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

Friedman Two-way Analysis of Variance by Ranks01:21

Friedman Two-way Analysis of Variance by Ranks

555
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...
555
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

8.8K
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).
8.8K
Two-Way ANOVA01:17

Two-Way ANOVA

3.6K
The two-way ANOVA is an extension of the one-way ANOVA. It is a statistical test performed on three or more samples categorized by two factors - a row factor and a column factor. Ronald Fischer mentioned it in 1925 in his book 'Statistical Methods for Researchers.'
The two-way ANOVA analysis initially begins by stating the null hypothesis that there is an interaction effect between the two factors of a dataset. This effect can be visualized using line segments formed by joining the...
3.6K
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

1.3K
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
1.3K
Goodness-of-Fit Test01:16

Goodness-of-Fit Test

9.4K
The goodness-of-fit test is a type of hypothesis test which determines whether the data "fits" a particular distribution. For example, one may suspect that some anonymous data may fit a binomial distribution. A chi-square test (meaning the distribution for the hypothesis test is chi-square) can be used to determine if there is a fit. The null and alternative hypotheses may be written in sentences or stated as equations or inequalities. The test statistic for a goodness-of-fit test is given as...
9.4K
Hazard Ratio01:12

Hazard Ratio

688
The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial...
688

You might also read

Related Articles

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

Sort by
Same author

What Lies INSIDE: Chemometric Insights on the Penetration Depth of Near-Infrared Radiation in Spectral Imaging Configurations.

Analytical chemistry·2026
Same author

Elemental profiling of processed foods using ICP-MS and chemometric evaluation of elemental patterns.

Food chemistry·2026
Same author

Systemic metabolic alterations in Ménière's disease: Insights from urinary <sup>1</sup>H NMR-based metabolomics.

iScience·2026
Same author

Volatilomic Differentiation of Protected-Origin Italian Balsamic Vinegars by HS-SPME-GC×GC-TOFMS.

Journal of separation science·2026
Same author

Can DNA withstand the test of time? Exploring degradation across storage conditions.

Forensic science international. Genetics·2026
Same author

A rapid urinary test for combining PSA and zinc to enhance prostate cancer diagnosis: results from a prospective study.

Prostate cancer and prostatic diseases·2025
Same journal

Insights from the first synthetic cannabinoid clandestine lab dismantled in Brazil.

Forensic science international·2026
Same journal

Determination of the new psychoactive substances MDMB-4en-PINACA, ADB-BUTINACA and some of their metabolites in blood and urine using DLLE-LC-MS/MS: application to real forensic case samples.

Forensic science international·2026
Same journal

The revolver halo as a forensic marker: Raman spectroscopic evidence of primer-driven gunshot residue deposition.

Forensic science international·2026
Same journal

Research on the effects of signature size on experts' opinions.

Forensic science international·2026
Same journal

Experimental and numerical study of non-penetrating FMJ ballistic impacts on coupled soft and bone tissue surrogates.

Forensic science international·2026
Same journal

Limitations of inkjet and spot amino acid targets for fingermark reagent research and monitoring - and some observations.

Forensic science international·2026
See all related articles

Related Experiment Video

Updated: Mar 24, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

3.0K

A likelihood ratio model for three-way data coupled with a PARAFAC model.

Agnieszka Martyna1, Eugenio Alladio2, Monica Romagnoli3

  • 1Forensic Chemistry Research Group, Institute of Chemistry, University of Silesia in Katowice, Szkolna 9, 40-007 Katowice, Poland.

Forensic Science International
|March 22, 2026
PubMed
Summary
This summary is machine-generated.

Forensic scientists compared weathered diesel fuel samples to identify arson accelerants. Likelihood ratio models showed potential but require improvement to reduce misidentification rates between similar and dissimilar samples.

Keywords:
Comparison of dataDiesel fuelFire debris analysisGC-MSHybrid likelihood ratio modelsPARAFAC

More Related Videos

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

3.8K
Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions
11:22

Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions

Published on: January 30, 2018

10.7K

Related Experiment Videos

Last Updated: Mar 24, 2026

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments
08:12

A Psychophysics Paradigm for the Collection and Analysis of Similarity Judgments

Published on: March 1, 2022

3.0K
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

3.8K
Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions
11:22

Using Three-color Single-molecule FRET to Study the Correlation of Protein Interactions

Published on: January 30, 2018

10.7K

Area of Science:

  • Forensic Science
  • Analytical Chemistry
  • Chemometrics

Background:

  • Diesel fuel is a common accelerant in arson cases due to its accessibility and effectiveness.
  • Distinguishing between weathered diesel samples from the same or different sources is crucial for arson investigations.

Purpose of the Study:

  • To evaluate the capability of Likelihood Ratio (LR) models in identifying diesel samples from the same source despite weathering.
  • To assess the effectiveness of LR models in differentiating diesel samples from different sources, irrespective of weathering.

Main Methods:

  • Gas Chromatography-Mass Spectrometry (GC-MS) analysis of diesel samples weathered to varying degrees.
  • Application of hybrid LR models utilizing latent variables derived from Parallel Factor Analysis (PARAFAC).
  • PARAFAC decomposition to generate new variables from concentration mode loadings for LR analysis.

Main Results:

  • LR models demonstrated potential in discriminating between differently weathered diesel samples.
  • Misleading evidence rates were observed to be relatively high, indicating a need for model refinement.
  • 14% of dissimilar source samples were incorrectly identified as originating from the same source.
  • 8% of same source, but differently weathered samples, were incorrectly identified as originating from different sources.

Conclusions:

  • The LR framework shows promise for analyzing weathered diesel accelerants in arson investigations.
  • Current hybrid LR models require further development to improve accuracy and reduce misclassification rates.
  • Refined models are necessary to reliably link or exclude diesel samples in forensic casework.