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Related Concept Videos

Instrument Calibration01:12

Instrument Calibration

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Instrument calibration is essential for ensuring that instruments produce accurate and consistent results. It is vital in manufacturing, healthcare, testing laboratories, and scientific research. Calibration processes are specific to each instrument and help enhance data accuracy. Each instrument has a unique calibration process tailored to its design and function to improve data accuracy.
Analytical Balance Calibration
An analytical balance measures mass and requires regular calibration to...
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Calibration Curves: Linear Least Squares01:20

Calibration Curves: Linear Least Squares

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A calibration curve is a plot of the instrument's response against a series of known concentrations of a substance. This curve is used to set the instrument response levels, using the substance and its concentrations as standards. Alternatively, or additionally, an equation is fitted to the calibration curve plot and subsequently used to calculate the unknown concentrations of other samples reliably.
For data that follow a straight line, the standard method for fitting is the linear...
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Calibration Curves: Correlation Coefficient01:10

Calibration Curves: Correlation Coefficient

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In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the...
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Estimation of the Physical Quantities01:05

Estimation of the Physical Quantities

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On many occasions, physicists, other scientists, and engineers need to make estimates of a particular quantity. These are sometimes referred to as guesstimates, order-of-magnitude approximations, back-of-the-envelope calculations, or Fermi calculations. The physicist Enrico Fermi was famous for his ability to estimate various kinds of data with surprising precision. Estimating does not mean guessing a number or a formula at random. Instead, estimation means using prior experience and sound...
8.4K
Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model01:13

Parameters Affecting Nonlinear Elimination: Zero-Order Input, First-Order Absorption and Two-Compartment Model

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Drugs administered through various routes can lead to nonlinear elimination, resulting in complex pharmacokinetic behaviors crucial to understanding efficacious drug dosing.
When a drug is administered through a constant intravenous infusion and eliminated via nonlinear pharmacokinetics, it follows zero-order input. For example, oral drugs undergo first-order absorption upon administration and are eliminated through nonlinear pharmacokinetics.
In the case of subcutaneously administered drugs,...
377
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

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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...
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Split Point Analysis and Uncertainty Quantification of Thermal-Optical Organic/Elemental Carbon Measurements
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Continuous Online Item Calibration: Parameter Recovery and Item Utilization.

Hao Ren1, Wim J van der Linden2, Qi Diao2

  • 1Pacific Metrics, 1 Lower Ragsdale Dr #150, Monterey, CA, 93940, USA. hren@pacificmetrics.com.

Psychometrika
|March 15, 2017
PubMed
Summary
This summary is machine-generated.

This study explored adaptive online test item calibration designs, optimizing field-test item assignment and stopping rules. Efficient parameter recovery and item utilization were achieved through adaptive testing and assignment strategies.

Keywords:
Bayesian optimal designD-optimalityadaptive testingitem calibration

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Area of Science:

  • Educational Measurement
  • Psychometrics
  • Computerized Adaptive Testing

Background:

  • Online test item calibration is crucial for accurate assessment.
  • Traditional calibration methods can be inefficient.
  • Adaptive testing offers potential improvements in efficiency and accuracy.

Purpose of the Study:

  • To investigate parameter recovery and item utilization in online test item calibration.
  • To evaluate different designs for adaptive assignment of field-test items.
  • To assess the impact of optimality criteria and stopping rules on calibration efficiency.

Main Methods:

  • Employed a double adaptive design for both examinee testing and field-test item assignment.
  • Utilized four optimality criteria based on posterior distributions of ability and item parameters.
  • Implemented various stopping rules based on posterior standard deviations and sample size.

Main Results:

  • Demonstrated the impact of different optimality criteria and stopping rules on statistical efficiency.
  • Showcased the influence of these factors on the time required for item calibration.
  • Identified effective strategies for parameter recovery and item utilization in adaptive online calibration.

Conclusions:

  • Adaptive designs significantly enhance parameter recovery and item utilization in online test item calibration.
  • Specific optimality criteria and stopping rules lead to improved statistical efficiency.
  • Recommendations are provided for practical implementation of these adaptive calibration designs.