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Articles 1 - 12 of 12
Full-Text Articles in Physical Sciences and Mathematics
On The Authentic Notion, Relevance, And Solution Of The Jeffreys-Lindley Paradox In The Zettabyte Era, Miodrag M. Lovric
On The Authentic Notion, Relevance, And Solution Of The Jeffreys-Lindley Paradox In The Zettabyte Era, Miodrag M. Lovric
Journal of Modern Applied Statistical Methods
The Jeffreys-Lindley paradox is the most quoted divergence between the frequentist and Bayesian approaches to statistical inference. It is embedded in the very foundations of statistics and divides frequentist and Bayesian inference in an irreconcilable way. This paradox is the Gordian Knot of statistical inference and Data Science in the Zettabyte Era. If statistical science is ready for revolution confronted by the challenges of massive data sets analysis, the first step is to finally solve this anomaly. For more than sixty years, the Jeffreys-Lindley paradox has been under active discussion and debate. Many solutions have been proposed, none entirely satisfactory. …
Jmasm 49: A Compilation Of Some Popular Goodness Of Fit Tests For Normal Distribution: Their Algorithms And Matlab Codes (Matlab), Metin Öner, İpek Deveci Kocakoç
Jmasm 49: A Compilation Of Some Popular Goodness Of Fit Tests For Normal Distribution: Their Algorithms And Matlab Codes (Matlab), Metin Öner, İpek Deveci Kocakoç
Journal of Modern Applied Statistical Methods
The main purpose of this study is to review calculation algorithms for some of the most common non-parametric and omnibus tests for normality, and to provide them as a compiled MATLAB function. All tests are coded to provide p-values for those normality tests, and the proposed function gives the results as an output table.
The Bayes Factor For Case-Control Studies With Misclassified Data, Tzesan Lee
The Bayes Factor For Case-Control Studies With Misclassified Data, Tzesan Lee
Journal of Modern Applied Statistical Methods
The question of how to test if collected data for a case-control study are misclassified was investigated. A mixed approach was employed to calculate the Bayes factor to assess the validity of the null hypothesis of no-misclassification. A real-world data set on the association between lung cancer and smoking status was used as an example to illustrate the proposed method.
P-Values Versus Significance Levels, Phillip I. Good
P-Values Versus Significance Levels, Phillip I. Good
Journal of Modern Applied Statistical Methods
In this article Phillip Good responds to Richard Anderson's article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.
Randomization Test P-Values Versus Significance Levels, Bryan Manly
Randomization Test P-Values Versus Significance Levels, Bryan Manly
Journal of Modern Applied Statistical Methods
Bryan Manly responds to Richard Anderson's article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.
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
Comparison Of Several Tests For Combining Several Independent Tests, Madhusudan Bhandary, Xuan Zhang
Comparison Of Several Tests For Combining Several Independent Tests, Madhusudan Bhandary, Xuan Zhang
Journal of Modern Applied Statistical Methods
Several tests for combining p-values from independent tests have been considered to address a particular common testing problem. A simulation study shows that Fisher’s (1932) Inverse Chi-square test is optimal based on a power comparison of several different tests.
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.
An Equivalence Test Based On N And P, Markus Neuhäeuser
An Equivalence Test Based On N And P, Markus Neuhäeuser
Journal of Modern Applied Statistical Methods
An equivalence test is proposed which is based on the P-value of a test for a difference and the sample size. This test may be especially appropriate for an exploratory re-analysis if only a non-significant test for a difference was reported. Thus, neither a confidence interval is available, nor is there access to the raw data. The test is illustrated using two examples; for both applications the smallest equivalence range for which equivalence could be demonstrated is calculated.
Inference For P(Y, Vee Ming Ng
Inference For P(Y, Vee Ming Ng
Journal of Modern Applied Statistical Methods
Some tests and confidence bounds for the reliability parameter R=P(Y
Jmasm20: Exact Permutation Critical Values For The Kruskal-Wallis One-Way Anova, Justice I. Odiase, Sunday M. Ogbonmwan
Jmasm20: Exact Permutation Critical Values For The Kruskal-Wallis One-Way Anova, Justice I. Odiase, Sunday M. Ogbonmwan
Journal of Modern Applied Statistical Methods
The exhaustive enumeration of all the permutations of the observations in an experiment is the only possible way of truly constructing exact tests of significance. The permutation paradigm requires no distributional assumptions and works well with values that are normal, almost normal and non-normally distributed. The Kruskal-Wallis test does not require the assumptions that the samples are from normal populations and that the samples have the same standard deviation. In this article, the exact permutation distribution of the Kruskal-Wallis test statistic is generated empirically by actually obtaining all the distinct permutations of an experiment. The tables of exact critical values …
An Algorithm For Generating Unconditional Exact Permutation Distribution For A Two-Sample Experiment, Justice I. Odiase, Sunday M. Ogbonmwan
An Algorithm For Generating Unconditional Exact Permutation Distribution For A Two-Sample Experiment, Justice I. Odiase, Sunday M. Ogbonmwan
Journal of Modern Applied Statistical Methods
An Algorithm that generates the unconditional exact permutation distribution of a 2 x n experiment is presented. The algorithm is able to handle ranks as well as actual observations. It makes it possible to obtain exact p-values for several statistics, especially when sample sizes are small and the application of large sample approximation is unreliable. An illustrative implementation is achieved and leads to the computation of exact p-values for the Mood test when the sample size is small.