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Related Concept Videos

Sample Size Calculation01:19

Sample Size Calculation

Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches01:23

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...
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.
Randomized Experiments01:13

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.
Simple randomization
Simple...
Bonferroni Test01:10

Bonferroni Test

The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:

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Related Experiment Video

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Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index
06:55

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Blinded sample size recalculation in multicentre trials with normally distributed outcome.

Katrin Jensen1, Meinhard Kieser

  • 1Institute of Medical Biometry and Informatics, Ruprecht-Karls University Heidelberg, Germany.

Biometrical Journal. Biometrische Zeitschrift
|April 16, 2010
PubMed
Summary

Internal pilot studies allow sample size adjustments in ongoing clinical trials. This method ensures accurate sample sizes in multicenter trials, maintaining statistical power and controlling error rates.

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Area of Science:

  • Clinical Trials
  • Biostatistics
  • Pharmaceutical Research

Background:

  • Internal pilot study designs permit estimation of nuisance parameters for sample size calculations using accumulating trial data.
  • This allows correction of sample size misspecifications made during the planning phase with updated information.
  • Regulatory guidelines mandate maintaining personnel blindness and controlling type I error rates when using internal pilot study designs.

Purpose of the Study:

  • To propose a blinded sample size recalculation procedure for internal pilot studies in multicenter trials.
  • To address uncertainties in endpoint variance and disparities in center sample sizes.
  • To evaluate the procedure's performance regarding type I error rate, expected power, and sample size.

Main Methods:

  • Development of a blinded sample size recalculation procedure for internal pilot studies in multicenter trials.
  • Application to trials with normally distributed outcomes and two balanced treatment groups.
  • Analysis using both weighted and unweighted approaches.
  • Investigation of the procedure's performance through simulation studies.

Main Results:

  • The proposed procedure minimally exceeded the maximal type I error rate for both weighted and unweighted analyses.
  • The procedure achieved the specified value for expected power in many cases.
  • Expected power was consistently close to the specified value across simulations.

Conclusions:

  • The blinded sample size recalculation procedure is effective for internal pilot studies in multicenter trials.
  • It successfully manages uncertainties in variance and center sample size imbalance.
  • The procedure maintains statistical integrity while optimizing sample size and power.