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Articles 631 - 660 of 1162
Full-Text Articles in Statistics and Probability
Use Of Two Variables Having Common Mean To Improve The Bar-Lev, Bobovitch And Boukai Randomized Response Model, Oluseun Odumade, Sarjinder Singh
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.
Maximum Downside Semi Deviation Stochastic Programming For Portfolio Optimization Problem, Anton Abdulbasah Kamil, Khlipah Ibrahim
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 …
On Bayesian Shrinkage Setup For Item Failure Data Under A Family Of Life Testing Distribution, Gyan Prakash
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.
Bayesian Analysis Of Location-Scale Family Of Distributions Using S-Plus And R Software, Sheikh Parvaiz Ahmad, Aquil Ahmed, Athar Ali Khan
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.
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
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.
Bayesian Analysis For Component Manufacturing Processes, L. V. Nandakishore
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.
Neighbor Balanced Block Designs For Two Factors, Seema Jaggi, Cini Varghese, N. R. Abeynayake
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.
Ann Forecasting Models For Ise National-100 Index, Ozer Ozdemir, Atilla Aslanargun, Senay Asma
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.
Markov Chain Analysis And Student Academic Progress: An Empirical Comparative Study, Shafiqah Alawadhi, Mokhtar Konsowa
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.
Reducing Selection Bias In Analyzing Longitudinal Health Data With High Mortality Rates, Xian Liu, Charles C. Engel, Han Kang, Kristie L. Gore
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.
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
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.
Notes On Hypothesis Testing Under A Single-Stage Design In Phase Ii Trial, Kung-Jong Lui
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 …
Adjusted Confidence Interval For The Population Median Of The Exponential Distribution, Moustafa Omar Ahmed Abu-Shawiesh
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 …
A Comparison Between Unbiased Ridge And Least Squares Regression Methods Using Simulation Technique, Mowafaq M. Al-Kassab, Omar Q. Qwaider
A Comparison Between Unbiased Ridge And Least Squares Regression Methods Using Simulation Technique, Mowafaq M. Al-Kassab, Omar Q. Qwaider
Journal of Modern Applied Statistical Methods
The parameters of the multiple linear regression are estimated using least squares ( B̂LS ) and unbiased ridge regression methods (B̂(KI,J)). Data was created for fourteen independent variables with four different values of correlation between these variables using Monte Carlo techniques. The above methods were compared using the mean squares error criterion. Results show that the unbiased ridge method is preferable to the least squares method.
A General Class Of Chain-Type Estimators In The Presence Of Non-Response Under Double Sampling Scheme, Sunil Kumar, Housila P. Singh, Sandeep Bhougal
A General Class Of Chain-Type Estimators In The Presence Of Non-Response Under Double Sampling Scheme, Sunil Kumar, Housila P. Singh, Sandeep Bhougal
Journal of Modern Applied Statistical Methods
General class chain ratio type estimators for estimating the population mean of a study variable are examined in the presence of non-response under a double sampling scheme using a factor-type estimator (FTE). Properties of the suggested estimators are studied and compared to those of existing estimators. An empirical study is carried out to demonstrate the performance of the suggested estimators; empirical results support the theoretical study.
On Scientific Research: The Role Of Statistical Modeling And Hypothesis Testing, Lisa L. Harlow
On Scientific Research: The Role Of Statistical Modeling And Hypothesis Testing, Lisa L. Harlow
Journal of Modern Applied Statistical Methods
Comments on Rodgers (2010a, 2010b) and Robinson and Levin (2010) are presented. Rodgers (2010a) initially reported on a growing trend towards more mathematical and statistical modeling; and a move away from null hypothesis significance testing (NHST). He defended and clarified those views in his sequel. Robinson and Levin argued against the perspective espoused by Rodgers and called for more research using experimentally manipulated interventions and less emphasis on correlational research and ill-founded prescriptive statements. In this response, the goal of science and major scientific approaches are discussed as well as their strengths and shortcomings. Consideration is given to how their …
Nonlinear Trigonometric Transformation Time Series Modeling, K. A. Bashiru, O. E. Olowofeso, S. A. Owabumoye
Nonlinear Trigonometric Transformation Time Series Modeling, K. A. Bashiru, O. E. Olowofeso, S. A. Owabumoye
Journal of Modern Applied Statistical Methods
The nonlinear trigonometric transformation and augmented nonlinear trigonometric transformation with a polynomial of order two was examined. The two models were tested and compared using daily mean temperatures for 6 major towns in Nigeria with different rates of missing values. The results were used to determine the consistency and efficiency of the models formulated.
Derivation Of Mass Independent Quantum Treatment Of Phenomenon, David Parker
Derivation Of Mass Independent Quantum Treatment Of Phenomenon, David Parker
Journal of Modern Applied Statistical Methods
The derivation and applications is presented of a spatial variable or spatial radius which is related to the inertia or mass-energy of any quantum body by a Lorentz invariant relation. Mass independent DeBroglie and Schroedinger equations are derived and applied to the resolution of the linguistic incompatibility between quantum theory and the geometrical weak equivalence principle. The equivalence principle is restated in terms of the spatial radius. The gravitational attraction between bodies and the relativistic energy are both presented in terms of the spatial radius follows. The ratio of the gravitational force to the Coulomb force at the Planck scale …
Ranked Set Sampling Using Auxiliary Variables Of A Randomized Response Procedure For Estimating The Mean Of A Sensitive Quantitative Character, Carlos N. Bouza
Ranked Set Sampling Using Auxiliary Variables Of A Randomized Response Procedure For Estimating The Mean Of A Sensitive Quantitative Character, Carlos N. Bouza
Journal of Modern Applied Statistical Methods
The analysis of the behavior of estimators of the mean of a sensitive variable is considered when a randomized response procedure is used. The results deal with the inference based on simple random sampling with replacement study design. A study of the behavior of the procedures for a ranked set sampling design is developed. A gain in accuracy is generally associated with the proposed alternative model.
An Equivalence Test Based On N And P, Markus Neuhäeuser
An Equivalence Test Based On N And P, Markus Neuhäeuser
Journal of Modern Applied Statistical Methods
An equivalence test is proposed which is based on the P-value of a test for a difference and the sample size. This test may be especially appropriate for an exploratory re-analysis if only a non-significant test for a difference was reported. Thus, neither a confidence interval is available, nor is there access to the raw data. The test is illustrated using two examples; for both applications the smallest equivalence range for which equivalence could be demonstrated is calculated.
The Effectiveness Of Stepwise Discriminant Analysis As A Post Hoc Procedure To A Significant Manova, Erik L. Heiny, Daniel J. Mundform
The Effectiveness Of Stepwise Discriminant Analysis As A Post Hoc Procedure To A Significant Manova, Erik L. Heiny, Daniel J. Mundform
Journal of Modern Applied Statistical Methods
The effectiveness of SWDA as a post hoc procedure in a two-way MANOVA was examined using various numbers of dependent variables, sample sizes, effect sizes, correlation structures, and significance levels. The procedure did not work well in general except with small numbers of variables, larger samples and low correlations between variables.
Model Based Vs. Model Independent Tests For Cross-Correlation, H.E.T. Holgersson, Peter S. Karlsson
Model Based Vs. Model Independent Tests For Cross-Correlation, H.E.T. Holgersson, Peter S. Karlsson
Journal of Modern Applied Statistical Methods
This article discusses the issue of whether cross correlation should be tested by model dependent or model independent methods. Several different tests are proposed and their main properties are investigated analytically and with simulations. It is argued that model independent tests should be used in applied work.
On Exact 100(1-Α)% Confidence Interval Of Autocorrelation Coefficient In Multivariate Data When The Errors Are Autocorrelated, Madhusudan Bhandary
On Exact 100(1-Α)% Confidence Interval Of Autocorrelation Coefficient In Multivariate Data When The Errors Are Autocorrelated, Madhusudan Bhandary
Journal of Modern Applied Statistical Methods
An exact 100(1−α)% confidence interval for the autocorrelation coefficient ρ is derived based on a single multinormal sample. The confidence interval is the interval between the two roots of a quadratic equation in ρ . A real life example is also presented.
The Performance Of Multiple Imputation For Likert-Type Items With Missing Data, Walter Leite, S. Natasha Beretvas
The Performance Of Multiple Imputation For Likert-Type Items With Missing Data, Walter Leite, S. Natasha Beretvas
Journal of Modern Applied Statistical Methods
The performance of multiple imputation (MI) for missing data in Likert-type items assuming multivariate normality was assessed using simulation methods. MI was robust to violations of continuity and normality. With 30% of missing data, MAR conditions resulted in negatively biased correlations. With 50% missingness, all results were negatively biased.
Median-Unbiased Optimal Smoothing And Trend Extraction, Dimitrios D. Thomakos
Median-Unbiased Optimal Smoothing And Trend Extraction, Dimitrios D. Thomakos
Journal of Modern Applied Statistical Methods
The problem of smoothing a time series for extracting its low frequency characteristics, collectively called its trend, is considered. A competitive approach is proposed and compared with existing methods in choosing the optimal degree of smoothing based on the distribution of the residuals from the smooth trend.
On A Comparison Between Two Measures Of Spatial Association, Faisal G. Khamis, Abdul Aziz Jemain, Kamarulzaman Ibrahim
On A Comparison Between Two Measures Of Spatial Association, Faisal G. Khamis, Abdul Aziz Jemain, Kamarulzaman Ibrahim
Journal of Modern Applied Statistical Methods
Two measures of spatial association between two variables were used by many researchers. These are the Wartenberg (1985) and Lee (2001) measures. Based on simulation for lattice data, the sensitivity of both measures was studied and compared with different choices of spatial structures, spatial weights and sample sizes using bias and mean square error. Different scenarios are used in terms of assumed numbers and sample sizes. Moran’s I is used to examine the spatial autocorrelation of such a variable with itself. Both the Wartenberg and Lee measures are found to be sensitive, however, Wartenberg’s measure is found to be somewhat …
An Evaluation Of Multiple Imputation For Meta-Analytic Structural Equation Modeling, Carolyn F. Furlow, S. Natasha Beretvas
An Evaluation Of Multiple Imputation For Meta-Analytic Structural Equation Modeling, Carolyn F. Furlow, S. Natasha Beretvas
Journal of Modern Applied Statistical Methods
A simulation study was used to evaluate multiple imputation (MI) to handle MCAR correlations in the first step of meta-analytic structural equation modeling: the synthesis of the correlation matrix and the test of homogeneity. No substantial parameter bias resulted from using MI. Although some SE bias was found for meta-analyses involving smaller numbers of studies, the homogeneity test was never rejected when using MI.
Impact Of Measurement Model Modification On Structural Parameter Integrity When Measurement Model Is Misspecified, Weihua Fan
Journal of Modern Applied Statistical Methods
In the process of model modification, parameters of residual covariances are often treated as free parameters to improve model fit. However, the effect of such measurement model modifications on the important structural parameter estimates under various measurement model misspecifications has not been systematically studied. Monte Carlo simulation was conducted to compare structural estimates before and after measurement model modifications of adding residual covariances under varying sample sizes and model misspecifications. Results showed that researchers should pay attention when such measurement model modifications are made to initially misspecified model with missing path(s).
Can Specification Searches Be Useful For Hypothesis Generation?, Samuel B. Green, Marilyn S. Thompson
Can Specification Searches Be Useful For Hypothesis Generation?, Samuel B. Green, Marilyn S. Thompson
Journal of Modern Applied Statistical Methods
Previous studies suggest that results from specification searches, as typically employed in structural equation modeling, should not be used to reach strong research conclusions due to their poor reliability. Analyses of computer generated data indicate that search results can be sufficiently reliable for exploratory purposes with properly designed and analyzed studies.
Measuring Openness, Gaetano Ferrieri
Measuring Openness, Gaetano Ferrieri
Journal of Modern Applied Statistical Methods
A method for measuring international openness is elaborated. This synthetic indicator measures the capacity of countries for a given phenomenon adjusted for their weight in the same phenomenon. The method implemented and applied to international trade and illustrated here as a case study in merchandise exports, has a wide range of applications in the socio-economic field.