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

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

1.0K
This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
1.0K
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

210
Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least...
210
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

937
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...
937
Distributions to Estimate Population Parameter01:26

Distributions to Estimate Population Parameter

5.0K
The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...
5.0K
Probability Laws01:49

Probability Laws

43.8K
Overview
43.8K
Multiple Regression01:25

Multiple Regression

3.7K
Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
3.7K

You might also read

Related Articles

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

Sort by
Same author

The Association Between Prospective Payment System and Post-Acute Care Outcomes Among Traditional Medicare Beneficiaries in Inpatient Rehabilitation Facilities.

Journal of the American Medical Directors Association·2026
Same author

Length of stay of post-acute care: determinants and differences between traditional medicare and medicare advantage.

Health affairs scholar·2025
Same author

Classifying the Integration of Healthcare Providers and Insurers.

Health economics·2025
Same author

Care transition management and patient outcomes in hospitalized Medicare beneficiaries.

The American journal of managed care·2024
Same author

Clinical decisions, patient race, and flawed data.

Proceedings of the National Academy of Sciences of the United States of America·2024
Same author

Regional variation in length of stay for stroke inpatient rehabilitation in traditional Medicare and Medicare Advantage.

Health affairs scholar·2024

Related Experiment Video

Updated: Dec 31, 2025

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

10.7K

Estimation of Multivariate Probit Models via Bivariate Probit.

John Mullahy1

  • 1Univ. of Wisconsin-Madison, NUI Galway, and NBER.

The Stata Journal
|January 15, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces an efficient method for estimating multivariate probit (MVP) models using sequential bivariate probit estimators. This approach offers faster computation and handles more outcomes compared to existing methods.

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

3.6K
Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.7K

Related Experiment Videos

Last Updated: Dec 31, 2025

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

10.7K
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

3.6K
Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills
06:52

Using Cholesky Decomposition to Explore Individual Differences in Longitudinal Relations between Reading Skills

Published on: September 17, 2019

6.7K

Area of Science:

  • Econometrics
  • Statistical Modeling
  • Computational Statistics

Background:

  • Multivariate probit (MVP) models are crucial for analyzing multiple binary outcomes.
  • Existing Stata procedures like mvprobit can be computationally intensive and limited in dimensionality.

Purpose of the Study:

  • To propose and evaluate a novel method for estimating MVP models.
  • To demonstrate the computational efficiency and scalability of the new approach.

Main Methods:

  • Utilizing a chain of bivariate probit estimators (biprobit and suest) within Stata.
  • Developing a Mata function to implement the sequential estimation procedure.

Main Results:

  • The proposed method significantly reduces computation time compared to mvprobit.
  • The approach allows for essentially unlimited dimensionality of the outcome set.
  • Simulation results indicate no loss in estimator precision relative to mvprobit.

Conclusions:

  • The chain of bivariate probit estimators offers a computationally efficient and scalable alternative for MVP model estimation.
  • This method provides consistent parameter estimates under standard assumptions.
  • The approach enhances the practical application of MVP models in complex scenarios.