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Blind Procedures

Blind Procedures

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 child was...

Randomized Experiments

Randomized Experiments

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.
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Clinical Trials

Clinical Trials

Clinical trials are prospective experimental studies conducted on humans to determine the safety and efficacy of treatments, drugs, diet methods, and medical devices. Using statistics in clinical trials enables researchers to derive reasonable and accurate conclusions from the collected data, allowing them to make wise decisions in uncertain situations. In medical research, statistical methods are crucial for preventing errors and bias.
There are four phases in a clinical trial. A phase one...

Blinding

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.

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches

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, controlled...

Censoring Survival Data

Censoring Survival Data

Survival analysis is a statistical method used to analyze time-to-event data, often employed in fields such as medicine, engineering, and social sciences. One of the key challenges in survival analysis is dealing with incomplete data, a phenomenon known as "censoring." Censoring occurs when the event of interest (such as death, relapse, or system failure) has not occurred for some individuals by the end of the study period or is otherwise unobservable, and it might have many different reasons...

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Related Experiment Video

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A Clinical Trial Assessing the Safety, Efficacy, and Delivery of Olive-Oil-Based Three-Chamber Bags for Parenteral Nutrition

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Nonignorable censoring in randomized clinical trials.

Jiameng Zhang¹, Daniel F Heitjan

¹Center for Biostatistics in AIDS Research, Harvard School of Public Health, 651 Huntington Ave, Boston, MA 02115, USA. jzhang@sdac.harvard.edu

Clinical Trials (London, England)

|January 21, 2006

Summary

This study introduces a method to assess how non-ignorable censoring affects clinical trial survival estimates. Results show that while non-ignorable censoring can impact survival data, substantial effects require implausibly high levels of non-ignorability.

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Area of Science:

Biostatistics
Clinical Trials
Survival Analysis

Background:

Clinical trial survival data can be censored due to study end, especially for late enrollees.
If survival improves over time, longer survivors face earlier censoring, creating correlated survival and censoring times.
This correlation, termed non-ignorable censoring, can invalidate standard survival models assuming independent censoring.

Purpose of the Study:

To demonstrate a graphical method for analyzing the sensitivity of survival model parameter estimates to non-ignorable censoring.
To assess the impact of departures from the assumption of independent censoring in survival analysis.

Main Methods:

Employs a parametric survival model combined with a scaled beta model for censoring, accounting for censoring time's dependence on survival time.
Utilizes an index of local sensitivity to non-ignorability (Troxel et al.) to quantify the impact.
High sensitivity suggests significant influence of non-ignorable censoring, necessitating further modeling.

Main Results:

A simulation study confirmed the practical validity and usability of the proposed approach.
Applied to a left ventricular assist device trial, sensitivity was slightly higher for mean survival estimates in the better-surviving device arm.
The degree of non-ignorability needed to substantially alter estimates was found to be implausibly large.

Conclusions:

The study provides a practical sensitivity analysis framework for evaluating the reliability of survival parameter estimates in clinical trials.
Demonstrates that while non-ignorable censoring is a concern, its impact on estimates may be less substantial than initially feared under realistic conditions.