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Related Concept Videos

Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

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In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
In the...
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Sampling Methods: Sample Types01:18

Sampling Methods: Sample Types

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Sampling materials are classified into three main types: solid, liquid, and gas.
Solid samples include a variety of substances, such as sediments from water bodies, soil, metals, and biological tissues. Two standard methods for extracting sediments from water bodies are grab sampling and piston coring. Grab sampling involves using a device to collect a discrete sediment sample from the bottom of a water body with minimal disturbance. Grab samples do not always represent the entire area due to...
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Chronopharmacokinetics: Time-Dependent Pharmacokinetics01:20

Chronopharmacokinetics: Time-Dependent Pharmacokinetics

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Chronopharmacokinetics studies the temporal change in drug absorption and elimination. These changes can be cyclical or non-cyclical. Cyclical changes occur over a regular interval, while non-cyclical changes occur over a longer, irregular period.
Time-dependent pharmacokinetics refers to non-cyclical changes in drug rate processes over a period of time. It can lead to nonlinear pharmacokinetics, where the relationship between drug concentration and time is not proportional. Non-cyclical...
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Sampling Plans01:23

Sampling Plans

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Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
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Sample Handling01:02

Sample Handling

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Transportation of samples from the collection point to the laboratory, as well as storage and preservation techniques, are crucial for maintaining sample integrity and ensuring accurate and reliable test results.
Samples should be transported carefully from collection points to the laboratory. They should be properly sealed and clearly labeled to prevent cross-contamination. To preserve the sample integrity, optimal temperature conditions during transport are essential. This could involve using...
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Sampling Theorem01:15

Sampling Theorem

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In signal processing, the analysis of continuous-time signals, denoted as x(t), often involves sampling techniques to convert these signals into discrete-time signals. This process is essential for digital representation and manipulation. A critical component in sampling is the train of impulses, characterized by the sampling interval and the sampling frequency. The relationship between these parameters and the original signal's properties dictates the success of the sampling process.
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A New Portable In Vitro Exposure Cassette for Aerosol Sampling
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Nested exposure case-control sampling: a sampling scheme to analyze rare time-dependent exposures.

Jan Feifel1, Madlen Gebauer2, Martin Schumacher3

  • 1Ulm University, Helmholtzstrasse 20, 89081, Ulm, Germany. jan.feifel@uni-ulm.de.

Lifetime Data Analysis
|November 15, 2018
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Summary
This summary is machine-generated.

This study introduces novel sampling schemes for nested case-control designs, improving efficiency in large cohort studies with time-dependent exposures. These methods reduce data collection needs while maintaining analytical rigor for complex epidemiological research.

Keywords:
Cost-effective samplingCox proportional hazards modelHospital-acquired pneumoniaMatched case-control studyTime-dependent covariate

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Area of Science:

  • Epidemiology
  • Biostatistics

Background:

  • Nested case-control designs are efficient for rare outcomes in large cohorts.
  • Traditional methods may be suboptimal when time-dependent exposures, not rare outcomes, are of primary interest.

Purpose of the Study:

  • To develop and evaluate new sampling schemes for nested case-control studies.
  • To address situations where time-dependent exposures (e.g., adverse events) are key, even if outcomes are not rare.
  • To enhance data collection efficiency in observational health research.

Main Methods:

  • Utilized the counting process formulation of general nested case-control designs.
  • Proposed three novel sampling schemes with time-dependent and history-dependent inclusion probabilities.
  • Conducted bootstrap analysis on a full cohort dataset from hospital epidemiology.

Main Results:

  • The proposed sampling schemes offer practical utility compared to full cohort analysis.
  • Demonstrated advantages over a simplified nested case-control approach when outcomes are not rare.
  • Investigated the impact of time-dependent exposures on study efficiency.

Conclusions:

  • The novel sampling schemes are effective for large cohort studies with time-dependent exposures.
  • These methods provide a more efficient alternative to full cohort or simplified nested case-control designs in specific scenarios.
  • Offers a valuable methodological advancement for observational health studies.