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Articles 1231 - 1260 of 1633
Full-Text Articles in Statistical Theory
An Alternative To Warner’S Randomized Response Model, Sat Gupta, Javid Shabbir
An Alternative To Warner’S Randomized Response Model, Sat Gupta, Javid Shabbir
Journal of Modern Applied Statistical Methods
A modification to Warner’s (1965) Randomized Response Model is suggested. The suggested model is more efficient than the original model.
Inference For P(Y, Vee Ming Ng
Inference For P(Y, Vee Ming Ng
Journal of Modern Applied Statistical Methods
Some tests and confidence bounds for the reliability parameter R=P(Y
Determining Parallel Analysis Criteria, Marley W. Watkins
Determining Parallel Analysis Criteria, Marley W. Watkins
Journal of Modern Applied Statistical Methods
Determining the number of factors to extract is a critical decision in exploratory factor analysis. Simulation studies have found the Parallel Analysis criterion to be accurate, but it is computationally intensive. Two freeware programs that implement Parallel Analysis on Macintosh and Windows operating systems are presented.
Change Point Estimation Of Bilevel Functions, Leming Qu, Yi-Cheng Tu
Change Point Estimation Of Bilevel Functions, Leming Qu, Yi-Cheng Tu
Journal of Modern Applied Statistical Methods
Reconstruction of a bilevel function such as a bar code signal in a partially blind deconvolution problem is an important task in industrial processes. Existing methods are based on either the local approach or the regularization approach with a total variation penalty. This article reformulated the problem explicitly in terms of change points of the 0-1 step function. The bilevel function is then reconstructed by solving the nonlinear least squares problem subject to linear inequality constraints, with starting values provided by the local extremas of the derivative of the convolved signal from discrete noisy data. Simulation results show a considerable …
Correlation Between The Number Of Epileptic And Healthy Children In Family Size That Follows A Size-Biased Modified Power Series Distribution, Ramalingam Shanmugam, Anwar Hassan, Peer Bilal Ahmad
Correlation Between The Number Of Epileptic And Healthy Children In Family Size That Follows A Size-Biased Modified Power Series Distribution, Ramalingam Shanmugam, Anwar Hassan, Peer Bilal Ahmad
Journal of Modern Applied Statistical Methods
An expression for the correlation between the random number of epileptic and healthy children in family whose size follows a size-biased Modified Power Series Distribution (SBMPSD) is obtained and illustrated. As special cases, results are extracted for size biased Modified Negative Binomial Distribution (SBGNBD), size biased Modified Poisson Distribution (SBGPD) and size biased Modified Logarithmic Series Distribution (SBGLSD).
Simulation Of Non-Normal Autocorrelated Variables, H.E.T. Holgersson
Simulation Of Non-Normal Autocorrelated Variables, H.E.T. Holgersson
Journal of Modern Applied Statistical Methods
All statistical methods rely on assumptions to some extent. Two assumptions frequently met in statistical analyses are those of normal distribution and independence. When examining robustness properties of such assumptions by Monte Carlo simulations it is therefore crucial that the possible effects of autocorrelation and non-normality are not confounded so that their separate effects may be investigated. This article presents a number of non-normal variables with non-confounded autocorrelation, thus allowing the analyst to specify autocorrelation or shape properties while keeping the other effect fixed.
Interval Estimation Of Risk Difference In Simple Compliance Randomized Trials, Kung-Jong Lui
Interval Estimation Of Risk Difference In Simple Compliance Randomized Trials, Kung-Jong Lui
Journal of Modern Applied Statistical Methods
Consider the simple compliance randomized trial, in which patients randomly assigned to the experimental treatment may switch to receive the standard treatment, while patients randomly assigned to the standard treatment are all assumed to receive their assigned treatment. Six asymptotic interval estimators for the risk difference in probabilities of response among patients who would accept the experimental treatment were developed. Monte Carlo methods were employed to evaluate and compare the finite-sample performance of these estimators. An example studying the effect of vitamin A supplementation on reducing mortality in preschool children was included to illustrate their practical use.
A Robust Exponentially Weighted Moving Average Control Chart For The Process Mean, Michael B. C. Khoo, S. Y. Sim
A Robust Exponentially Weighted Moving Average Control Chart For The Process Mean, Michael B. C. Khoo, S. Y. Sim
Journal of Modern Applied Statistical Methods
To date, numerous extensions of the exponentially weighted moving average, EWMA charts have been made. A new robust EWMA chart for the process mean is proposed. It enables easier detection of outliers and increase sensitivity to other forms of out-of-control situation when outliers are present.
A Comparison Of Risk Classification Methods For Claim Severity Data, Noriszura Ismail, Abdul Aziz Jemain
A Comparison Of Risk Classification Methods For Claim Severity Data, Noriszura Ismail, Abdul Aziz Jemain
Journal of Modern Applied Statistical Methods
The objective of this article is to compare several risk classification methods for claim severity data by using weighted equation which is written as a weighted difference between the observed and fitted values. The weighted equation will be applied to estimate claim severities which is equivalent to the total claim costs divided by the number of claims.
Supporting And Preparing Future Decision-Makers With The Needed Tools, Michael Wolf-Branigin
Supporting And Preparing Future Decision-Makers With The Needed Tools, Michael Wolf-Branigin
Journal of Modern Applied Statistical Methods
Supporting and Preparing Future Decision-makers with the Needed ToolsEducational and social service researchers and evaluators continue to develop advanced statistical methods. To ensure that our students have the essential skills as they enter direct service, the focus must be on assuring that they learn readily understandable methods that are appropriate for small samples and use repeated measures.
Statistical Tests, Tests Of Significance, And Tests Of A Hypothesis Using Excel, David A. Heiser
Statistical Tests, Tests Of Significance, And Tests Of A Hypothesis Using Excel, David A. Heiser
Journal of Modern Applied Statistical Methods
Microsoft’s spreadsheet program Excel has many statistical functions and routines. Over the years there have been criticisms about the inaccuracies of these functions and routines (see McCullough 1998, 1999). This article reviews some of these statistical methods used to test for differences between two samples. In practice, the analysis is done by a software program and often with the actual method used unknown. The user has to select the method and variations to be used, without full knowledge of just what calculations are used. Usually there is no convenient trace back to textbook explanations. This article describes the Excel algorithm …
Obituary: Cliff Lunneborg, Jmasm Editors
Obituary: Cliff Lunneborg, Jmasm Editors
Journal of Modern Applied Statistical Methods
No abstract provided.
Pietro Paoli, Italian Algebraist, John L. Cuzzocrea, Shlomo S. Sawilowsky
Pietro Paoli, Italian Algebraist, John L. Cuzzocrea, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
Pietro Paoli was a leading Italian mathematician in the late 18th century. His signed letter pertaining to the death of astronomer Giuseppe Antonio Slop is translated from Italian to flowing (American) English.
Robust Confidence Intervals For Effect Size In The Two-Group Case, H. J. Keselman, James Algina, Katherine Fradette
Robust Confidence Intervals For Effect Size In The Two-Group Case, H. J. Keselman, James Algina, Katherine Fradette
Journal of Modern Applied Statistical Methods
The probability coverage of intervals involving robust estimates of effect size based on seven procedures was compared for asymmetrically trimming data in an independent two-groups design, and a method that symmetrically trims the data. Four conditions were varied: (a) percentage of trimming, (b) type of nonnormal population distribution, (c) population effect size, and (d) sample size. Results indicated that coverage probabilities were generally well controlled under the conditions of nonnormality. The symmetric trimming method provided excellent probability coverage. Recommendations are provided.
Sample Size Calculation And Power Analysis Of Time-Averaged Difference, Honghu Liu, Tongtong Wu
Sample Size Calculation And Power Analysis Of Time-Averaged Difference, Honghu Liu, Tongtong Wu
Journal of Modern Applied Statistical Methods
Little research has been done on sample size and power analysis under repeated measures design. With detailed derivation, we have shown sample size calculation and power analysis equations for timeaveraged difference to allow unequal sample sizes between two groups for both continuous and binary measures and explored the relative importance of number of unique subjects and number of repeated measurements within each subject on statistical power through simulation.
Testing Normality Against The Laplace Distribution, Taisuke Otsu
Testing Normality Against The Laplace Distribution, Taisuke Otsu
Journal of Modern Applied Statistical Methods
Some normality test statistics are proposed by testing non-nested hypotheses of the normal distribution and the Laplace distribution. If the null hypothesis is normal, the proposed non-nested tests are asymptotically equivalent to Geary’s (1935) normality test. The proposed test statistics are compared by the method of approximate slopes and Monte Carlo experiments.
Testing For Aptitude-Treatment Interactions In Analysis Of Covariance And Randomized Block Designs Under Assumption Violations, Tim Moses, Alan Klockars
Testing For Aptitude-Treatment Interactions In Analysis Of Covariance And Randomized Block Designs Under Assumption Violations, Tim Moses, Alan Klockars
Journal of Modern Applied Statistical Methods
This study compared the robustness of two analysis strategies designed to detect Aptitude-Treatment Interactions to two of their similarly-held assumptions, normality and residual variance homogeneity. The analysis strategies were the test of slope differences in analysis of covariance and the test of the Block-by- Treatment interaction in randomized block analysis of variance. With equal sample sizes in the treatment groups the results showed that residual variance heterogeneity has little effect on either strategy but nonnormality makes the test of slope differences liberal and the test of the Block-by-Treatment interaction conservative. With unequal sample sizes in the treatment groups the often-reported …
Type I Error Of Four Pairwise Mean Comparison Procedures Conducted As Protected And Unprotected Tests, J. Jackson Barnette, James E. Mclean
Type I Error Of Four Pairwise Mean Comparison Procedures Conducted As Protected And Unprotected Tests, J. Jackson Barnette, James E. Mclean
Journal of Modern Applied Statistical Methods
Type I error control accuracy of four commonly used pairwise mean comparison procedures, conducted as protected or unprotected tests, is examined. If error control philosophy is experimentwise, Tukey’s HSD, as an unprotected test, is most accurate and if philosophy is per-experiment, Dunn-Bonferroni, conducted as an unprotected test, is most accurate.
Kim And Warde’S Mixed Randomized Response Technique For Complex Surveys, Amitava Saha
Kim And Warde’S Mixed Randomized Response Technique For Complex Surveys, Amitava Saha
Journal of Modern Applied Statistical Methods
The randomized response (RR) technique introduced by Warner (1965) was found to be an effective method for reducing answer bias and ensuring better respondent cooperation in estimating the proportion of people in a community bearing a sensitive attribute. Chaudhuri (2001a, 2001b, 2002, 2003) extended Warner’s method and several other well-known RR devices to complex surveys adopting a varying probability sampling design. Kim and Warde (2004) proposed an RR model assuming that the sample is selected with simple random sampling (SRS) with replacement (SRSWR). Here, the method of estimation is presented when sample is chosen with varying selection probabilities and Kim …
A Nonrigorous Approach Of Incorporating Sensitizing Rules Into Multivariate Control Charts, Michael B. C. Khoo
A Nonrigorous Approach Of Incorporating Sensitizing Rules Into Multivariate Control Charts, Michael B. C. Khoo
Journal of Modern Applied Statistical Methods
Multivariate control charts are becoming more important in the monitoring of processes in manufacturing industries because the quality of a process is usually determined by several correlated variables (quality characteristics). The most popular multivariate process control procedure is based on the Hotelling control chart. It is used to monitor the mean vector of a process. A nonrigorous approach of using four sensitizing rules is introduced to improve the performance of a conventional Hotelling chart. The use of these rules on a conventional Hotelling chart do not require a transformation of the T2 statistics into normal random variables. Thus, the …
Sample Size Selection For Pair-Wise Comparisons Using Information Criteria, Xuemei Pan, C. Mitchell Dayton
Sample Size Selection For Pair-Wise Comparisons Using Information Criteria, Xuemei Pan, C. Mitchell Dayton
Journal of Modern Applied Statistical Methods
This article provides results for rates of correct identifications of paired-comparison information criteria and Tukey HSD as functions of the pattern of mean differences and of sample size. Therefore, the tables provided are useful for selecting sample sizes in real world applications.
Quasi-Maximum Likelihood Estimation For Latent Variable Models With Mixed Continuous And Polytomous Data, Jens C. Eickhoff
Quasi-Maximum Likelihood Estimation For Latent Variable Models With Mixed Continuous And Polytomous Data, Jens C. Eickhoff
Journal of Modern Applied Statistical Methods
Latent variable modeling is a multivariate technique commonly used in the social and behavioral sciences. The models used in such analysis relate all observed variables to latent common factors. In many situations, however, some outcome variables are in polytomous form while other outcomes are measured on a continuous scale. Maximum likelihood estimation for latent variable models with mixed polytomous and continuous outcomes is computationally intensive and may become difficult to implement in many applications. In this article, a computationally practical, yet efficient, Quasi- Maximum Likelihood approach for latent variable models with mixed continuous and polytomous variables is proposed. Asymptotic properties …
Determination Of Optimal Block Designs With Pre-Assigned Variance For Elementary Contrasts, Seemon Thomas, Alex Thannippara, S. C. Bagui, D. K. Ghosh
Determination Of Optimal Block Designs With Pre-Assigned Variance For Elementary Contrasts, Seemon Thomas, Alex Thannippara, S. C. Bagui, D. K. Ghosh
Journal of Modern Applied Statistical Methods
A method for obtaining optimal designs from the class of variance balanced and connected designs was developed for comparing treatment effects with a pre-assigned variance. The properties of the C-matrix of a block design are employed in developing this method. Some new results concerning the design parameters and the non-zero characteristic root of the C-matrix are also presented.
A Bayesian Subset Analysis Of Sensory Evaluation Data, Balgobin Nandram
A Bayesian Subset Analysis Of Sensory Evaluation Data, Balgobin Nandram
Journal of Modern Applied Statistical Methods
In social sciences it is easy to carry out sensory experiments using say a J-point hedonic scale. One major problem with the J-point hedonic scale is that a conversion from the category scales to numeric scores might not be sensible because the panelists generally view increments on the hedonic scale as psychologically unequal. In the current problem several products are rated by a set of panelists on the J-point hedonic scale. One objective is to select the best subset of products and to assess the quality of the products by estimating the mean and standard deviation response …
Estimating The Slope Of Simple Linear Regression In The Presence Of Outliers, Mohammed Al-Haj Ebrahem, Amjad D. Al-Nasser
Estimating The Slope Of Simple Linear Regression In The Presence Of Outliers, Mohammed Al-Haj Ebrahem, Amjad D. Al-Nasser
Journal of Modern Applied Statistical Methods
In this article, an estimation procedure to simple linear regression in the presence of outliers is proposed. The performance of the proposed estimator, the AM estimator, is compared with other traditional estimators: least squares, Theil type repeated median, and geometric mean. A numerical example is given to illustrate the proposed estimator. Simulation results indicate that the proposed estimator is accurate and has a high precision in the presence of outliers.
Selection Of Independent Binary Features Using Probabilities: An Example From Veterinary Medicine, Ludmila I. Kuncheva, Zoë S.J. Hoare, Peter D. Cockcroft
Selection Of Independent Binary Features Using Probabilities: An Example From Veterinary Medicine, Ludmila I. Kuncheva, Zoë S.J. Hoare, Peter D. Cockcroft
Journal of Modern Applied Statistical Methods
Supervised classification into c mutually exclusive classes based on n binary features is considered. The only information available is an n×c table with probabilities. Knowing that the best d features are not the d best, simulations were run for 4 feature selection methods and an application to diagnosing BSE in cattle and Scrapie in sheep is presented.
Training Statisticians To Be Alert To The Dangers Of Misapplying Statistical Methods, Vance W. Berger
Training Statisticians To Be Alert To The Dangers Of Misapplying Statistical Methods, Vance W. Berger
Journal of Modern Applied Statistical Methods
Statisticians are faced with a variety of challenges. Their ability to cope successfully with these challenges depends, in large part, on the quality of their training. It is not the purpose of this article to present a comprehensive training plan that will overhaul the standard curriculum a statistician might follow under current training regimens (i.e., in a degree program). Rather, the objective is to point out important areas that appear to be under-represented in standard curricula and correspondingly overlooked too often in practice. The hope is that these areas might be better integrated into the training of the next generation …
Power Of The T Test For Normal And Mixed Normal Distributions, Marilyn S. Thompson, Samuel B. Green, Yi-Hsin Chen, Shawn Stockford, Wen-Juo Lo
Power Of The T Test For Normal And Mixed Normal Distributions, Marilyn S. Thompson, Samuel B. Green, Yi-Hsin Chen, Shawn Stockford, Wen-Juo Lo
Journal of Modern Applied Statistical Methods
Previous research suggests that the power of the independent-samples t test decreases when population distributions are mixed normal rather than normal, and that robust methods have superior power under these conditions. However, under some conditions, the power for the independent-samples t test can be greater when the population distributions for the independent groups are mixed normal rather than normal. The implications of these results are discussed.
Misconceptions Leading To Choosing The T Test Over The Wilcoxon Mann-Whitney Test For Shift In Location Parameter, Shlomo S. Sawilowsky
Misconceptions Leading To Choosing The T Test Over The Wilcoxon Mann-Whitney Test For Shift In Location Parameter, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
There exist many misconceptions in choosing the t over the Wilcoxon Rank-Sum test when testing for shift. Examples are given in the following three groups: (1) false statement, (2) true premise, but false conclusion, and (3) true statement irrelevant in choosing between the t test and the Wilcoxon Rank Sum test.
Jmasm21: Pcic_Sas: Best Subsets Using Information Criteria, C. Mitchell Dayton, Xuemei Pan
Jmasm21: Pcic_Sas: Best Subsets Using Information Criteria, C. Mitchell Dayton, Xuemei Pan
Journal of Modern Applied Statistical Methods
PCIC_SAS is a SAS program for identifying optimal subsets of means based on independent groups. All possible configurations of ordered subsets of groups are considered and a best model is identified using both the AIC and BIC information criteria. Results for models with homogeneous variances as well as models with heterogeneity of variance in the same pattern as the means are reported.