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Articles 31 - 60 of 67
Full-Text Articles in Social and Behavioral Sciences
The Information Criterion, Masume Ghahramani
The Information Criterion, Masume Ghahramani
Journal of Modern Applied Statistical Methods
The Akaike information criterion, AIC, is widely used for model selection. Using the AIC as the estimator of asymptotic unbias for the second term Kullbake-Leibler risk considers the divergence between the true model and offered models. However, it is an inconsistent estimator. A proposed approach the problem is the use of A'IC, a consistently offered information criterion. Model selection of classic and linear models are considered by a Monte Carlo simulation.
Fitting Stereotype Logistic Regression Models For Ordinal Response Variables In Educational Research (Stata), Xing Liu
Journal of Modern Applied Statistical Methods
The stereotype logistic (SL) model is an alternative to the proportional odds (PO) model for ordinal response variables when the proportional odds assumption is violated. This model seems to be underutilized. One major reason is the constraint of current statistical software packages. Statistical Package for the Social Sciences (SPSS) cannot perform the SL regression analysis, and SAS does not have the procedure developed to directly estimate the model. The purpose of this article was to illustrate the stereotype logistic (SL) regression model, and apply it to estimate mathematics proficiency level of high school students using Stata. In addition, it compared …
Comparison Of Three Calculation Methods For A Bayesian Inference Of Two Poisson Parameters, Yohei Kawasaki, Etsuo Miyaoka
Comparison Of Three Calculation Methods For A Bayesian Inference Of Two Poisson Parameters, Yohei Kawasaki, Etsuo Miyaoka
Journal of Modern Applied Statistical Methods
The statistical inference drawn from the difference between two independent Poisson parameters is often discussed in medical literature. Kawasaki and Miyaoka (2012) proposed an index θ = P(λ1,post < λ2,post), where λ1,post and λ2,post denote Poisson parameters following posterior density. A new calculation method is proposed using MCMC and an approximate expression and exact expression for θ are compared.
On The Exponentiated Weibull Distribution For Modeling Wind Speed In South Western Nigeria, Olanrewaju I. Shittu, K A. Adepoju
On The Exponentiated Weibull Distribution For Modeling Wind Speed In South Western Nigeria, Olanrewaju I. Shittu, K A. Adepoju
Journal of Modern Applied Statistical Methods
One of the bases for assessment of wind energy potential for a specified region is the probability distribution of wind speed. Thus, appropriate and adequate specification of the probability distribution of wind speed becomes increasingly important. Several distributions have been proposed for describing wind distribution. Among the most popular distributions is the Weibull whose choice is due to its flexibility. An exponentiated Weibull distribution is proposed as an alternative to model wind speed data with a view to comparing it with the existing Weibull distribution. Results indicate that the proposed distribution outperforms the existing Weibull distribution for modeling wind speed …
Relative Importance Of Predictors In Multilevel Modeling, Yan Liu, Bruno D. Zumbo, Amery D. Wu
Relative Importance Of Predictors In Multilevel Modeling, Yan Liu, Bruno D. Zumbo, Amery D. Wu
Journal of Modern Applied Statistical Methods
The Pratt index is a useful and practical strategy for day-to-day researchers when ordering predictors in a multiple regression analysis. The purposes of this study are to introduce and demonstrate the use of the Pratt index to assess the relative importance of predictors for a random intercept multilevel model.
An Alternative Test For The Equality Of Intraclass Correlation Coefficients Under Unequal Family Sizes For Several Populations, Madhusudan Bhandary, Koji Fujiwara
An Alternative Test For The Equality Of Intraclass Correlation Coefficients Under Unequal Family Sizes For Several Populations, Madhusudan Bhandary, Koji Fujiwara
Journal of Modern Applied Statistical Methods
An alternative test for the equality of several intraclass correlation coefficients under unequal family sizes based on several independent multinormal samples is proposed. It was found that the alternative test consistently and reliably produced results superior to those of Likelihood ratio test (LRT) proposed by Bhandary and Alam (2000) and Fmax test proposed by Bhandary and Fujiwara (2006) in terms of power for various combinations of intraclass correlation coefficient values and also the alternative test stays closer to the significance level under null hypothesis compared to the Likelihood ratio test and Fmax test. This alternative test is computationally …
Statistical Power Of Alternative Structural Models For Comparative Effectiveness Research: Advantages Of Modeling Unreliability, Emil N. Coman, Eugen Iordache, Lisa Dierker, Judith Fifield, Jean J. Schensul, Suzanne Suggs, Russell Barbour
Statistical Power Of Alternative Structural Models For Comparative Effectiveness Research: Advantages Of Modeling Unreliability, Emil N. Coman, Eugen Iordache, Lisa Dierker, Judith Fifield, Jean J. Schensul, Suzanne Suggs, Russell Barbour
Journal of Modern Applied Statistical Methods
The advantages of modeling the unreliability of outcomes when evaluating the comparative effectiveness of health interventions is illustrated. Adding an action-research intervention component to a regular summer job program for youth was expected to help in preventing risk behaviors. A series of simple two-group alternative structural equation models are compared to test the effect of the intervention on one key attitudinal outcome in terms of model fit and statistical power with Monte Carlo simulations. Some models presuming parameters equal across the intervention and comparison groups were under- powered to detect the intervention effect, yet modeling the unreliability of the outcome …
Bias And Precision Of The Squared Canonical Correlation Coefficient Under Nonnormal Data Condition, Lesley F. Leach, Robin K. Henson
Bias And Precision Of The Squared Canonical Correlation Coefficient Under Nonnormal Data Condition, Lesley F. Leach, Robin K. Henson
Journal of Modern Applied Statistical Methods
Monte Carlo methods were employed to investigate the effect of nonnormality on the bias associated with the squared canonical correlation coefficient (Rc2). The majority of Rc2 estimates were found to be extremely biased, but the magnitude of bias was impacted little by the degree of nonnormality.
An Exploratory Graphical Method For Identifying Associations In R X C Contingency Tables, Martin L. Lesser, Meredith B. Akerman
An Exploratory Graphical Method For Identifying Associations In R X C Contingency Tables, Martin L. Lesser, Meredith B. Akerman
Journal of Modern Applied Statistical Methods
On finding a significant association between rows and columns of an r x c contingency table, the next step is to study the nature of the association in more detail. The use of a scree plot to visualize the largest contributions to Χ2 among all cells in the table in order to determine the nature of the association in more detail is proposed.
Median Based Modified Ratio Estimators With Known Quartiles Of An Auxiliary Variable, Jambulingam Subramani, G Prabavathy
Median Based Modified Ratio Estimators With Known Quartiles Of An Auxiliary Variable, Jambulingam Subramani, G Prabavathy
Journal of Modern Applied Statistical Methods
New median based modified ratio estimators for estimating a finite population mean using quartiles and functions of an auxiliary variable are proposed. The bias and mean squared error of the proposed estimators are obtained and the mean squared error of the proposed estimators are compared with the usual simple random sampling without replacement (SRSWOR) sample mean, ratio estimator, a few existing modified ratio estimators, the linear regression estimator and median based ratio estimator for certain natural populations. A numerical study shows that the proposed estimators perform better than existing estimators; in addition, it is shown that the proposed median based …
Ridge Regression In Calibration Models With Symmetric Padding Extension-Daubechies Wavelet Transform Preprocessing, Nurwiani, S Sunaryo, Setiawan, B W. Otok
Ridge Regression In Calibration Models With Symmetric Padding Extension-Daubechies Wavelet Transform Preprocessing, Nurwiani, S Sunaryo, Setiawan, B W. Otok
Journal of Modern Applied Statistical Methods
Wavelet transformation is commonly used in calibration models as a preprocessing step. This preprocessing does not involve all results of a spectrum discretization; consequently, a lot of information can be missing. To avoid missing information, a symmetric padding extension (SPE) can be used to place all data points into dyadic scales, however, high dimensional discretization points need to be reduced. Dimension reduction can be performed with Daubechies wavelet transformation (DWT). Scale function and Daubechies wavelet are continuous functions, thus they perform a faster approximation. SPE-DWT preprocessing combines SPE and DWT. Multicollinearity often occurs in calibration models; the ridge regression (RR) …
Estimation And Testing In Type-Ii Generalized Half Logistic Distribution, R R. L. Kantam, V Ramakrishna, M S. Ravikumar
Estimation And Testing In Type-Ii Generalized Half Logistic Distribution, R R. L. Kantam, V Ramakrishna, M S. Ravikumar
Journal of Modern Applied Statistical Methods
A generalization of the Half Logistic Distribution is developed through exponentiation of its survival function and named the Type II Generalized Half Logistic Distribution (GHLD). The distributional characteristics are presented and estimation of its parameters using maximum likelihood and modified maximum likelihood methods is studied with comparisons. Discrimination between Type II GHLD and exponential distribution in pairs is conducted via likelihood ratio criterion.
A Compound Of Geeta Distribution With Generalized Beta Distribution, Adil Rashid, T R. Jan
A Compound Of Geeta Distribution With Generalized Beta Distribution, Adil Rashid, T R. Jan
Journal of Modern Applied Statistical Methods
A compound of Geeta distribution with Generalized Beta distribution (GBD) is obtained and the compound is specialized for different values of β. The first order factorial moments of some special compound distributions are also obtained. A chronological overview of recent developments in the compounding of distributions is provided in the introduction.
Hierarchical Clustering With Simple Matching And Joint Entropy Dissimilarity Measure, A Mete ÇilingtüRk, ÖZlem ErgüT
Hierarchical Clustering With Simple Matching And Joint Entropy Dissimilarity Measure, A Mete ÇilingtüRk, ÖZlem ErgüT
Journal of Modern Applied Statistical Methods
Conventional clustering algorithms are restricted for use with data containing ratio or interval scale variables; hence, distances are used. As social studies require merely categorical data, the literature is enriched with more complicated clustering techniques and algorithms of categorical data. These techniques are based on similarity or dissimilarity matrices. The algorithms are using density based or pattern based approaches. A probabilistic nature to similarity structure is proposed. The entropy dissimilarity measure has comparable results with simple matching dissimilarity at hierarchical clustering. It overcomes dimension increase through binarization of the categorical data. This approach is also functional with the clustering methods, …
Distance Correlation Coefficient: An Application With Bayesian Approach In Clinical Data Analysis, Atanu Bhattacharjee
Distance Correlation Coefficient: An Application With Bayesian Approach In Clinical Data Analysis, Atanu Bhattacharjee
Journal of Modern Applied Statistical Methods
The distance correlation coefficient – based on the product-moment approach – is one method by which to explore the relationship between variables. The Bayesian approach is a powerful tool to determine statistical inferences with credible intervals. Prior information about the relationship between BP and Serum cholesterol was applied to formulate the distance correlation between the two variables. The conjugate prior is considered to formulate the posterior estimates of the distance correlations. The illustrated method is simple and is suitable for other experimental studies.
Estimation Of Reliability In Multicomponent Stress-Strength Based On Generalized Rayleigh Distribution, Gadde Srinivasa Rao
Estimation Of Reliability In Multicomponent Stress-Strength Based On Generalized Rayleigh Distribution, Gadde Srinivasa Rao
Journal of Modern Applied Statistical Methods
A multicomponent system of k components having strengths following k- independently and identically distributed random variables x1, x2, ..., xk and each component experiencing a random stress Y is considered. The system is regarded as alive only if at least s out of k (s < k) strengths exceed the stress. The reliability of such a system is obtained when strength and stress variates are given by a generalized Rayleigh distribution with different shape parameters. Reliability is estimated using the maximum likelihood (ML) method of estimation in samples drawn from strength and stress …
Stochastic Randomized Response Model For A Quantitative Sensitive Random Variable, Sarjinder Singh, Stephen A. Sedory
Stochastic Randomized Response Model For A Quantitative Sensitive Random Variable, Sarjinder Singh, Stephen A. Sedory
Journal of Modern Applied Statistical Methods
A new stochastic randomized response model is introduced that is useful for estimating the population mean of a sensitive quantitative variable. The proposed stochastic randomized response model is an extension of the stochastic randomized response model from a qualitative sensitive variable to a quantitative variable found in Singh (2002). The stochastic nature of a randomized response device helps increase a respondent’s cooperation while collecting information on sensitive variables in a society. The Bar-Lev, Bobovitch, and Boukai (2004) model is shown to be a special case of the proposed model.
Specifying Asymmetric Star Models With Linear And Nonlinear Garch Innovations: Monte Carlo Approach, Olaoluwa S. Yaya, Olanrewaju I. Shittu
Specifying Asymmetric Star Models With Linear And Nonlinear Garch Innovations: Monte Carlo Approach, Olaoluwa S. Yaya, Olanrewaju I. Shittu
Journal of Modern Applied Statistical Methods
Economic and finance time series are typically asymmetric and are expected to be modeled using asymmetrical nonlinear time series models. Smooth Transition Autoregressive (STAR) models: Logistic (LSTAR) and Exponential (ESTAR) are known to be asymmetric and symmetric respectively. Under non-normal and heteroscedastic innovations, the residuals of these models are estimated using Generalized Autoregressive Conditionally Heteroscedastic (GARCH) models with variants which include linear and nonlinear forms. The small sample properties of STAR-GARCH variants are yet to be established but these properties are investigated using Monte Carlo (MC) simulation. An MC investigation was conducted to investigate the performance of selections of STAR-GARCH …
Robust Regression Analysis For Non-Normal Situations Under Symmetric Distributions Arising In Medical Research, S S. Ganguly
Robust Regression Analysis For Non-Normal Situations Under Symmetric Distributions Arising In Medical Research, S S. Ganguly
Journal of Modern Applied Statistical Methods
In medical research, while carrying out regression analysis, it is usually assumed that the independent (covariates) and dependent (response) variables follow a multivariate normal distribution. In some situations, the covariates may not have normal distribution and instead may have some symmetric distribution. In such a situation, the estimation of the regression parameters using Tiku’s Modified Maximum Likelihood (MML) method may be more appropriate. The method of estimating the parameters is discussed and the applications of the method are illustrated using real sets of data from the field of public health.
A Flexible Method For Conducting Power Analysis For Two- And Three-Level Hierarchical Linear Models In R, Yi Pan, Matthew T. Mcbee
A Flexible Method For Conducting Power Analysis For Two- And Three-Level Hierarchical Linear Models In R, Yi Pan, Matthew T. Mcbee
Journal of Modern Applied Statistical Methods
A general approach for conducting power analysis in two- and three-level hierarchical linear models (HLMs) is described. The method can be used to perform power analysis to detect fixed effects at any level of a HLM with dichotomous or continuous covariates. It can easily be extended to perform power analysis for functions of parameters. Important steps in the derivation of this approach are illustrated and numerical examples are provided. Sample code implementing this approach is provided using the free program R.
Jmasm 33: A Two Dependent Samples Maximum Test Calculator: Excel, Saverpierre Maggio, Shlomo Sawilowsky
Jmasm 33: A Two Dependent Samples Maximum Test Calculator: Excel, Saverpierre Maggio, Shlomo Sawilowsky
Journal of Modern Applied Statistical Methods
An Excel Macro was created to provide researchers with an easy to use resource in order to calculate the two dependent samples maximum test as provided in Maggio and Sawilowsky (2014), which permits conducting both the two dependent samples t-test and Wilcoxon signed-ranks test on the same data while eliminating concerns related to Type I error inflation and choice of statistical tests.
A Comparison Of Shape And Scale Estimators Of The Two-Parameter Weibull Distribution, Florence George
A Comparison Of Shape And Scale Estimators Of The Two-Parameter Weibull Distribution, Florence George
Journal of Modern Applied Statistical Methods
Weibull distributions are widely used in reliability and survival analysis. In this paper, different methods to estimate the shape and scale parameters of the two-parameter Weibull distribution have been reviewed and compared, based on the bias, mean square error and variance. Because a theoretical comparison is not possible, an extensive simulation study has been conducted to compare the performance of different estimators. Based on the simulation study it was observed that MLE consistently performs better than other methods.
Predicting Survival Time Of Localized Melanoma Patients Using Discrete Survival Time Method, Taysseer Sharaf, Chris P. Tsokos
Predicting Survival Time Of Localized Melanoma Patients Using Discrete Survival Time Method, Taysseer Sharaf, Chris P. Tsokos
Journal of Modern Applied Statistical Methods
Melanoma is the most fatal type of skin cancer. It is ranked first in death of skin cancer diseases. This study establishes a statistical model that can predict the survival time of localized melanoma patients, as a function of age at diagnosis, tumor thickness, and extension of the tumor (tumor invasion). The discrete time survival method was used to build the statistical model. The patients involved in the current study were observed from the SEER database. Patients were divided into nine groups according to age at diagnosis. Variation in survival time was found to be significant among some of the …
Robustness Of Several Estimators Of The Acf Of Ar(1) Process With Non-Gaussian Errors, A A. Smadi, J J. Jaber, A G. Al-Zu'bi
Robustness Of Several Estimators Of The Acf Of Ar(1) Process With Non-Gaussian Errors, A A. Smadi, J J. Jaber, A G. Al-Zu'bi
Journal of Modern Applied Statistical Methods
The autocorrelation function (ACF) plays an important role in the context of ARMA modeling, especially for their identification and estimation. This study considers the robust estimation of the ACF of the AR(1) model if the white noise (WN) process is non- Gaussian. Three estimators including the ordinary moment estimator and two other (robust) estimators are considered. The impacts of the deviation from normality of the WN process on those estimators in terms of bias, MSE and distribution via Monte-Carlo simulation are examined. The empirical distribution of those estimators when the errors are normal, t, Cauchy and exponential are studied. …
Likelihood Ratio Type Test For Linear Failure Rate Distribution Vs. Exponential Distribution, R R. L. Kantam, M C. Priya, M S. Ravikumar
Likelihood Ratio Type Test For Linear Failure Rate Distribution Vs. Exponential Distribution, R R. L. Kantam, M C. Priya, M S. Ravikumar
Journal of Modern Applied Statistical Methods
The Linear Failure Rate Distribution (LFRD) is considered. The graphs of its probability density function are examined for selected parameter combinations. Some of them are similar to the well-known exponential distribution. Incidentally exponential distribution is one of the two component models of the LFRD model. In view of the simpler form of exponential model as applicable in inference, looking at the frequency curves of LFRD, a test statistic is proposed based on ratio of likelihood functions containing the standard forms of the density functions of both LFRD and Exponential to discriminate between LFRD and exponential models. The critical values and …
Population Mean Estimation With Sub Sampling The Non-Respondents Using Two Phase Sampling, Sunil Kumar, M Viswanathaiah
Population Mean Estimation With Sub Sampling The Non-Respondents Using Two Phase Sampling, Sunil Kumar, M Viswanathaiah
Journal of Modern Applied Statistical Methods
The problem of non-response in double (or two phase) sampling is dealt with combined ratio, product and regression estimators. Expressions of bias and MSE for these estimators are obtained. Comparisons of a proposed strategy with a usual unbiased estimator and other estimators are carried out and results obtained are illustrated numerically using an empirical sample.
Two Parameter Modified Ratio Estimators With Two Auxiliary Variables For Estimation Of Finite Population Mean With Known Skewness, Kurtosis And Correlation Coefficient, Jambulingam Subramani, G Prabavathy
Two Parameter Modified Ratio Estimators With Two Auxiliary Variables For Estimation Of Finite Population Mean With Known Skewness, Kurtosis And Correlation Coefficient, Jambulingam Subramani, G Prabavathy
Journal of Modern Applied Statistical Methods
Consider the two parameter modified ratio estimators for the estimation of finite population mean using the skewness, kurtosis and correlation coefficient of two auxiliary variables. The efficiencies of the proposed modified ratio estimators are assessed with that of the simple random sampling without replacement (SRSWOR) sample mean and some of the existing ratio estimators in terms of mean squared errors. The entire above is explained with the help of certain natural populations available in the literature.
Separate Ratio-Type Estimators Of Population Mean In Stratified Random Sampling, Rajesh Tailor, Hilal A. Lone
Separate Ratio-Type Estimators Of Population Mean In Stratified Random Sampling, Rajesh Tailor, Hilal A. Lone
Journal of Modern Applied Statistical Methods
Separate ratio-type estimators for population mean with their properties are considered. Some separate ratio-type estimators for population mean using known parameters of auxiliary variate are proposed. The bias and mean squared error of the proposed estimators are obtained up to the first degree of approximation. It is shown that the proposed estimators are more efficient than unbiased estimators in stratified random sampling and usual separate ratio estimators under certain obtained conditions. To judge the merits of the proposed estimators, an empirical study was conducted.
Inference For The Rayleigh Distribution Based On Progressive Type-Ii Fuzzy Censored Data, Abbas Pak, Gholam Ali Parham, Mansour Saraj
Inference For The Rayleigh Distribution Based On Progressive Type-Ii Fuzzy Censored Data, Abbas Pak, Gholam Ali Parham, Mansour Saraj
Journal of Modern Applied Statistical Methods
Classical statistical analysis of the Rayleigh distribution deals with precise information. However, in real world situations, experimental performance results cannot always be recorded or measured precisely, but each observable event may only be identified with a fuzzy subset of the sample space. Therefore, the conventional procedures used for estimating the Rayleigh distribution parameter will need to be adapted to the new situation. This article discusses different estimation methods for the parameters of the Rayleigh distribution on the basis of a progressively type-II censoring scheme when the available observations are described by means of fuzzy information. They include the maximum likelihood …
Evaluation Of Area Under The Constant Shape Bi-Weibull Roc Curve, Sudesh Pundir, R Amala
Evaluation Of Area Under The Constant Shape Bi-Weibull Roc Curve, Sudesh Pundir, R Amala
Journal of Modern Applied Statistical Methods
The Receiver Operating Characteristic (ROC) curve generated based on assuming a constant shape Bi-Weibull distribution is studied. In the context of ROC curve analysis, it is assumed that biomarker values from controls and cases follow some specific distribution and the accuracy is evaluated by using the ROC model developed from that specified distribution. This article assumes that the biomarker values from the two groups follow Weibull distributions with equal shape parameter and different scale parameters. The ROC model, area under the ROC curve (AUC), asymptotic and bootstrap confidence intervals for the AUC are derived. Theoretical results are validated by simulation …