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Related Concept Videos

Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This phenomenon...
Strategies for Assessing and Addressing Confounding01:25

Strategies for Assessing and Addressing Confounding

Confounding is a critical issue in epidemiological studies, often leading to misleading conclusions about associations between exposures and outcomes. It occurs when the relationship between the exposure and the outcome is mixed with the effects of other factors that influence the outcome. Given that, addressing confounding is of high importance for drawing accurate inferences in research.
Confounding can be addressed at both the design phase of a study and through analytical methods after data...
Drug Concentration Versus Time Correlation01:15

Drug Concentration Versus Time Correlation

The plasma drug concentration-time curve is a crucial tool in pharmacokinetics, representing the drug's concentration in plasma at different time intervals post-administration. This curve illustrates the drug's journey from absorption into the systemic circulation, distribution to body tissues, and eventual elimination through excretion or biotransformation.
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Blinding01:11

Blinding

Blinding is a commonly used method of not telling participants which treatment a subject is receiving. Blinding is a critical part of a randomized control trial or RCT. It reduces the bias that affects the results. In an RCT, blinding is used in the form of a placebo. A placebo effect occurs when untreated subjects falsely believe they have received the treatment and report improved symptoms. A placebo or a dummy treatment is administered to subjects to negate the bias caused by such an effect.
Time Course of Drug Effect01:14

Time Course of Drug Effect

The progression of a drug's impact can be analyzed by examining both the concentration-time course and the effect-time course. The concentration-time course is determined by the drug's half-life and is influenced by factors such as its pharmacokinetics, including absorption, distribution, metabolism, and elimination. The effect of the drug is often related to its concentration in the plasma and is calculated using the maximum drug effect and the plasma concentration that generates 50 percent of...
Confirmation Biases01:31

Confirmation Biases

The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?

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Related Experiment Video

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A Within-Subject Experimental Design using an Object Location Task in Rats
09:28

A Within-Subject Experimental Design using an Object Location Task in Rats

Published on: May 6, 2021

Time-modified confounding.

Robert W Platt1, Enrique F Schisterman, Stephen R Cole

  • 1Department of Pediatrics and Epidemiology, McGillUniversity, Montreal, Quebec, Canada. robert.platt@mcgill.ca

American Journal of Epidemiology
|August 14, 2009
PubMed
Summary
This summary is machine-generated.

Time-modified confounding, where confounder effects change over time, requires new statistical approaches. Marginal structural models can accurately adjust for this bias, improving causal inference in longitudinal studies.

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Related Experiment Videos

Last Updated: Jun 21, 2026

A Within-Subject Experimental Design using an Object Location Task in Rats
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Area of Science:

  • Epidemiology
  • Biostatistics
  • Causal Inference

Background:

  • Confounding is a major challenge in observational studies, potentially biasing treatment effect estimates.
  • Existing methods primarily address time-varying confounding where confounder values change.
  • However, the impact of confounders can also evolve over time, a phenomenon termed time-modified confounding.

Purpose of the Study:

  • To introduce and define the concept of time-modified confounding.
  • To propose a statistical approach using marginal structural models to address this bias.
  • To demonstrate the effectiveness of the proposed method through an example and simulation.

Main Methods:

  • Definition of time-modified confounding, distinguishing it from time-varying confounding.
  • Application of marginal structural models (MSMs) with inverse probability-of-treatment weighting (IPTW).
  • Specification of the treatment model within MSMs to account for time-varying effects of confounders.

Main Results:

  • MSMs incorporating time-modified confounding adjustments produced unbiased estimates and appropriate confidence intervals.
  • Standard MSMs that did not account for time-modified confounding exhibited significant bias.
  • Simulations confirmed the robustness of the proposed method under time-modified confounding.

Conclusions:

  • Time-modified confounding is a critical consideration in longitudinal causal inference.
  • Marginal structural models, when correctly specified to include time-modified confounding, provide valid estimates.
  • Accurate modeling of confounder effects over time is essential for reliable causal conclusions.