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Articles 541 - 570 of 1091
Full-Text Articles in Statistical Theory
Type I Error Inflation Of The Separate-Variances Welch T Test With Very Small Sample Sizes When Assumptions Are Met, Albert K. Adusah, Gordon P. Brooks
Type I Error Inflation Of The Separate-Variances Welch T Test With Very Small Sample Sizes When Assumptions Are Met, Albert K. Adusah, Gordon P. Brooks
Journal of Modern Applied Statistical Methods
This Monte Carlo study shows that the separate-variances Welch t test has inflated Type I error rates at very small sample sizes, especially when sample sizes are very small in one group and larger in the second group – even when all assumptions for the statistical test are met.
One Is Not Enough: The Need For Multiple Respondents In Survey Research Of Organizations, Joseph L. Balloun, Hilton Barrett, Art Weinstein
One Is Not Enough: The Need For Multiple Respondents In Survey Research Of Organizations, Joseph L. Balloun, Hilton Barrett, Art Weinstein
Journal of Modern Applied Statistical Methods
The need for multiple respondents per organization in organizational survey research is supported. Leadership teams’ ratings of their implementations of market orientation are examined, along with learning orientation, entrepreneurial management, and organizational flexibility. Sixty diverse organizations, including not-for-profit organizations in education and healthcare as well as manufacturing and service businesses, were included. The major finding was the large rating variance within the leadership teams of each organization. The results are enlightening and have definite implications for improved design of survey research on organizations.
Is Next Twelve Months Period Tumor Recurrence Free Under Restricted Rate Due To Medication? A Probabilistic Warning, Ramalingam Shanmugam
Is Next Twelve Months Period Tumor Recurrence Free Under Restricted Rate Due To Medication? A Probabilistic Warning, Ramalingam Shanmugam
Journal of Modern Applied Statistical Methods
A methodology is formulated to analyze tumor recurrence data when its incidence rate is restricted due to medication. Analytic results are derived to make a probabilistic early warning of tumor recurrence free period of length τ; that is, the chance for a safe period of lengthτ is estimated. The captured data are length biased. Expressions are developed to extract and relate to counterparts of the non-length biased data. Three data sets are considered as illustrations: (1) patients who are given a placebo, (2) patients who are given the medicine pyridoxine and (3) patients who are given the medicine thiotepa.
The Likelihood Of Choosing The Borda-Winner With Partial Preference Rankings Of The Electorate, Ömer Eğecioğlu, Ayça Ebru Giritligil
The Likelihood Of Choosing The Borda-Winner With Partial Preference Rankings Of The Electorate, Ömer Eğecioğlu, Ayça Ebru Giritligil
Journal of Modern Applied Statistical Methods
Given that n voters report only the first r (1 ≤ r < m) ranks of their linear preference rankings over m alternatives, the likelihood of implementing Borda outcome is investigated. The information contained in the first r ranks is aggregated through a Borda-like method, namely the r-Borda rule. Monte-Carlo simulations are run to detect changes in the likelihood of r-Borda winner(s) to coincide with the original Borda winner(s) as a function of m, n and r. The voters’ preferences are generated through the Impartial Anonymous and Neutral Culture Model, where both the names of the …
An Exact Test For The Equality Of Intraclass Correlation Coefficients Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara
An Exact Test For The Equality Of Intraclass Correlation Coefficients Under Unequal Family Sizes, Madhusudan Bhandary, Koji Fujiwara
Journal of Modern Applied Statistical Methods
An exact test for the equality of two intraclass correlation coefficients under unequal family sizes based on two independent multi-normal samples is proposed. This exact test consistently and reliably produced results superior to those of the Likelihood Ratio Test (LRT) and the large sample Z-test proposed by Young and Bhandary (1998). The test generally performed better in terms of power (for higher intraclass correlation values) for various combinations of intraclass correlation coefficient values and the exact test remained closer to the significance level under the null hypothesis compared to the other two tests. For small sample situations, sizes of the …
Extension Of Grizzle’S Classic Crossover Design, James F. Reed Iii
Extension Of Grizzle’S Classic Crossover Design, James F. Reed Iii
Journal of Modern Applied Statistical Methods
The crossover design compares treatments A and B over two periods using sequences AB and BA (the AB|BA design) and is the classic design most often illustrated and critiqued in textbooks. Other crossover designs have been used but their use is relatively rare and not always well understood. This article introduces alternatives to a randomized two-treatment, two-period crossover study design. One strategy, which is to extend the classic AB|BA by adding a third period to repeat one of the two treatments, has several attractive advantages; an added treatment period may not imply a large additional cost but will allow carryover …
Double Acceptance Sampling Plans Based On Truncated Life Tests For Marshall-Olkin Extended Lomax Distribution, G. Srinivasa Rao
Double Acceptance Sampling Plans Based On Truncated Life Tests For Marshall-Olkin Extended Lomax Distribution, G. Srinivasa Rao
Journal of Modern Applied Statistical Methods
Double Acceptance Sampling Plans (DASP) is developed for a truncated life test when the lifetime of an item follows the Marshall-Olkin extended Lomax distribution. Probability of Acceptance (PA) is calculated for different consumer’s confidence levels fixing the producer’s risk at 0.05. Probability of acceptance and producer’s risk are illustrated with examples.
Estimation Of Population Mean In Successive Sampling By Sub-Sampling Non-Respondents, Housila P. Singh, Sunil Kumar, Sandeep Bhougal
Estimation Of Population Mean In Successive Sampling By Sub-Sampling Non-Respondents, Housila P. Singh, Sunil Kumar, Sandeep Bhougal
Journal of Modern Applied Statistical Methods
The estimation of the population mean in mail surveys is investigated in the context of sampling on two occasions where the population mean of the auxiliary variable is available in the presence of non-response only for the current occasion in two occasion successive sampling. The behavior of the proposed estimator is compared with the estimator for the same situation but in the absence of non-response. An empirical illustration demonstrates the performance of the proposed estimator.
Fisher’S Exact Test For Misclassified Data, Tze-San Lee
Fisher’S Exact Test For Misclassified Data, Tze-San Lee
Journal of Modern Applied Statistical Methods
Ecole Supérieure de Commerce de Tunis. Fisher’s exact test is adapted to handle the misclassified data arising from comparing two binomial populations. The bias-adjusted odds ratio is proposed to account for misclassification errors. Its expected power depends in a nonlinear way on the true sensitivity and specificity of the classification method. The data taken from the no conviction rate of criminality for two types of twin populations was used to illustrate how to calculate true sensitivity and specificity and the expected power of the adjusted odds ratio.
Improved Estimation Of The Population Mean Using Known Parameters Of An Auxiliary Variable, Rajesh Tailor, Balkishan Sharma
Improved Estimation Of The Population Mean Using Known Parameters Of An Auxiliary Variable, Rajesh Tailor, Balkishan Sharma
Journal of Modern Applied Statistical Methods
An improved ratio-cum-product type estimator of the finite population mean is proposed using known information on the coefficient of variation of an auxiliary variate and correlation coefficient between a study variate and an auxiliary variate. Realistic conditions are obtained under which the proposed estimator is more efficient than the simple mean estimator, usual ratio and product estimators and estimators proposed by Singh and Diwivedi (1981), Pandey and Dubey (1988), Upadhaya and Singh (1999), and Singh, et al., (2004). An empirical study supports theoretical findings.
Inference In Simple Regression For The Intercept Utilizing Prior Information On The Slope, Ayman Baklizi, Adil E. Yousif
Inference In Simple Regression For The Intercept Utilizing Prior Information On The Slope, Ayman Baklizi, Adil E. Yousif
Journal of Modern Applied Statistical Methods
Shrinkage type estimators are developed for the intercept parameter of a simple linear regression model and the case when it is suspected a priori that the slope parameter is equal to some specific value is considered. Three different estimators of the intercept parameters are examined. The relative performances of the estimators are investigated based on a simulation study of the biases and mean squared errors. The associated bootstrap confidence intervals are also studied and their performance is evaluated.
Factors Influencing The Mixture Index Of Model Fit In Contingency Tables Showing Independence, Xuemei Pan, C. Mitchell Dayton
Factors Influencing The Mixture Index Of Model Fit In Contingency Tables Showing Independence, Xuemei Pan, C. Mitchell Dayton
Journal of Modern Applied Statistical Methods
Several competing computational techniques for dealing with sampling zeros were evaluated when estimating the two-point mixture model index, π* , in contingency tables under an independence assumption. Also, the performance of the estimate and associated standard errors were studied under various combinations of conditions.
Bayesian Regression Analysis With Examples In S-Plus And R, Sheikh P. Ahmad, A. A. Khan, A. Ahmed
Bayesian Regression Analysis With Examples In S-Plus And R, Sheikh P. Ahmad, A. A. Khan, A. Ahmed
Journal of Modern Applied Statistical Methods
An extended version of normal theory Bayesian regression models, including extreme-value, logistic and normal regression models is examined. Methods proposed are illustrated numerically; the regression coefficient of pH on electrical conductivity (EC) of soil data is analyzed using both S-PLUS and R software.
Bayesian Threshold Moving Average Models, Mahmoud M. Smadi, M. T. Alodat
Bayesian Threshold Moving Average Models, Mahmoud M. Smadi, M. T. Alodat
Journal of Modern Applied Statistical Methods
A Bayesian approach in threshold moving average model for time series with two regimes is provided. The posterior distribution of the delay and threshold parameters are used to examine and investigate the intrinsic characteristics of this nonlinear time series model. The proposed approach is applied to both simulated data and a real data set obtained from a chemical system. Key words: Threshold time series, moving average model, Bayesian
A Robust One-Sided Variability Control Chart, P. Borysov, Ping Sa
A Robust One-Sided Variability Control Chart, P. Borysov, Ping Sa
Journal of Modern Applied Statistical Methods
A new control charting technique to monitor the variability of any distribution is proposed. The simulation study shows that the new method outperforms all the existing methods in controlling the Type I error rates and it also has good power performance for all distributions considered in the study.
A Test That Combines Frequency And Quantitative Information, Norman Cliff
A Test That Combines Frequency And Quantitative Information, Norman Cliff
Journal of Modern Applied Statistical Methods
In many simple designs, observed frequencies in subclasses defined by a qualitative variable are compared to the frequencies expected on the basis of population proportions, design parameters or models. Often there is a quantitative variable which may be affected in the same way as the frequencies. Its differences among the groups may also be analyzed. A simple test is described that combines the effects on the frequencies and on the quantitative variable based on comparing the sums of the values for the quantitative value within each group to the random expectation. The sampling variance of the difference is derived and …
Comparing The Strength Of Association Of Two Predictors Via Smoothers Or Robust Regression Estimators, Rand R. Wilcox
Comparing The Strength Of Association Of Two Predictors Via Smoothers Or Robust Regression Estimators, Rand R. Wilcox
Journal of Modern Applied Statistical Methods
Consider three random variables, Y , X1 and X2, having some unknown trivariate distribution and let n2j (j = 1, 2) be some measure of the strength of association between Y and Xj. When n2j is taken to be Pearson’s correlation numerous methods for testing Ho : n21 = n22 have been proposed. However, Pearson’s correlation is not robust and the methods for testing H0 are not level robust in general. This article examines methods for testing H0 based on a robust fit. The …
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.
New Perspectives In Applying The Regression-Discontinuity Design For Program Evaluation: A Simulation Analysis, Sally A. Lesik
New Perspectives In Applying The Regression-Discontinuity Design For Program Evaluation: A Simulation Analysis, Sally A. Lesik
Journal of Modern Applied Statistical Methods
Evaluating educational programs is a core component of assessment. One challenge occurs because participants often enter into programs with diverse skills and backgrounds. The regression-discontinuity design has been used to evaluate programs amongst a diverse group, but noncompliance is a limitation. A simulation analysis illustrates the impact of noncompliance.
Information Technology For Increasing Qualitative Information Processing Efficiency, S. N. Martyshenko, E. A. Egorov
Information Technology For Increasing Qualitative Information Processing Efficiency, S. N. Martyshenko, E. A. Egorov
Journal of Modern Applied Statistical Methods
The problem of qualitative information processing in questionnaires is considered and a solution for this problem is offered. The computer technology developed by the authors to automate the offered decision is described.
General Piecewise Growth Mixture Model: Word Recognition Development For Different Learners In Different Phases, Amery D. Wu, Bruno D. Zumbo, Linda S. Siegel
General Piecewise Growth Mixture Model: Word Recognition Development For Different Learners In Different Phases, Amery D. Wu, Bruno D. Zumbo, Linda S. Siegel
Journal of Modern Applied Statistical Methods
The General Piecewise Growth Mixture Model (GPGMM), without losing generality to other fields of study, can answer six crucial research questions regarding children’s word recognition development. Using child word recognition data as an example, this study demonstrates the flexibility and versatility of the GPGMM in investigating growth trajectories that are potentially phasic and heterogeneous. The strengths and limitations of the GPGMM and lessons learned from this hands-on experience are discussed.
A Simulation Study Of The Relative Efficiency Of The Minimized Integrated Square Error Estimator (L2e) For Phase I Control Charting, John N. Dyer
Journal of Modern Applied Statistical Methods
Parameter estimates used in control charting, the sample mean and variance, are based on maximum likelihood estimation (MLE). Unfortunately, MLEs are not robust to contaminated data and can lead to improper conclusions regarding parameter values. This article proposes a more robust estimation technique; the minimized integrated square error estimator (L2E).
Maximum Likelihood Solution For The Linear Structural Relationship With Three Parameters Known, Androulla Michaeloudis
Maximum Likelihood Solution For The Linear Structural Relationship With Three Parameters Known, Androulla Michaeloudis
Journal of Modern Applied Statistical Methods
A maximum likelihood solution is obtained for the simple linear structural relation model where the underlying incidental distribution and one error variance are assumed known. Expressions for the asymptotic standard errors of the maximum likelihood estimates are obtained and these are verified using a simulation study.
Logistic Regression Models For Higher Order Transition Probabilities Of Markov Chain For Analyzing The Occurrences Of Daily Rainfall Data, Narayan Chanra Sinha, M. Ataharul Islam, Kazi Saleh Ahamed
Logistic Regression Models For Higher Order Transition Probabilities Of Markov Chain For Analyzing The Occurrences Of Daily Rainfall Data, Narayan Chanra Sinha, M. Ataharul Islam, Kazi Saleh Ahamed
Journal of Modern Applied Statistical Methods
Logistic regression models for transition probabilities of higher order Markov models are developed for the sequence of chain dependent repeated observations. To identify the significance of these models and their parameters a test procedure for a likelihood ratio criterion is developed. A method of model selection is suggested on the basis of AIC and BIC procedures. The proposed models and test procedures are applied to analyze the occurrences of daily rainfall data for selected stations in Bangladesh. Based on results from these models, the transition probabilities of first order Markov model for temperature and humidity provided the most suitable option …
Number Of Replications Required In Monte Carlo Simulation Studies: A Synthesis Of Four Studies, Daniel J. Mundform, Jay Schaffer, Myoung-Jin Kim, Dale Shaw, Ampai Thongteeraparp, Pornsin Supawan
Number Of Replications Required In Monte Carlo Simulation Studies: A Synthesis Of Four Studies, Daniel J. Mundform, Jay Schaffer, Myoung-Jin Kim, Dale Shaw, Ampai Thongteeraparp, Pornsin Supawan
Journal of Modern Applied Statistical Methods
Monte Carlo simulations are used extensively to study the performance of statistical tests and control charts. Researchers have used various numbers of replications, but rarely provide justification for their choice. Currently, no empirically-based recommendations regarding the required number of replications exist. Twenty-two studies were re-analyzed to determine empirically-based recommendations.
Matched-Pair Studies With Misclassified Ordinal Data, Tze-San Lee
Matched-Pair Studies With Misclassified Ordinal Data, Tze-San Lee
Journal of Modern Applied Statistical Methods
The problem of matched-pair studies with misclassified ordinal data is considered. Misclassification is assumed to occur only between the adjacent columns/rows. Bias-adjusted generalized odds ratio and a test for marginal homogeneity are presented to account for misclassification bias. Data from lambing records of 227 Merino ewes are used to illustrate how to calculate these bias-adjusted estimators and – because validation data are not available – a sensitivity analysis is conducted.
A Robust Root Mean Square Standardized Effect Size In One-Way Fixed-Effects Anova, Guili Zhang, James Algina
A Robust Root Mean Square Standardized Effect Size In One-Way Fixed-Effects Anova, Guili Zhang, James Algina
Journal of Modern Applied Statistical Methods
A robust Root Mean Square Standardized Effect Size (RMSSER) was developed to address the unsatisfactory performance of the Root Mean Square Standardized Effect Size. The coverage performances of the confidence intervals (CI) for RMSSER were investigated. The coverage probabilities of the non-central F distribution-based CI for RMSSER were adequate.
The Overall F-Tests For Seasonal Unit Roots Under Nonstationary Alternatives: Some Theoretical Results And A Monte Carlo Investigation, Ghassen El Montasser
The Overall F-Tests For Seasonal Unit Roots Under Nonstationary Alternatives: Some Theoretical Results And A Monte Carlo Investigation, Ghassen El Montasser
Journal of Modern Applied Statistical Methods
In many empirical studies concerning seasonal time series, it has been shown that the whole set of unit roots associated with seasonal random walks are not present. This article focuses on the overall F-tests for seasonal unit roots under some nonstationary alternatives different from the seasonal random walk. The asymptotic theory of these tests is established for these cases using a new approach based on circulant matrix concepts. The simulation results joined to this theoretic analysis showed that the overall F-tests, as well as their augmented versions, maintained high power against the nonstationary alternatives.
Weighting Large Datasets With Complex Sampling Designs: Choosing The Appropriate Variance Estimation Method, Sara Mann, James Chowhan
Weighting Large Datasets With Complex Sampling Designs: Choosing The Appropriate Variance Estimation Method, Sara Mann, James Chowhan
Journal of Modern Applied Statistical Methods
Using the Canadian Workplace and Employee Survey (WES), three variance estimation methods for weighting large datasets with complex sampling designs are compared: simple final weighting, standard bootstrapping and mean bootstrapping. Using a logit analysis, it is shown - depending on which weighting method is used - different predictor variables are significant. The potential lack of independence inherent in a multi-stage cluster sample design, as in the WES, results in a downward bias in the variance when conducting statistical inference (using the simple final weight), which in turn results in increased Type I errors. Bootstrap methods can account for the survey’s …
Using Finite Mixture Modeling To Deal With Systematic Measurement Error: A Case Study, Min Liu, Gregory R. Hancock, Jeffrey R. Harring
Using Finite Mixture Modeling To Deal With Systematic Measurement Error: A Case Study, Min Liu, Gregory R. Hancock, Jeffrey R. Harring
Journal of Modern Applied Statistical Methods
Conventional methods and analyses view measurement error as random. A scenario is presented where a variable was measured with systematic error. Mixture models with systematic parameter constraints were used to test hypotheses in the context of general linear models; this accommodated the heterogeneity arising due to systematic measurement error.