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

Sieve Analysis and Grading Curves01:19

Sieve Analysis and Grading Curves

993
Sieve analysis is a method used to determine the particle size distribution of aggregate materials. This process involves the following steps:
993
Precipitation Titration Curve: Analysis01:21

Precipitation Titration Curve: Analysis

1.9K
The precipitation titration curve demonstrates the change in concentration of one reactant with the volume of titrant added. During the titration of chloride ions with silver nitrate, the precipitation titration curve is divided into three regions: before, at, and after the equivalence point. Before the equivalence point, low redissolution of the sparingly soluble silver chloride precipitate gives a low silver ion concentration. However, in the second region, representing the equivalence point,...
1.9K
Bending of Curved Members - Strain Analysis01:14

Bending of Curved Members - Strain Analysis

534
The mechanics of deformation in curved members, such as beams or arches, under bending moments, involve complex responses. When such a member, symmetric about the y-axis and shaped like a segment of a circle centered at point C, is subjected to equal and opposite forces, its curvature and surface lengths change significantly. This alteration results in the shift of the curvature's center from C to C', indicating a tighter curve.
The important part of bending analysis for such a member...
534
Heating and Cooling Curves02:44

Heating and Cooling Curves

28.0K
When a substance—isolated from its environment—is subjected to heat changes, corresponding changes in temperature and phase of the substance is observed; this is graphically represented by heating and cooling curves.
For instance, the addition of heat raises the temperature of a solid; the amount of heat absorbed depends on the heat capacity of the solid (q = mcsolidΔT). According to thermochemistry, the relation between the amount of heat absorbed or released by a substance, q, and its...
28.0K
Acid-Base Titration Curves02:23

Acid-Base Titration Curves

141.6K
A titration curve is a plot of some solution property versus the amount of added titrant. For acid-base titrations, solution pH is a useful property to monitor because it varies predictably with the solution composition and, therefore, may be used to monitor the titration’s progress and detect its endpoint. Acid-base titration can be performed with a strong acid and a strong base, a strong acid and a weak base, or a strong base and a weak acid.
For a titration carried out for 25.00 mL of...
141.6K
z Scores and Area Under the Curve01:17

z Scores and Area Under the Curve

19.6K
z scores are the standardized values obtained after converting a normal distribution into a standard normal distribution. A z score is measured in units of the standard deviation. The z score tells you how many standard deviations the value x is above (to the right of) or below (to the left of) the mean, μ. Values of x that are larger than the mean have positive z scores, and values of x that are smaller than the mean have negative z scores. If x equals the mean, then x has a z score of...
19.6K

You might also read

Related Articles

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

Sort by
Same author

Toward Evidence Synthesis of Adverse Events in Imbalanced Time-to-Event Data.

Journal of evidence-based medicine·2026
Same author

Gut microbial bile salt hydrolase as a metabolic gatekeeper in digestive homeostasis and disease.

Frontiers in immunology·2026
Same author

Trial-design-aware funnel plot for publication bias assessment with non-inferiority or equivalence objectives.

Journal of clinical epidemiology·2026
Same author

Unpublished trials affected evidence synthesis substantially when estimating medication harms in children.

Journal of clinical epidemiology·2026
Same author

The hazards of using hazard ratios from proportional hazard models in indirect treatment comparisons.

Research synthesis methods·2026
Same author

Minimum distance estimation of mean and standard deviation from reported quantiles.

Research synthesis methods·2026
Same journal

Regression analysis of misclassified current status data with potentially unknown test accuracy.

Statistical methods in medical research·2026
Same journal

Bayesian multivariate linear mixed-effects models with varied association structures.

Statistical methods in medical research·2026
Same journal

Inference about the ratio of age-standardized rates between two overlapping populations.

Statistical methods in medical research·2026
Same journal

A robust neural network with random effects for subject-specific prediction of clustered count data.

Statistical methods in medical research·2026
Same journal

A comparison of methods for designing hybrid type 2 cluster-randomized trials with continuous effectiveness and implementation endpoints.

Statistical methods in medical research·2026
Same journal

Joint analysis of longitudinal and recurrent event data: A functional regression approach with autoregressive frailty.

Statistical methods in medical research·2026
See all related articles

Related Experiment Video

Updated: Feb 8, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.7K

A Bayesian hierarchical model for demand curve analysis.

Yen-Yi Ho1, Tien Nhu Vo2, Haitao Chu3

  • 11 Department of Statistics, College of Arts and Sciences, University of South Carolina, Columbia, SC, USA.

Statistical Methods in Medical Research
|July 10, 2018
PubMed
Summary
This summary is machine-generated.

This study introduces a new Bayesian hierarchical model for analyzing drug self-administration demand curves. This approach improves upon traditional methods by allowing for the estimation of variability in drug reinforcing strength.

Keywords:
Bayesian hierarchical modeldemand curve analysismixed effects regressionnon-linear least square regressionprism

More Related Videos

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.3K
Versatile Technique to Produce a Hierarchical Design in Nanoporous Gold
05:28

Versatile Technique to Produce a Hierarchical Design in Nanoporous Gold

Published on: February 10, 2023

2.2K

Related Experiment Videos

Last Updated: Feb 8, 2026

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
12:39

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

11.7K
Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments
13:00

Measuring Attention and Visual Processing Speed by Model-based Analysis of Temporal-order Judgments

Published on: January 23, 2017

10.3K
Versatile Technique to Produce a Hierarchical Design in Nanoporous Gold
05:28

Versatile Technique to Produce a Hierarchical Design in Nanoporous Gold

Published on: February 10, 2023

2.2K

Area of Science:

  • Behavioral neuroscience
  • Pharmacology
  • Biostatistics

Background:

  • Drug self-administration studies assess compound abuse liability and reinforcing properties.
  • Demand curve analysis quantifies how reinforcer demand changes with price, crucial for tobacco regulation.
  • Current methods like non-linear least square regression analyze data per subject, limiting variability estimation.

Purpose of the Study:

  • To review existing demand curve analysis methods.
  • To propose a novel Bayesian hierarchical model for analyzing drug self-administration data.
  • To compare the proposed model with existing approaches via simulation and case study.

Main Methods:

  • Review of non-linear least square and mixed effects regression.
  • Development and proposal of a Bayesian hierarchical model.
  • Simulation analyses to compare model performance.
  • Application to a nicotine self-administration in rats case study.

Main Results:

  • The proposed Bayesian hierarchical model allows for unified estimation of between- and within-subject variability.
  • Simulation results demonstrate the performance of the proposed model compared to traditional methods.
  • Case study illustrates the practical application of the new model for nicotine demand analysis.

Conclusions:

  • The Bayesian hierarchical model offers advantages for analyzing drug demand curve data, particularly in estimating variability.
  • This approach can provide more comprehensive insights into drug reinforcing strength.
  • The findings support the use of advanced statistical models in drug abuse liability research and policy-making.