Related Experiment Video

Updated: Apr 14, 2026

An R-Based Landscape Validation of a Competing Risk Model
05:37

An R-Based Landscape Validation of a Competing Risk Model

Published on: September 16, 2022

2.8K

New guideline for the reporting of studies developing, validating, or updating a prediction model

Karel G M Moons, Douglas G Altman, Johannes B Reitsma

    Clinical Chemistry
    |April 16, 2015
    PubMed
    Summary

    No abstract available in PubMed .

    More Related Videos

    Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack07:31

    Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack

    Published on: May 15, 2020

    8.3K
    Constructing and Visualizing Models using Mime-based Machine-learning Framework06:19

    Constructing and Visualizing Models using Mime-based Machine-learning Framework

    Published on: July 22, 2025

    3.2K

    Related Concept Videos

    Data Validation01:03

    Data Validation

    Data validation is an essential part of a comprehensive assessment. Validation is confirming or verifying and opening the door to gathering more assessment data as it clarifies vague or unclear data. The process of checking and verifying the collected information is called data validation. The primary purpose of data validation is to ensure data is as free from error, bias, and misinterpretation as possible.
    Nursing assessment guides are generally based on holistic models rather than medical...
    7.2K
    Data Validation01:15

    Data Validation

    Method validation is a crucial process in analytical chemistry designed to confirm that a given method consistently produces reliable and high-quality results. This process is essential when a method is applied to different sample matrices or when procedural modifications are made, ensuring that the results meet acceptable standards across various applications.
    Key parameters for method validation include:
    3.6K
    Prediction Intervals01:03

    Prediction Intervals

    The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
    However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
    3.6K
    Testing a Claim about Standard Deviation01:19

    Testing a Claim about Standard Deviation

    A complete procedure to test a claim about population standard deviation or population variance is explained here.
    The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
    As a first step, the hypothesis (null and alternative) concerning the claim about...
    3.2K
    Sensitivity, Specificity, and Predicted Value01:13

    Sensitivity, Specificity, and Predicted Value

    In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
    Sensitivity is the...
    1.8K
    Regression Analysis01:11

    Regression Analysis

    Regression analysis is a statistical tool that describes a mathematical relationship between a dependent variable and one or more independent variables.
    In regression analysis, a regression equation is determined based on the line of best fit– a line that best fits the data points plotted in a graph. This line is also called the regression line. The algebraic equation for the regression line is called the regression equation. It is represented as:
    9.0K