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Related Concept Videos

Sample Size Calculation01:19

Sample Size Calculation

6.9K
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...
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Testing a Claim about Population Proportion01:24

Testing a Claim about Population Proportion

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A complete procedure for testing a claim about a population proportion is provided here.
There are two methods of testing a claim about a population proportion: (1) Using the sample proportion from the data where a binomial distribution is approximated to the normal distribution and (2) Using the binomial probabilities calculated from the data.
The first method uses normal distribution as an approximation to the binomial distribution. The requirements are as follows: sample size is large...
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One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

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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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Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

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A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
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One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

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One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
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Central Limit Theorem01:14

Central Limit Theorem

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The central limit theorem, abbreviated as clt, is one of the most powerful and useful ideas in all of statistics. The central limit theorem for sample means says that if you repeatedly draw samples of a given size and calculate their means, and create a histogram of those means, then the resulting histogram will tend to have an approximate normal bell shape. In other words, as sample sizes increase, the distribution of means follows the normal distribution more closely.
The sample size, n, that...
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Practical guide to sample size calculations: superiority trials.

Laura Flight1, Steven A Julious1

  • 1Medical Statistics Group, University of Sheffield, Sheffield, UK.

Pharmaceutical Statistics
|November 21, 2015
PubMed
Summary
This summary is machine-generated.

Calculating the correct sample size is essential for research validity. This paper outlines steps for sample size calculations in superiority trials, offering practical guidance and examples for manual computation and app usage.

Keywords:
clinical trialspowersample sizesuperiority

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Area of Science:

  • Biostatistics
  • Clinical Trials

Background:

  • A robust sample size justification is crucial for the meaningfulness of research findings.
  • Accurate sample size estimation can be complex, requiring careful consideration of multiple factors.

Purpose of the Study:

  • To summarize the essential steps for conducting sample size calculations specifically for superiority trials.
  • To provide practical guidance and illustrative examples for performing these calculations.

Main Methods:

  • The paper outlines a systematic approach to sample size calculation for superiority trials.
  • Methods include both manual calculation techniques and the utilization of the SampSize application.

Main Results:

  • Clear steps are provided for determining appropriate sample sizes in superiority trial designs.
  • Examples demonstrate the practical application of these calculation methods.

Conclusions:

  • Effective sample size calculation is achievable through a structured approach.
  • The SampSize app offers a practical tool to aid researchers in sample size determination for superiority trials.