sampling error is the degree to which the sample estimate differs from the average value of the characteristic due to chance. The present discussion will be centered on non-sampling error, which may present serious deficiencies in the statistics and render the survey useless. According to Platek and Gray (1986), “Non-response has been generally recognized as important measure of the quality of data since it affects the estimates by introducing a possible bias in the estimates and …

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Statistics For National Development, Sani I. Doguwa Dec 2010

Statistics For National Development, Sani I. Doguwa

CBN Journal of Applied Statistics (JAS)

Good statistics that has been collected according to agreed good practices are crucial as a tool for development. Gross domestic product (GDP) and other measures of economic activity such as Gross National Income (GNI) together with their individual components, show how the economy is responding to government policy and other influences. The balance of payments can demonstrate the requirement for policy adjustments and is also one of the indicators scrutinised by potential foreign investors in the country. Agricultural statistics clearly have implications for longer-term planning, particularly if they show a move away from the land into urban areas or a …

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Spatial Epidemiology Of Birth Defects In The United States And The State Of Utah Using Geographic Information Systems And Spatial Statistics, Samson Y. Gebreab Dec 2010

Spatial Epidemiology Of Birth Defects In The United States And The State Of Utah Using Geographic Information Systems And Spatial Statistics, Samson Y. Gebreab

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Oral clefts are the most common form of birth defects in the United States (US) and the State of Utah has among the highest prevalence of oral clefts in the nation. The overall objective of this dissertation was to examine the spatial distribution of oral clefts and their linkage with a broad range of demographic, behavioral, social, economic, and environmental risk factors through the application of Geographic Information Systems (GIS) and spatial statistics. Using innovative linked micromaps plots, we investigated the geographic patterns of oral clefts occurrence from 1998 to 2002 and their relationships with maternal smoking rates and proportion …

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Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 2: Profiles Of Artist Neighborhoods, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran Nov 2010

Putting Artists On The Map: A Five Part Study Of Greater Cleveland Artists' Location Decisions - Part 2: Profiles Of Artist Neighborhoods, Mark Salling, Gregory Soltis, Charles Post, Sharon Bliss, Ellen Cyran

All Maxine Goodman Levin School of Urban Affairs Publications

A series of reports detailing the residential and work space location preferences of Cuyahoga county's artists.

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Regression Approach To Adjust Wia Performance Standards, Timothy J. Bartik, Randall W. Eberts, Kenneth J. Kline Nov 2010

Regression Approach To Adjust Wia Performance Standards, Timothy J. Bartik, Randall W. Eberts, Kenneth J. Kline

Presentations

No abstract provided.

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Generalized Variances Ratio Test For Comparing K Covariance Matrices From Dependent Normal Populations, Marcelo Angelo Cirillo, Daniel Furtado Ferreira, Thelma Sáfadi, Eric Batista Ferreira Nov 2010

Generalized Variances Ratio Test For Comparing K Covariance Matrices From Dependent Normal Populations, Marcelo Angelo Cirillo, Daniel Furtado Ferreira, Thelma Sáfadi, Eric Batista Ferreira

Journal of Modern Applied Statistical Methods

New tests based on the ratio of generalized variances are presented to compare covariance matrices from dependent normal populations. Monte Carlo simulation concluded that the tests considered controlled the Type I error, providing empirical probabilities that were consistent with the nominal level stipulated.

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A Ga-Based Sales Forecasting Model Incorporating Promotion Factors, Li-Chih Wang, Chin-Lien Wang Nov 2010

A Ga-Based Sales Forecasting Model Incorporating Promotion Factors, Li-Chih Wang, Chin-Lien Wang

Journal of Modern Applied Statistical Methods

Because promotions are critical factors highly related to product sales of consumer packaged goods (CPG) companies, predictors concerning sales forecast of CPG products must take promotions into consideration. Decomposition regression incorporating contextual factors offers a method for exploiting both reliability of statistical forecasting and flexibility of judgmental forecasting employing domain knowledge. However, it suffers from collinearity causing poor performance in variable identification and parameter estimation with traditional ordinary least square (OLS). Empirical research evidence shows that - in the case of collinearity - in variable identification, parameter estimation, and out of sample forecasting, genetic algorithms (GA) as an estimator outperform …

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Estimating The Non-Existent Mean And Variance Of The F-Distribution By Simulation, Hamid Reza Kamali, Parisa Shahnazari-Shahrezaei Nov 2010

Estimating The Non-Existent Mean And Variance Of The F-Distribution By Simulation, Hamid Reza Kamali, Parisa Shahnazari-Shahrezaei

Journal of Modern Applied Statistical Methods

In theory, all moments of some probability distributions do not necessarily exist. In the other words, they may be infinite or undefined. One of these distributions is the F-distribution whose mean and variance have not been defined for the second degree of freedom less than 3 and 5, respectively. In some cases, a large statistical population having an F-distribution may exist and the aim is to obtain its mean and variance which are an estimation of the non-existent mean and variance of F-distribution. This article considers a large sample F-distribution to estimate its non-existent mean and variance using Simul8 simulation …

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Ridge Regression Based On Some Robust Estimators, Hatice Samkar, Ozlem Alpu Nov 2010

Ridge Regression Based On Some Robust Estimators, Hatice Samkar, Ozlem Alpu

Journal of Modern Applied Statistical Methods

Robust ridge methods based on M, S, MM and GM estimators are examined in the presence of multicollinearity and outliers. GMWalker, using the LS estimator as the initial estimator is used. S and MM estimators are also used as initial estimators with the aim of evaluating the two alternatives as biased robust methods.

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A Flexible Method For Testing Independence In Two-Way Contingency Tables, Peyman Jafari, Noori Akhtar-Danesh, Zahra Bagheri Nov 2010

A Flexible Method For Testing Independence In Two-Way Contingency Tables, Peyman Jafari, Noori Akhtar-Danesh, Zahra Bagheri

Journal of Modern Applied Statistical Methods

A flexible approach for testing association in two-way contingency tables is presented. It is simple, does not assume a specific form for the association and is applicable to tables with nominal-by-nominal, nominal-by-ordinal, and ordinal-by-ordinal classifications.

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Statistical And Mathematical Modeling Versus Nhst? There’S No Competition!, Joseph Lee Rodgers Nov 2010

Statistical And Mathematical Modeling Versus Nhst? There’S No Competition!, Joseph Lee Rodgers

Journal of Modern Applied Statistical Methods

Some of Robinson & Levin’s critique of Rodgers (2010) is cogent, helpful, and insightful – although limiting. Recent methodology has advanced through the development of structural equation modeling, multi-level modeling, missing data methods, hierarchical linear modeling, categorical data analysis, as well as the development of many dedicated and specific behavioral models. These methodological approaches are based on a revised epistemological system, and have emerged naturally, without the need for task forces, or even much self-conscious discussion. The original goal was neither to develop nor promote a modeling revolution. That has occurred; I documented its development and its status. Two organizing …

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Effect Of Measurement Errors On The Separate And Combined Ratio And Product Estimators In Stratified Random Sampling, Housila P. Singh, Namrata Karpe Nov 2010

Effect Of Measurement Errors On The Separate And Combined Ratio And Product Estimators In Stratified Random Sampling, Housila P. Singh, Namrata Karpe

Journal of Modern Applied Statistical Methods

Separate and combined ratio, product and difference estimators are introduced for population mean μY of a study variable Y using auxiliary variable X in stratified sampling when the observations are contaminated with measurement errors. The bias and mean squared error of the proposed estimators have been derived under large sample approximation and their properties are analyzed. Generalized versions of these estimators are given along with their properties.

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Recommended Sample Size For Conducting Exploratory Factor Analysis On Dichotomous Data, Robert H. Pearson, Daniel J. Mundform Nov 2010

Recommended Sample Size For Conducting Exploratory Factor Analysis On Dichotomous Data, Robert H. Pearson, Daniel J. Mundform

Journal of Modern Applied Statistical Methods

Minimum sample sizes are recommended for conducting exploratory factor analysis on dichotomous data. A Monte Carlo simulation was conducted, varying the level of communalities, number of factors, variable-to-factor ratio and dichotomization threshold. Sample sizes were identified based on congruence between rotated population and sample factor loadings.

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Incidence And Prevalence For A Triply Censored Data, Hilmi F. Kittani Nov 2010

Incidence And Prevalence For A Triply Censored Data, Hilmi F. Kittani

Journal of Modern Applied Statistical Methods

The model introduced for the natural history of a progressive disease has four disease states which are expressed as a joint distribution of three survival random variables. Covariates are included in the model using Cox’s proportional hazards model with necessary assumptions needed. Effects of the covariates are estimated and tested. Formulas for incidence in the preclinical, clinical and death states are obtained, and prevalence formulas are obtained for the preclinical and clinical states. Estimates of the sojourn times in the preclinical and clinical states are obtained.

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Robust Estimators In Logistic Regression: A Comparative Simulation Study, Sanizah Ahmad, Norazan Mohamed Ramli, Habshah Midi Nov 2010

Robust Estimators In Logistic Regression: A Comparative Simulation Study, Sanizah Ahmad, Norazan Mohamed Ramli, Habshah Midi

Journal of Modern Applied Statistical Methods

The maximum likelihood estimator (MLE) is commonly used to estimate the parameters of logistic regression models due to its efficiency under a parametric model. However, evidence has shown the MLE has an unduly effect on the parameter estimates in the presence of outliers. Robust methods are put forward to rectify this problem. This article examines the performance of the MLE and four existing robust estimators under different outlier patterns, which are investigated by real data sets and Monte Carlo simulation.

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Use Of Two Variables Having Common Mean To Improve The Bar-Lev, Bobovitch And Boukai Randomized Response Model, Oluseun Odumade, Sarjinder Singh Nov 2010

Use Of Two Variables Having Common Mean To Improve The Bar-Lev, Bobovitch And Boukai Randomized Response Model, Oluseun Odumade, Sarjinder Singh

Journal of Modern Applied Statistical Methods

A new method to improve the randomized response model due to Bar-Lev, Bobovitch and Boukai (2004) is suggested. It has been observed that if two sensitive (or non sensitive) variables exist that are related to the main study sensitive variable, then those variables could be used to construct ratio type adjustments to the usual estimator of the population mean of a sensitive variable due to Bar-Lev, Bobovitch and Boukai (2004).The relative efficiency of the proposed estimators is studied with respect to the Bar-Lev, Bobovitch and Boukai (2004) models under different situations.

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Maximum Downside Semi Deviation Stochastic Programming For Portfolio Optimization Problem, Anton Abdulbasah Kamil, Khlipah Ibrahim Nov 2010

Maximum Downside Semi Deviation Stochastic Programming For Portfolio Optimization Problem, Anton Abdulbasah Kamil, Khlipah Ibrahim

Journal of Modern Applied Statistical Methods

Portfolio optimization is an important research field in financial decision making. The chief character within optimization problems is the uncertainty of future returns. Probabilistic methods are used alongside optimization techniques. Markowitz (1952, 1959) introduced the concept of risk into the problem and used a mean-variance model to identify risk with the volatility (variance) of the random objective. The mean-risk optimization paradigm has since been expanded extensively both theoretically and computationally. A single stage and two stage stochastic programming model with recourse are presented for risk averse investors with the objective of minimizing the maximum downside semideviation. The models employ the …

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On Bayesian Shrinkage Setup For Item Failure Data Under A Family Of Life Testing Distribution, Gyan Prakash Nov 2010

On Bayesian Shrinkage Setup For Item Failure Data Under A Family Of Life Testing Distribution, Gyan Prakash

Journal of Modern Applied Statistical Methods

Properties of the Bayes shrinkage estimator for the parameter are studied of a family of probability density function when item failure data are available. The symmetric and asymmetric loss functions are considered for two different prior distributions. In addition, the Bayes estimates of reliability function and hazard rate are obtained and their properties are studied.

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Bayesian Analysis Of Location-Scale Family Of Distributions Using S-Plus And R Software, Sheikh Parvaiz Ahmad, Aquil Ahmed, Athar Ali Khan Nov 2010

Bayesian Analysis Of Location-Scale Family Of Distributions Using S-Plus And R Software, Sheikh Parvaiz Ahmad, Aquil Ahmed, Athar Ali Khan

Journal of Modern Applied Statistical Methods

The Normal and Laplace’s methods of approximation for posterior density based on the location-scale family of distributions in terms of the numerical and graphical simulation are examined using S-PLUS and R Software.

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Empirical Characteristic Function Approach To Goodness Of Fit Tests For The Logistic Distribution Under Srs And Rss, M. T. Alodat, S. A. Al-Subh, Kamaruzaman Ibrahim, Abdul Aziz Jemain Nov 2010

Empirical Characteristic Function Approach To Goodness Of Fit Tests For The Logistic Distribution Under Srs And Rss, M. T. Alodat, S. A. Al-Subh, Kamaruzaman Ibrahim, Abdul Aziz Jemain

Journal of Modern Applied Statistical Methods

The integral of the squares modulus of the difference between the empirical characteristic function and the characteristic function of the hypothesized distribution is used by Wong and Sim (2000) to test for goodness of fit. A weighted version of Wong and Sim (2000) under ranked set sampling, a sampling technique introduced by McIntyre (1952), is examined. Simulations that show the ranked set sampling counterpart of Wong and Sim (2000) is more powerful.

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Bayesian Analysis For Component Manufacturing Processes, L. V. Nandakishore Nov 2010

Bayesian Analysis For Component Manufacturing Processes, L. V. Nandakishore

Journal of Modern Applied Statistical Methods

In manufacturing processes various machines are used to produce the same product. Based on the age, make, etc., of the machines the output may not always follow the same distribution. An attempt is made to introduce Bayesian techniques for a two machine problem. Two cases are presented in this article.

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Neighbor Balanced Block Designs For Two Factors, Seema Jaggi, Cini Varghese, N. R. Abeynayake Nov 2010

Neighbor Balanced Block Designs For Two Factors, Seema Jaggi, Cini Varghese, N. R. Abeynayake

Journal of Modern Applied Statistical Methods

The concept of Neighbor Balanced Block (NBB) designs is defined for the experimental situation where the treatments are combinations of levels of two factors and only one of the factors exhibits a neighbor effect. Methods of constructing complete NBB designs for two factors in a plot that is strongly neighbor balanced for one factor are obtained. These designs are variance balanced for estimating the direct effects of contrasts pertaining to combinations of levels of both the factors. An incomplete NBB design for two factors is also presented and is found to be partially variance balanced with three associate classes.

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Ann Forecasting Models For Ise National-100 Index, Ozer Ozdemir, Atilla Aslanargun, Senay Asma Nov 2010

Ann Forecasting Models For Ise National-100 Index, Ozer Ozdemir, Atilla Aslanargun, Senay Asma

Journal of Modern Applied Statistical Methods

Prediction of the outputs of real world systems with accuracy and high speed is crucial in financial analysis due to its effects on worldwide economics. Because the inputs of the financial systems are timevarying functions, the development of algorithms and methods for modeling such systems cannot be neglected. The most appropriate forecasting model for the ISE national-100 index was investigated. Box- Jenkins autoregressive integrated moving average (ARIMA) and artificial neural networks (ANN) are considered by using several evaluations. Results showed that the ANN model with linear architecture better fits the candidate data.

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Markov Chain Analysis And Student Academic Progress: An Empirical Comparative Study, Shafiqah Alawadhi, Mokhtar Konsowa Nov 2010

Markov Chain Analysis And Student Academic Progress: An Empirical Comparative Study, Shafiqah Alawadhi, Mokhtar Konsowa

Journal of Modern Applied Statistical Methods

An application of Markov Chain Analysis of student flow at Kuwait University is presented based on a random sample of 1,100 students from the academic years 1996-1997 to 2004-2005. Results were obtained for each college and in total which allows for a comparative study. The students’ mean lifetimes in different levels of study in the colleges as well as the percentage of dropping out of the system are estimated.

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Reducing Selection Bias In Analyzing Longitudinal Health Data With High Mortality Rates, Xian Liu, Charles C. Engel, Han Kang, Kristie L. Gore Nov 2010

Reducing Selection Bias In Analyzing Longitudinal Health Data With High Mortality Rates, Xian Liu, Charles C. Engel, Han Kang, Kristie L. Gore

Journal of Modern Applied Statistical Methods

Two longitudinal regression models, one parametric and one nonparametric, are developed to reduce selection bias when analyzing longitudinal health data with high mortality rates. The parametric mixed model is a two-step linear regression approach, whereas the nonparametric mixed-effects regression model uses a retransformation method to handle random errors across time.

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Geographic Factors Of Residential Burglaries - A Case Study In Nashville, Tennessee, Jonathan A. Hall Nov 2010

Geographic Factors Of Residential Burglaries - A Case Study In Nashville, Tennessee, Jonathan A. Hall

Masters Theses & Specialist Projects

This study examines geographic patterns and geographic factors of residential burglary at the Nashville, TN area for a twenty year period at five year interval starting in 1988. The purpose of this study is to identify what geographic factors have impacted on residential burglary rates, and if there were changes in the geographic patterns of residential burglary over the study period. Several criminological theories guide this study, with the most prominent being Social Disorganization Theory and Routine Activities Theory. Both of these theories focus on the relationships of place and crime. A number of spatial analysis methods are hence adopted …

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The Not-So-Quiet Revolution: Cautionary Comments On The Rejection Of Hypothesis Testing In Favor Of A “Causal” Modeling Alternative, Daniel H. Robinson, Joel R. Levin Nov 2010

The Not-So-Quiet Revolution: Cautionary Comments On The Rejection Of Hypothesis Testing In Favor Of A “Causal” Modeling Alternative, Daniel H. Robinson, Joel R. Levin

Journal of Modern Applied Statistical Methods

Rodgers (2010) recently applauded a revolution involving the increased use of statistical modeling techniques. It is argued that such use may have a downside, citing empirical evidence in educational psychology that modeling techniques are often applied in cross-sectional, correlational studies to produce unjustified causal conclusions and prescriptive statements.

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Notes On Hypothesis Testing Under A Single-Stage Design In Phase Ii Trial, Kung-Jong Lui Nov 2010

Notes On Hypothesis Testing Under A Single-Stage Design In Phase Ii Trial, Kung-Jong Lui

Journal of Modern Applied Statistical Methods

A primary objective of a phase II trial is to determine future development is warranted for a new treatment based on whether it has sufficient activity against a specified type of tumor. Limitations exist in the commonly-used hypothesis setting and the standard test procedure for a phase II trial. This study reformats the hypothesis setting to mirror the clinical decision process in practice. Under the proposed hypothesis setting, the critical points and the minimum required sample size for a desired power of finding a superior treatment at a given α -level are presented. An example is provided to illustrate how …

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Adjusted Confidence Interval For The Population Median Of The Exponential Distribution, Moustafa Omar Ahmed Abu-Shawiesh Nov 2010

Adjusted Confidence Interval For The Population Median Of The Exponential Distribution, Moustafa Omar Ahmed Abu-Shawiesh

Journal of Modern Applied Statistical Methods

The median confidence interval is useful for one parameter families, such as the exponential distribution, and it may not need to be adjusted if censored observations are present. In this article, two estimators for the median of the exponential distribution, MD, are considered and compared based on the sample median and the maximum likelihood method. The first estimator is the sample median, MD1, and the second estimator is the maximum likelihood estimator of the median, MDMLE. Both estimators are used to propose a modified confidence interval for the population median of the exponential distribution, MD …

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