Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

314
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and...
314
Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

293
Friedman's Two-Way Analysis of Variance by Ranks is a nonparametric test designed to identify differences across multiple test attempts when traditional assumptions of normality and equal variances do not apply. Unlike conventional ANOVA, which requires normally distributed data with equal variances, Friedman's test is ideal for ordinal or non-normally distributed data, making it particularly useful for analyzing dependent samples, such as matched subjects over time or repeated measures...
293
Test for Homogeneity01:23

Test for Homogeneity

2.1K
The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can...
2.1K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

2.6K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
2.6K
The Mantel-Cox Log-Rank Test01:19

The Mantel-Cox Log-Rank Test

534
The Mantel-Cox log-rank test is a widely used statistical method for comparing the survival distributions of two groups. It tests whether a statistically significant difference exists in survival times between the groups without assuming a specific distribution for the survival data, making it a non-parametric test. This flexibility makes the log-rank test particularly valuable in medical research and other fields where the timing of an event, such as death or disease recurrence, is of...
534
Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test01:09

Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test

1.8K
In parametric statistics, two fundamental tests stand out for their utility and wide application: the Student's t-test and goodness-of-fit tests. These tests provide researchers with a robust method for drawing insights from data, testing hypotheses, and making informed decisions based on their findings.
The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with...
1.8K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

New strategies for detecting atypical observations based on the information matrix equality.

Journal of applied statistics·2025
Same author

A beta regression analysis of COVID-19 mortality in Brazil.

Infectious Disease Modelling·2023
Same author

Beta distribution misspecification tests with application to Covid-19 mortality rates in the United States.

PloS one·2022
Same author

Bootstrap-based inferential improvements to the simplex nonlinear regression model.

PloS one·2022
Same author

Bartlett-corrected tests for varying precision beta regressions with application to environmental biometrics.

PloS one·2021
Same author

Inflated Kumaraswamy distributions.

Anais da Academia Brasileira de Ciencias·2019

Related Experiment Video

Updated: Sep 8, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K

Modified likelihood ratio tests for unit gamma regressions.

Ana C Guedes1, Francisco Cribari-Neto1, Patrícia L Espinheira1

  • 1Departamento de Estatística, Universidade Federal de Pernambuco, Recife, PE, Brazil.

Journal of Applied Statistics
|June 16, 2022
PubMed
Summary

This study introduces modified likelihood ratio tests for unit gamma regression, improving inference accuracy with small sample sizes. These new tests offer more reliable results for rates and proportions compared to traditional methods.

Keywords:
62F8662J0262J05Beta regressionlikelihood ratio testnonnested modelsunit gamma distributionunit gamma regression

More Related Videos

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.0K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.3K

Related Experiment Videos

Last Updated: Sep 8, 2025

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
04:35

Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach

Published on: July 3, 2020

3.4K
Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits
08:27

Applying an eMASS Customization Program as a Research Tool to Evaluate Consumer Benefits

Published on: September 27, 2019

7.0K
Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

10.3K

Area of Science:

  • Statistics
  • Econometrics

Background:

  • Regression analysis often involves doubly limited continuous dependent variables like rates and proportions.
  • The unit gamma regression model is suitable for such data, typically using maximum likelihood estimation and likelihood ratio tests.

Purpose of the Study:

  • To propose modified likelihood ratio test statistics for unit gamma regression.
  • To enhance the accuracy of inferences, particularly in small sample size scenarios.

Main Methods:

  • Development of two novel modified likelihood ratio test statistics.
  • Evaluation through numerical simulations for fixed and varying dispersion models.
  • Assessment of tests involving nonnested models.

Main Results:

  • The proposed modified tests provide more accurate inferences than standard likelihood ratio tests with small sample sizes.
  • Simulation evidence supports the improved performance across different dispersion scenarios and model types.

Conclusions:

  • Modified likelihood ratio tests offer a significant improvement for statistical inference in unit gamma regression with limited data.
  • These methods are valuable for analyzing rates, proportions, and similar bounded continuous variables.