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Full-Text Articles in Physical Sciences and Mathematics
Generalized Ratio-Cum-Product Estimator For Finite Population Mean Under Two-Phase Sampling Scheme, Gajendra Kumar Vishwakarma, Sayed Mohammed Zeeshan
Generalized Ratio-Cum-Product Estimator For Finite Population Mean Under Two-Phase Sampling Scheme, Gajendra Kumar Vishwakarma, Sayed Mohammed Zeeshan
Journal of Modern Applied Statistical Methods
A method to lower the MSE of a proposed estimator relative to the MSE of the linear regression estimator under two-phase sampling scheme is developed. Estimators are developed to estimate the mean of the variate under study with the help of auxiliary variate (which are unknown but it can be accessed conveniently and economically). The mean square errors equations are obtained for the proposed estimators. In addition, optimal sample sizes are obtained under the given cost function. The comparison study has been done to set up conditions for which developed estimators are more effective than other estimators with novelty. The …
A New Exponential Approach For Reducing The Mean Squared Errors Of The Estimators Of Population Mean Using Conventional And Non-Conventional Location Parameters, Housila P. Singh, Anita Yadav
A New Exponential Approach For Reducing The Mean Squared Errors Of The Estimators Of Population Mean Using Conventional And Non-Conventional Location Parameters, Housila P. Singh, Anita Yadav
Journal of Modern Applied Statistical Methods
Classes of ratio-type estimators t (say) and ratio-type exponential estimators te (say) of the population mean are proposed, and their biases and mean squared errors under large sample approximation are presented. It is the class of ratio-type exponential estimators te provides estimators more efficient than the ratio-type estimators.
The Importance Of Type I Error Rates When Studying Bias In Monte Carlo Studies In Statistics, Michael Harwell
The Importance Of Type I Error Rates When Studying Bias In Monte Carlo Studies In Statistics, Michael Harwell
Journal of Modern Applied Statistical Methods
Two common outcomes of Monte Carlo studies in statistics are bias and Type I error rate. Several versions of bias statistics exist but all employ arbitrary cutoffs for deciding when bias is ignorable or non-ignorable. This article argues Type I error rates should be used when assessing bias.
Efficient Class Of Estimators For Finite Population Mean Using Auxiliary Information In Two-Occasion Successive Sampling, G. N. Singh, Mohd Khalid
Efficient Class Of Estimators For Finite Population Mean Using Auxiliary Information In Two-Occasion Successive Sampling, G. N. Singh, Mohd Khalid
Journal of Modern Applied Statistical Methods
In the case of sampling on two occasions, a class of estimators is considered which uses information on the first occasion as well as the second occasion in order to estimate the population means on the current (second) occasion. The usefulness of auxiliary information in enhancing the efficiency of this estimation is examined through the class of proposed estimators. Some properties of the class of estimators and a strategy of optimum replacement are discussed. The proposed class of estimators were empirically compared with the sample mean estimator in the case of no matching. The established optimum estimator, which is a …
A Strategy For Using Bias And Rmse As Outcomes In Monte Carlo Studies In Statistics, Michael Harwell
A Strategy For Using Bias And Rmse As Outcomes In Monte Carlo Studies In Statistics, Michael Harwell
Journal of Modern Applied Statistical Methods
To help ensure important patterns of bias and accuracy are detected in Monte Carlo studies in statistics this paper proposes conditioning bias and root mean square error (RMSE) measures on estimated Type I and Type II error rates. A small Monte Carlo study is used to illustrate this argument.
Effective Estimation Strategy Of Finite Population Variance Using Multi-Auxiliary Variables In Double Sampling, Reba Maji, G. N. Singh, Arnab Bandyopadhyay
Effective Estimation Strategy Of Finite Population Variance Using Multi-Auxiliary Variables In Double Sampling, Reba Maji, G. N. Singh, Arnab Bandyopadhyay
Journal of Modern Applied Statistical Methods
Estimation of population variance in two-phase (double) sampling is considered using information on multiple auxiliary variables. An unbiased estimator is proposed and its properties are studied under two different structures. The superiority of the suggested estimator over some contemporary estimators of population variance was established through empirical studies from a natural and an artificially generated dataset.
Efficient And Unbiased Estimation Procedure Of Population Mean In Two-Phase Sampling, Reba Maji, Arnab Bandyopadhyay, G. N. Singh
Efficient And Unbiased Estimation Procedure Of Population Mean In Two-Phase Sampling, Reba Maji, Arnab Bandyopadhyay, G. N. Singh
Journal of Modern Applied Statistical Methods
In this paper, an unbiased regression-ratio type estimator has been developed for estimating the population mean using two auxiliary variables in double sampling. Its properties are studied under two different cases. Empirical studies and graphical simulation have been done to demonstrate the efficiency of the proposed estimator over other estimators.
An Improved Generalized Estimation Procedure Of Current Population Mean In Two-Occasion Successive Sampling, G. N. Singh, Alok Kumar Singh, Anup Kumar Sharma
An Improved Generalized Estimation Procedure Of Current Population Mean In Two-Occasion Successive Sampling, G. N. Singh, Alok Kumar Singh, Anup Kumar Sharma
Journal of Modern Applied Statistical Methods
The present work is an attempt to make use of several auxiliary variables on both occasions for improving the precision of estimates for the current population mean in two-occasion successive sampling. A generalized exponential-cum-regression type estimator of the current population mean is proposed and its optimum replacement strategy has been discussed. Empirical studies are carried out to show the dominance of the proposed estimation procedure over the sample mean estimator and natural successive sampling estimator. Empirical results have been interpreted and suitable recommendations are put forward to survey practitioners.
Almost Unbiased Estimator Using Known Value Of Population Parameter(S) In Sample Surveys, Rajesh Singh, S.B. Gupta, Sachin Malik
Almost Unbiased Estimator Using Known Value Of Population Parameter(S) In Sample Surveys, Rajesh Singh, S.B. Gupta, Sachin Malik
Journal of Modern Applied Statistical Methods
An almost unbiased estimator using known value of some population parameter(s) is proposed. A class of estimators is defined which includes Singh and Solanki (2012) and Sahai and Ray (1980), Sisodiya and Dwivedi (1981), Singh, Cauhan, Sawan, and Smarandache (2007), Upadhyaya and Singh (1984), Singh and Tailor (2003) estimators. Under simple random sampling without replacement (SRSWOR) scheme the expressions for bias and mean square error (MSE) are derived. Numerical illustrations are given.
A Comparison Of Semi-Parametric And Nonparametric Methods For Estimating Mean Time To Event For Randomly Left Censored Data, Farzana Chowdhury, Jahida Gulshan, Syed Shahadat Hossain
A Comparison Of Semi-Parametric And Nonparametric Methods For Estimating Mean Time To Event For Randomly Left Censored Data, Farzana Chowdhury, Jahida Gulshan, Syed Shahadat Hossain
Journal of Modern Applied Statistical Methods
The aim of this study was to make a comparison among existing estimation methods (Kaplan-Meier, Nelson-Aalen and Regression on Ordered Statistics (ROS)) for randomly left censored time to event data under selected distributions and for different level of censoring and sample sizes in order to determine the strength of these methods based on simulated data. Comparisons among the methods are made on the basis of unbiasedness and Monte Carlo Standard Error of the summary statistics (mean time to event) obtained by those methods under different conditions.
Estimation Of Gumbel Parameters Under Ranked Set Sampling, Omar M. Yousef, Sameer A. Al-Subh
Estimation Of Gumbel Parameters Under Ranked Set Sampling, Omar M. Yousef, Sameer A. Al-Subh
Journal of Modern Applied Statistical Methods
Consider the MLEs (maximum likelihood estimators) of the parameters of the Gumbel distribution using SRS (simple random sample) and RSS (ranked set sample) and the MOMEs (method of moment estimators) and REGs (regression estimators) based on SRS. A comparison between these estimators using bias and MSE (mean square error) was performed using simulation. It appears that the MLE based on RSS can be a robust competitor to the MLE based on SRS.
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 …
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.
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.
Estimation Of Variance Using Known Coefficient Of Variation And Median Of An Auxiliary Variable, J. Subramani, G. Kumarapandiyan
Estimation Of Variance Using Known Coefficient Of Variation And Median Of An Auxiliary Variable, J. Subramani, G. Kumarapandiyan
Journal of Modern Applied Statistical Methods
A modified ratio type variance estimator for estimating population variance of a study variable when the population median and coefficient of variation of an auxiliary variable are known is proposed. The bias and mean squared error of the proposed estimator are derived and conditions under which the proposed estimator performs better than the traditional ratio type variance estimators and modified ratio type variance estimators are obtained. Using a numerical study results show that the proposed estimator performs better than the traditional ratio type variance estimator and existing modified ratio type variance estimators.
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.
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.
Ratio Type Estimator Of Ratio Of Two Population Means In Stratified Random Sampling, Rajesh Tailor, Sunil Chouhan
Ratio Type Estimator Of Ratio Of Two Population Means In Stratified Random Sampling, Rajesh Tailor, Sunil Chouhan
Journal of Modern Applied Statistical Methods
A ratio estimator is proposed for the ratio of two population means using auxiliary information in stratified random sampling. Bias and mean squared error expressions are obtained under large sample approximation, and the proposed estimator is compared both theoretically and empirically with the conventional estimator of ratio for two population means in stratified random sampling.
Modified Ratio And Product Estimators For Population Mean In Systematic Sampling, Housila P. Singh, Rajesh Tailor, Narendra Kumar Jatwa
Modified Ratio And Product Estimators For Population Mean In Systematic Sampling, Housila P. Singh, Rajesh Tailor, Narendra Kumar Jatwa
Journal of Modern Applied Statistical Methods
The estimation of population mean in systematic sampling is explored. Properties of a ratio and product estimator that have been suggested in systematic sampling are investigated, along with the properties of double sampling. Following Swain (1964), the cost aspect is also discussed.
Discriminant Analysis For Repeated Measures Data: Effects Of Mean And Covariance Misspecification On Bias And Error In Discriminant Function Coefficients, Tolulope T. Sajobi, Lisa M. Lix, Longhai Li, William Laverty
Discriminant Analysis For Repeated Measures Data: Effects Of Mean And Covariance Misspecification On Bias And Error In Discriminant Function Coefficients, Tolulope T. Sajobi, Lisa M. Lix, Longhai Li, William Laverty
Journal of Modern Applied Statistical Methods
Discriminant analysis (DA) procedures based on parsimonious mean and/or covariance structures have been proposed for repeated measures (RM) data. Bias and means square error of discriminant function coefficients (DFCs) for DA procedures are investigated when the mean and/or covariance structures are correctly specified and misspecified.
Bias In Monte Carlo Simulations Due To Pseudo-Random Number Generator Initial Seed Selection, Jack C. Hill, Shlomo S. Sawilowsky
Bias In Monte Carlo Simulations Due To Pseudo-Random Number Generator Initial Seed Selection, Jack C. Hill, Shlomo S. Sawilowsky
Journal of Modern Applied Statistical Methods
Pseudo-random number generators can bias Monte Carlo simulations of the standard normal probability distribution function with initial seeds selection. Five generator designs were initial-seeded with values from 10000HEX to 1FFFFHEX, estimates of the mean were calculated for each seed, the distribution of mean estimates was determined for each generator and simulation histories were graphed for selected seeds.
Effect Of Measurement Errors On The Separate And Combined Ratio And Product Estimators In Stratified Random Sampling, Housila P. Singh, Namrata Karpe
Effect Of Measurement Errors On The Separate And Combined Ratio And Product Estimators In Stratified Random Sampling, Housila P. Singh, Namrata Karpe
Journal of Modern Applied Statistical Methods
Separate and combined ratio, product and difference estimators are introduced for population mean μY of a study variable Y using auxiliary variable X in stratified sampling when the observations are contaminated with measurement errors. The bias and mean squared error of the proposed estimators have been derived under large sample approximation and their properties are analyzed. Generalized versions of these estimators are given along with their properties.
A Randomization Method To Control The Type I Error Rates In Best Subset Regression, Yasser A. Shehata, Paul White
A Randomization Method To Control The Type I Error Rates In Best Subset Regression, Yasser A. Shehata, Paul White
Journal of Modern Applied Statistical Methods
A randomization method for the assessment of statistical significance for best subsets regression is given. The procedure takes into account the number of potential predictors and the inter-dependence between predictors. The approach corrects a non-trivial problem with Type I errors and can be used to assess individual variable significance.
Utility Of Weights For Weighted Kappa As A Measure Of Interrater Agreement On Ordinal Scale, Moonseong Heo
Utility Of Weights For Weighted Kappa As A Measure Of Interrater Agreement On Ordinal Scale, Moonseong Heo
Journal of Modern Applied Statistical Methods
Kappa statistics, unweighted or weighted, are widely used for assessing interrater agreement. The weights of the weighted kappa statistics in particular are defined in terms of absolute and squared distances in ratings between raters. It is proposed that those weights can be used for assessment of interrater agreements. A closed form expectations and variances of the agreement statistics referred to as AI1 and AI2, functions of absolute and squared distances in ratings between two raters, respectively, are obtained. AI1 and AI2 are compared with the weighted and unweighted kappa statistics in …
Using Exploratory Factor Analysis For Locating Invariant Referents In Factor Invariance Studies, W. Holmes Finch, Brian F. French
Using Exploratory Factor Analysis For Locating Invariant Referents In Factor Invariance Studies, W. Holmes Finch, Brian F. French
Journal of Modern Applied Statistical Methods
Model identification in multi-group confirmatory factor analysis (MCFA) requires an equality constraint of referent variables across groups. Invariance assumption violations make it difficult to locate parameters that actually differ. Suggested procedures for locating invariant referents are cumbersome, complex, and provide imperfect results. Exploratory factor analysis (EFA) may be an alternative because of its ease of use, yet empirical evaluation of its effectiveness is lacking. EFAs accuracy for distinguishing invariant from non-invariant referents was examined.
Applications Of Some Improved Estimators In Linear Regression, B. M. Golam Kibria
Applications Of Some Improved Estimators In Linear Regression, B. M. Golam Kibria
Journal of Modern Applied Statistical Methods
The problem of estimation of the regression coefficients under multicollinearity situation for the restricted linear model is discussed. Some improve estimators are considered, including the unrestricted ridge regression estimator (URRE), restricted ridge regression estimator (RRRE), shrinkage restricted ridge regression estimator (SRRRE), preliminary test ridge regression estimator (PTRRE), and restricted Liu estimator (RLIUE). The were compared based on the sampling variance-covariance criterion. The RRRE dominates other ridge estimators when the restriction does or does not hold. A numerical example was provided. The RRRE performed equivalently or better than the RLIUE in the sense of having smaller sampling variance.
Not All Effects Are Created Equal: A Rejoinder To Sawilowsky, J. Kyle Roberts, Robin K. Henson
Not All Effects Are Created Equal: A Rejoinder To Sawilowsky, J. Kyle Roberts, Robin K. Henson
Journal of Modern Applied Statistical Methods
In the continuing debate over the use and utility of effect sizes, more discussion often helps to both clarify and syncretize methodological views. Here, further defense is given of Roberts & Henson (2002) in terms of measuring bias in Cohen’s d, and a rejoinder to Sawilowsky (2003) is presented.
Exploration Of Distributions Of Ratio Of Partial Sum Of Sample Eigenvalues When All Population Eigenvalues Are The Same, Moonseong Heo
Exploration Of Distributions Of Ratio Of Partial Sum Of Sample Eigenvalues When All Population Eigenvalues Are The Same, Moonseong Heo
Journal of Modern Applied Statistical Methods
This paper explores empirically the first two moments of ratio of the partial sum of the first two sample eigenvalues to the sum of all eigenvalues when the population eigenvalues of a covariance matrix are all the same. Estimation of the first two moments can be practically crucial in assessing non-randomness of observed patterns on planar graphical displays based on lower rank approximations of data matrices. For derivation of the moments, exact and large sample asymptotic distributions of the sample ratios are reviewed but neither can be applicable to derivation of the moments. Therefore, I rely on simulations, where data …