Results 11 to 20 of about 20,253,687 (309)

A Simulation-Based Scaled Test Statistic for Assessing Model-Data Fit in Least-Squares Unrestricted Factor-Analysis Solutions

open access: yesMethodology, 2023
A shortcoming of least-squares unrestricted factor analysis (UFA) procedures, which are widely used in psychometric applications is that a test statistic for assessing model-data fit cannot be easily derived from the minimum fit function value.
Urbano Lorenzo-Seva, Pere J. Ferrando
doaj   +2 more sources

A groupwise association test for rare mutations using a weighted sum statistic. [PDF]

open access: yesPLoS Genetics, 2009
Resequencing is an emerging tool for identification of rare disease-associated mutations. Rare mutations are difficult to tag with SNP genotyping, as genotyping studies are designed to detect common variants.
Bo Eskerod Madsen, Sharon R Browning
doaj   +2 more sources

Robust Test Statistic for Cooperative Spectrum Sensing Based on the Gerschgorin Circle Theorem

open access: yesIEEE Access, 2018
The Gerschgorin circle theorem was recently applied to build two detectors for the purpose of spectrum sensing in cognitive radio applications, the so-called Gerschgorin radius-based and the Gerschgorin disk-based detectors.
Dayan Adionel Guimaraes
doaj   +2 more sources

Extending multivariate distance matrix regression with an effect size measure and the asymptotic null distribution of the test statistic. [PDF]

open access: yesPsychometrika, 2017
Person-centered methods are useful for studying individual differences in terms of (dis)similarities between response profiles on multivariate outcomes.
McArtor DB, Lubke GH, Bergeman CS.
europepmc   +2 more sources

Evaluating Structural Equation Models for Categorical Outcomes: A New Test Statistic and a Practical Challenge of Interpretation. [PDF]

open access: yesMultivariate Behav Res, 2015
This research is concerned with two topics in assessing model fit for categorical data analysis. The first topic involves the application of a limited-information overall test, introduced in the item response theory literature, to structural equation ...
Monroe S, Cai L.
europepmc   +2 more sources

Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic. [PDF]

open access: yesPsychometrika, 2010
A scaled difference test statistic $\tilde{T}{}_{d}$ that can be computed from standard software of structural equation models (SEM) by hand calculations was proposed in Satorra and Bentler (Psychometrika 66:507–514, 2001). The statistic $\tilde{T}_{d}
Satorra A, Bentler PM.
europepmc   +2 more sources

EVALUATION OF A NEW MEAN SCALED AND MOMENT ADJUSTED TEST STATISTIC FOR SEM. [PDF]

open access: yesStruct Equ Modeling, 2013
Recently a new mean scaled and skewness adjusted test statistic was developed for evaluating structural equation models in small samples and with potentially nonnormal data, but this statistic has received only limited evaluation. The performance of this
Tong X, Bentler PM.
europepmc   +2 more sources

A Modified Chi-square Type Test Statistic for the Double Burr X Model with Applications to Right Censored Medical and Reliability Data

open access: yesPakistan Journal of Statistics and Operation Research, 2021
A new modified version of the Bagdonavičius-Nikulin goodness-of-fit test statistic is presented for validity for the right censor case under the double Burr type X distribution.
K. Aidi   +5 more
semanticscholar   +1 more source

The Derivation and Choice of Appropriate Test Statistic (Z, t, F and Chi-Square Test) in Research Methodology

open access: yesMathematics Letters, 2020
The main objective of this paper is to choose an appropriate test statistic for research methodology. Specifically, this article tries to explore the concept of statistical hypothesis test, derivation of the test statistic and its role on research ...
T. Abebe
semanticscholar   +1 more source

Verification, Testing and Statistics [PDF]

open access: yes, 2009
Though formal verification has been the holy grail of software validation, practical applications of verification run into two major challenges. The first challenge is in writing detailed specifications, and the second challenge is in scaling verification algorithms to large software.
Aditya V. Nori, Sriram K. Rajamani
openaire   +2 more sources

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