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Articles 451 - 480 of 1097
Full-Text Articles in Applied Statistics
Improved Estimators In Finite Population Surveys: Theory And Applications, Sunil Kumar
Improved Estimators In Finite Population Surveys: Theory And Applications, Sunil Kumar
Journal of Modern Applied Statistical Methods
Improved estimators are proposed for estimating the population mean Y̅ of the study variable y using auxiliary variable x in simple random sampling. Explicit expression for the bias and MSE of the proposed family are derived to the first order of approximation. The proposed estimators are compared with other estimators and theoretical findings are illustrated by two numerical examples.
An Approach For Dealing With Statuses Of Non-Statistically Significant Interactions Between Treatments, Zakaria M. Sawan
An Approach For Dealing With Statuses Of Non-Statistically Significant Interactions Between Treatments, Zakaria M. Sawan
Journal of Modern Applied Statistical Methods
A field experiment on cotton yield resulted in a non-statistically significant interaction. An approach for follow-up examination between treatments based on least significant difference values was suggested to identify the effect regardless of insignificance. It was found that the classical formula used in calculating the significance of interactions suffers a possible shortage that can be eliminated by applying a suggested revision.
Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing, Richard B. Anderson
Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing, Richard B. Anderson
Journal of Modern Applied Statistical Methods
To counter past assertions that permutation testing is not distribution-free, this article clarifies that the critical p value (alpha) in permutation testing is not a Type I error rate and that a test's validity is independent of the concept of Type I error.
A Response To Anderson's (2013) Conceptual Distinction Between The Critical P Value And Type I Error Rate In Permutation Testing, Fortunato Pesarin, Stefano Bonnini
A Response To Anderson's (2013) Conceptual Distinction Between The Critical P Value And Type I Error Rate In Permutation Testing, Fortunato Pesarin, Stefano Bonnini
Journal of Modern Applied Statistical Methods
Pesarin and Bonnini respond to Anderson's (2013) Conceptual Distinction between the Critical p value and Type I Error Rate in Permutation Testing
A Monte Carlo Simulation Of The Robust Rank-Order Test Under Various Population Symmetry Conditions, William T. Mickelson
A Monte Carlo Simulation Of The Robust Rank-Order Test Under Various Population Symmetry Conditions, William T. Mickelson
Journal of Modern Applied Statistical Methods
The Type I Error Rate of the Robust Rank Order test under various population symmetry conditions is explored through Monte Carlo simulation. Findings indicate the test has difficulty controlling Type I error under generalized Behrens-Fisher conditions for moderately sized samples.
Constructing A More Powerful Test In Two-Level Block Randomized Designs, Spyros Konstantopoulos
Constructing A More Powerful Test In Two-Level Block Randomized Designs, Spyros Konstantopoulos
Journal of Modern Applied Statistical Methods
A more powerful test is proposed for the treatment effect in two-level block randomized designs where random assignment takes place at the first level. When clustering at the second level is assumed to be known, the proposed test produces higher estimates of power than the typical test.
Bayesian Inference Of Pair-Copula Constriction For Multivariate Dependency Modeling Of Iran’S Macroeconomic Variables, M. R. Zadkarami, O. Chatrabgoun
Bayesian Inference Of Pair-Copula Constriction For Multivariate Dependency Modeling Of Iran’S Macroeconomic Variables, M. R. Zadkarami, O. Chatrabgoun
Journal of Modern Applied Statistical Methods
Bayesian inference of pair-copula constriction (PCC) is used for multivariate dependency modeling of Iran’s macroeconomics variables: oil revenue, economic growth, total consumption and investment. These constructions are based on bivariate t-copulas as building blocks and can model the nature of extreme events in bivariate margins individually. The model parameter was estimated based on Markov chain Monte Carlo (MCMC) methods. A MCMC algorithm reveals unconditional as well as conditional independence in Iran’s macroeconomic variables, which can simplify resulting PCC’s for these data.
Using The Bootstrap For Estimating The Sample Size In Statistical Experiments, Maher Qumsiyeh
Using The Bootstrap For Estimating The Sample Size In Statistical Experiments, Maher Qumsiyeh
Journal of Modern Applied Statistical Methods
Efron’s (1979) Bootstrap has been shown to be an effective method for statistical estimation and testing. It provides better estimates than normal approximations for studentized means, least square estimates and many other statistics of interest. It can be used to select the active factors - factors that have an effect on the response - in experimental designs. This article shows that the bootstrap can be used to determine sample size or the number of runs required to achieve a certain confidence level in statistical experiments.
The X-Alter Algorithm: A Parameter-Free Method Of Unsupervised Clustering, Thomas Laloë, Rémi Servien
The X-Alter Algorithm: A Parameter-Free Method Of Unsupervised Clustering, Thomas Laloë, Rémi Servien
Journal of Modern Applied Statistical Methods
Using quantization techniques, Laloë (2010) defined a new clustering algorithm called Alter. This L1-based algorithm is shown to be convergent but suffers two major flaws. The number of clusters, K, must be supplied by the user and the computational cost is high. This article adapts the X-means algorithm (Pelleg & Moore, 2000) to solve both problems.
Estimating Heterogeneous Intra-Class Correlation Coefficients In Dyadic Ecological Momentary Assessment, Emily A. Blood, Leslie A. Kalish, Lydia A. Shrier
Estimating Heterogeneous Intra-Class Correlation Coefficients In Dyadic Ecological Momentary Assessment, Emily A. Blood, Leslie A. Kalish, Lydia A. Shrier
Journal of Modern Applied Statistical Methods
A method is described for estimating and testing predictors for influence on the variance of momentary behaviors in dyadic ecological momentary assessment data. Results show that the method allows intraclass correlations of momentary observations from two members of the same couple to vary by observation-level, individual-level and couple-level predictors.
Jmasm 32: Multiple Imputation Of Missing Multilevel, Longitudinal Data: A Case When Practical Considerations Trump Best Practices?, Jennifer E. V. Lloyd, Jelena Obradović, Richard M. Carpiano, Frosso Motti-Stefanidi
Jmasm 32: Multiple Imputation Of Missing Multilevel, Longitudinal Data: A Case When Practical Considerations Trump Best Practices?, Jennifer E. V. Lloyd, Jelena Obradović, Richard M. Carpiano, Frosso Motti-Stefanidi
Journal of Modern Applied Statistical Methods
A pedagogical tool is presented for applied researchers dealing with incomplete multilevel, longitudinal data. It explains why such data pose special challenges regarding missingness. Syntax created to perform a multiply-imputed growth modeling procedure in Stata Version 11 (StataCorp, 2009) is also described.
Bootstrap Interval Estimation Of Reliability Via Coefficient Omega, Miguel A. Padilla, Jasmin Divers
Bootstrap Interval Estimation Of Reliability Via Coefficient Omega, Miguel A. Padilla, Jasmin Divers
Journal of Modern Applied Statistical Methods
Three different bootstrap confidence intervals (CIs) for coefficient omega were investigated. The CIs were assessed through a simulation study with conditions not previously investigated. All methods performed well; however, the normal theory bootstrap (NTB) CI had the best performance because it had more consistent acceptable coverage under the simulation conditions investigated.
Fitting Proportional Odds Models To Educational Data With Complex Sampling Designs In Ordinal Logistic Regression, Xing Liu, Hari Koirala
Fitting Proportional Odds Models To Educational Data With Complex Sampling Designs In Ordinal Logistic Regression, Xing Liu, Hari Koirala
Journal of Modern Applied Statistical Methods
The conventional proportional odds (PO) model assumes that data are collected using simple random sampling by which each sampling unit has the equal probability of being selected from a population. However, when complex survey sampling designs are used, such as stratified sampling, clustered sampling or unequal selection probabilities, it is inappropriate to conduct ordinal logistic regression analyses without taking sampling design into account. Failing to do so may lead to biased estimates of parameters and incorrect corresponding variances. This study illustrates the use of PO models with complex survey data to predict mathematics proficiency levels using Stata and compare the …
Selection Of Mixed Sampling Plan With Qss-1(N; CN, CT) Plan As Attribute Plan Indexed Through Mapd And Lql, R. Sampath Kumar, M. Indra, R. Radhakrishnan
Selection Of Mixed Sampling Plan With Qss-1(N; CN, CT) Plan As Attribute Plan Indexed Through Mapd And Lql, R. Sampath Kumar, M. Indra, R. Radhakrishnan
Journal of Modern Applied Statistical Methods
A procedure for the construction and selection of the mixed sampling plan using MAPD as a quality standard with the QSS-1 (n; cN, cT) plan as an attribute plan is presented. The plans indexed through MAPD and LQL are constructed and compared for efficiency. Tables are provided for selection of an appropriate sampling plan.
On Some Negative Integer Moments Of Quasi-Negative-Binomial Distribution, Anwar Hassan, Sheikh Bilal
On Some Negative Integer Moments Of Quasi-Negative-Binomial Distribution, Anwar Hassan, Sheikh Bilal
Journal of Modern Applied Statistical Methods
Negative integer moments of the quasi-negative-binomial distribution (QNBD) are investigated. This distribution includes recurrence relations which are helpful in the solution of many applied statistical problems, particularly in life testing and survey sampling, where ratio estimators are useful. Results study show the negative-binomial distribution when the parameter θ2 is zero and also indicate the mean of the QNBD model when its parameters are changed.
On Some Properties And Estimation Of Size-Biased Polya-Eggenberger Distribution, Anwar Hassan, Sheikh Bilal, Imtiyaz Ahmad Shah
On Some Properties And Estimation Of Size-Biased Polya-Eggenberger Distribution, Anwar Hassan, Sheikh Bilal, Imtiyaz Ahmad Shah
Journal of Modern Applied Statistical Methods
A size-biased version of Polya-Eggenberger distribution is introduced explicitly and by a mixture model. The proposed distribution is unimodal with positive integer moments. The recurrence relation between moments (about the origin) of the proposed distribution is established and its relationship with other distributions is discussed. Different estimation techniques are proposed to estimate the parameters of the distribution.
Regression Split By Levels Of The Dependent Variable, Stan Lipovetsky
Regression Split By Levels Of The Dependent Variable, Stan Lipovetsky
Journal of Modern Applied Statistical Methods
Multiple regression coefficients split by the levels of the dependent variable are examined. The decomposition of the coefficients can be defined by points on the ordinal scale or by levels in the numerical response using the Gifi system of binary variables. This approach permits consideration of specific values of the coefficients at each layer of the response variable. Numerical results illustrate how to identify levels of interpretable regression coefficients.
Extreme Value Charts And Analysis Of Means (Anom) Based On The Log Logistic Distribution, B. Srinivasa Rao, J. Pratapa Reddy, G. Sarath Babu
Extreme Value Charts And Analysis Of Means (Anom) Based On The Log Logistic Distribution, B. Srinivasa Rao, J. Pratapa Reddy, G. Sarath Babu
Journal of Modern Applied Statistical Methods
A probability model of a quality characteristic is assumed to follow a log logistic distribution. This article proposes variable control charts, termed extreme value charts, based on the extreme values of each subgroup. The control chart constants depend on the probability model of the extreme order statistics and the size of each subgroup. The analysis of means (ANOM) technique for a skewed population is applied with respect to log logistic distribution. Results are illustrated using examples based on real data.
Examining Growth With Statistical Shape Analysis And Comparison Of Growth Models, Deniz Sigirli, Ilker Ercan
Examining Growth With Statistical Shape Analysis And Comparison Of Growth Models, Deniz Sigirli, Ilker Ercan
Journal of Modern Applied Statistical Methods
Growth curves have been widely used in the fields of biology, zoology and medicine for assessing some measurable trait of an organism, such as height, weight, area or volume. In statistical shape analysis, a size measure is obtained using the geometrical information of an object as opposed to linear measurements. The performances of commonly used non-linear growth curves are compared by using centroid size as a size measure in a simulation study. An example is provided on the relationship between centroid size of the cerebellum and disease duration in multiple sclerosis patients.
Examining Multiple Comparison Procedures According To Error Rate, Power Type And False Discovery Rate, Guven Ozkaya, Ilker Ercan
Examining Multiple Comparison Procedures According To Error Rate, Power Type And False Discovery Rate, Guven Ozkaya, Ilker Ercan
Journal of Modern Applied Statistical Methods
Examining pairwise differences between means is a common practice of applied researchers, and the selection of an appropriate multiple comparison procedure (MCP) is important for analyzing pairwise comparisons. This study examines the performance of MCPs under the assumption of homogeneity of variances for various numbers of groups with equal and unequal sample sizes via a simulation study. MCPs are compared according to type I error rate, power type and false discovery rate (FDR). Results show that the LSD and Duncan procedures have high error rates and Scheffe’s procedure has low power; no remarkable differences between the other procedures considered were …
Class(Es) Of Factor-Type Estimator(S) In Presence Of Measurement Error, Diwakar Shukla, Sharad Pathak, Narendra Singh Thakur
Class(Es) Of Factor-Type Estimator(S) In Presence Of Measurement Error, Diwakar Shukla, Sharad Pathak, Narendra Singh Thakur
Journal of Modern Applied Statistical Methods
When data is collected via sample survey it is assumed whatever is reported by a respondent is correct. However, given the issues of prestige bias, personal respect and honor, respondents’ self-reported data often produces over- or under- estimated values as opposed to true values regarding the variables under question. This causes measurement error to be present in sample values. This article considers the factortype estimator as an estimation tool and examines its performance under a measurement error model. Expressions of optimization are derived and theoretical results are supported by numerical examples.
Exact Logistic Regression For A Matched Pairs Case-Control Design With Polytomous Exposure Variables, Shyam S. Ganguly
Exact Logistic Regression For A Matched Pairs Case-Control Design With Polytomous Exposure Variables, Shyam S. Ganguly
Journal of Modern Applied Statistical Methods
Logistic regression methods are useful in estimating odds ratios under matched pairs case-control designs when the exposure variable of interest is binary or polytomous in nature. Analysis is typically performed using large sample approximation techniques. When conducting the analysis with polytomous exposure variable, situations where the numbers of discordant pairs in the resulting cells are small or the data structure is sparse can be encountered. In such situations, the asymptotic method of analysis is questionable, thus an exact method of analysis may be more suitable. A method is presented that performs exact inference in the case of pair-wise matched case-control …
Modified Edf Goodness Of Fit Tests For Logistic Distribution Under Srs And Rss, S. A. Al-Subh, M. T. Alodat, Kamaruzaman Ibrahim, Abdul Aziz Jemain
Modified Edf Goodness Of Fit Tests For Logistic Distribution Under Srs And Rss, S. A. Al-Subh, M. T. Alodat, Kamaruzaman Ibrahim, Abdul Aziz Jemain
Journal of Modern Applied Statistical Methods
Modified forms of goodness of fit tests are presented for the logistic distribution using statistics based on the empirical distribution function (EDF). A method to improve the power of the modified EDF goodness of fit tests is introduced based on Ranked Set sampling (RSS). Data are collected via the Ranked Set Sampling (RSS) technique (McIntyre, 1952). Critical values for the logistic distribution with unknown parameters are provided and the powers of the tests are given for a number of alternative distributions. A simulation study is presented to illustrate the power of the new method.
Small-To-Medium Enterprises And Economic Growth: A Comparative Study Of Clustering Techniques, Karim K. Mardaneh
Small-To-Medium Enterprises And Economic Growth: A Comparative Study Of Clustering Techniques, Karim K. Mardaneh
Journal of Modern Applied Statistical Methods
Small-to-medium enterprises (SMEs) in regional (non-metropolitan) areas are considered when economic planning may require large data sets and sophisticated clustering techniques. The economic growth of regional areas was investigated using four clustering algorithms. Empirical analysis demonstrated that the modified global k-means algorithm outperformed other algorithms.
Posterior Estimates Of Poisson Distribution Using R Software, Raja Sultan, S.P. Ahmad
Posterior Estimates Of Poisson Distribution Using R Software, Raja Sultan, S.P. Ahmad
Journal of Modern Applied Statistical Methods
The Bayesian estimation of unknown parameter of the Poisson distribution is examined under different priors. The posterior distributions for the unknown parameter of the Poisson distribution are derived using the following priors: uniform, Jeffrey’s, Gamma distribution, Gamma-Chi-square distribution, Gammaexponential distribution and Chi-square-exponential distribution. Numerical and graphical illustrations of the posterior densities of the parameters of interest were conducted using R Software.
Weighted Cook-Johnson Copula And Their Characterizations: Application To Probably Modeling Of The Hot Spring Eruptions, Hakim Bekrizadeh, Gholam Ali Parham, Mohamd Reza Zadkarmi
Weighted Cook-Johnson Copula And Their Characterizations: Application To Probably Modeling Of The Hot Spring Eruptions, Hakim Bekrizadeh, Gholam Ali Parham, Mohamd Reza Zadkarmi
Journal of Modern Applied Statistical Methods
Copulas have emerged as a practical method for multivariate modeling. A limited amount of work has been conducted regarding the application of copula-based modeling in context analysis. This study generalizes the Cook-Johnson copula under the appropriate weighted function and provides examples and the properties of the generalized Cook-Johnson copula. Results show that the generalized Cook-Johnson copula is suitable for probable modeling of hot spring eruption.
Comparing Two Independent Groups Via A Quantile Generalization Of The Wilcoxon-Mann-Whitney Test, Rand R. Wilcox
Comparing Two Independent Groups Via A Quantile Generalization Of The Wilcoxon-Mann-Whitney Test, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
The Wilcoxon-Mann-Whitney test, as well as modern improvements, are based in part on an estimate of p = P(D < 0), where D = X−Y and X and Y are independent random variables; a common goal is to test H0: p = 0.5. This corresponds to testing H0: ξ0.5, where ξ0.5 is the 0.5 quantile of the distribution of D. If the distributions associated with X and Y do not differ, then D has a symmetric distribution about zero. In particular, ξq + ξ1-q = 0 for any q ≤ 0.5, where ξq is the qth quantile. Methods aimed at testing H0: p = 0.5 are generalized by …
Single Sampling Plans For Variables Indexed By Aql And Aoql With Measurement Error, R. Sankle, J.R. Singh
Single Sampling Plans For Variables Indexed By Aql And Aoql With Measurement Error, R. Sankle, J.R. Singh
Journal of Modern Applied Statistical Methods
Single sampling plans are investigated for variables indexed by acceptable quality level (AQL) and average outgoing quality limit (AOQL) under measurement error. Procedures and tables are provided for selection of single sampling plans for variables for given AQL and AOQL when rejected lots are 100% inspected for replacement of a nonconforming unit. For a particular sampling plan in operation for an observed measurement, a method for determining true operating characteristic (OC) functions and average outgoing quality (AOQ) is described for various error sizes.
An Extension Of Cochran-Orcutt Procedure For Generalized Linear Regression Models With Periodically Correlated Errors, Abdullah A. Smadi, Nour H. Abu-Afouna
An Extension Of Cochran-Orcutt Procedure For Generalized Linear Regression Models With Periodically Correlated Errors, Abdullah A. Smadi, Nour H. Abu-Afouna
Journal of Modern Applied Statistical Methods
An important assumption of ordinary regression models is independence among errors. This research considers the case of periodically correlated errors following the periodic AR model of order 1 (PAR(1)). The remedial measure for correlated errors in regression known as the Cochran-Orcutt procedure is generalized to the case of periodically correlated errors. The motivation for making such generalizations is that the response data may inhibit some seasonality, which may not be captured by the traditional AR(1) autoregressive model. The proposed procedure is described and the bias and MSE of the resulting intercept and slope parameter estimates of the simple LR model …
A Proposed Ridge Parameter To Improve The Least Square Estimator, Ghadban Khalaf
A Proposed Ridge Parameter To Improve The Least Square Estimator, Ghadban Khalaf
Journal of Modern Applied Statistical Methods
Ridge regression, a form of biased linear estimation, is a more appropriate technique than ordinary least squares (OLS) estimation in the case of highly intercorrelated explanatory variables in the linear regression model Y = β + u. Two proposed ridge regression parameters from the mean square error (MSE) perspective are evaluated. A simulation study was conducted to demonstrate the performance of the proposed estimators compared to the OLS, HK and HKB estimators. Results show that the suggested estimators outperform the OLS and the other estimators regarding the ridge parameters in all situations examined.