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Related Concept Videos

Randomized Experiments01:13

Randomized Experiments

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The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
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Blinding01:11

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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.
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Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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Biopharmaceutical studies constitute a vital field aiming to enhance drug delivery methods and refine therapeutic approaches, drawing upon diverse interdisciplinary knowledge. In research methodologies, the choice between controlled and non-controlled studies significantly influences the study's reliability and accuracy.
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
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Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs01:20

Bioequivalence Experimental Study Designs: Completely Randomized and Randomized Block Designs

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Body:Bioequivalence experimental study designs are crucial methodologies used in evaluating and comparing the bioavailability of different drug products. These designs are categorized into various types: completely randomized, randomized block, repeated measures, cross and carry-over, and Latin square designs.Completely randomized designs involve randomly allocating treatments to all subjects participating in the experiment. This allocation is achieved by assigning unique random numbers to...
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What is an Experiment?01:12

What is an Experiment?

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An experiment is a planned activity carried out under controlled conditions. The purpose of an experiment is to investigate the relationship between two variables. When one variable causes change in another, we call the first variable the explanatory or independent variable. The affected variable is called the response or dependent variable. In a randomized experiment, the researcher manipulates values of the explanatory variable and measures the resulting changes in the response variable. The...
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Blind Procedures

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Ideally, the people who observe and record the children’s behavior are unaware of who was assigned to the experimental or control group, in order to control for experimenter bias. Experimenter bias refers to the possibility that a researcher’s expectations might skew the results of the study. Remember, conducting an experiment requires a lot of planning, and the people involved in the research project have a vested interest in supporting their hypotheses. If the observers knew which...
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Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
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Defining and Identifying Per-protocol Effects in Randomized Trials.

Jacqueline E Rudolph1, Ashley I Naimi1, Daniel J Westreich2

  • 1From the Department of Epidemiology, University of Pittsburgh, Pittsburgh, PA.

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|August 3, 2020
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Summary
This summary is machine-generated.

Researchers can estimate per-protocol effects, comparing outcomes based on treatment adherence, not just assignment. This study defines per-protocol effects and discusses their identification in trials with noncompliance.

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Area of Science:

  • Causal inference in clinical trials
  • Epidemiology
  • Biostatistics

Background:

  • Noncompliance to assigned treatment is common in clinical trials.
  • Estimating treatment effects under noncompliance requires careful consideration of causal definitions.
  • Per-protocol effect estimation is of interest when adherence to a treatment protocol is crucial.

Purpose of the Study:

  • To provide a general counterfactual definition of a per-protocol effect.
  • To illustrate substantive and methodologic examples of per-protocol effects.
  • To clarify that per-protocol effects extend beyond simple comparisons of always-treated groups.

Main Methods:

  • Development of a general counterfactual framework for per-protocol effects.
  • Discussion of identifiability conditions for causal per-protocol effects.
  • Identification of potential violations of these conditions in practice.

Main Results:

  • A formal definition of per-protocol effects is presented.
  • Examples demonstrate the broader applicability of per-protocol effect estimation.
  • Conditions for the causal identification of per-protocol effects are outlined.

Conclusions:

  • Per-protocol effects offer a valuable tool for analyzing trials with noncompliance.
  • Understanding the counterfactual definition is key to accurate estimation.
  • Awareness of identifiability conditions and their violations is crucial for valid causal inference.