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Related Concept Videos

Sample Size Calculation01:19

Sample Size Calculation

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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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One-Way ANOVA: Equal Sample Sizes01:15

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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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One-Way ANOVA: Unequal Sample Sizes01:15

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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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Dose Size and Dosing Frequency: Determination Methods01:21

Dose Size and Dosing Frequency: Determination Methods

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Determining the optimal dose size and dosing frequency in pharmacotherapy is crucial for achieving therapeutic effectiveness while minimizing adverse effects. This article explores the methodologies employed in determining these parameters, focusing on their significance and interplay to tailor dosing regimens.Dose Size: Dose size refers to the amount of a drug administered in a single dose. It is determined based on the drug's pharmacodynamics and pharmacokinetics properties and...
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Mesh Analysis with Current Sources01:10

Mesh Analysis with Current Sources

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Mesh analysis becomes simpler when analyzing circuits with current sources, whether independent or dependent. The presence of current sources reduces the number of equations required for analysis. Two cases illustrate this:
Current Source in One Mesh: The analysis process is straightforward when a current source is found in only one mesh within the circuit. Mesh currents are assigned as usual, with the mesh containing the current source excluded from the analysis. Kirchhoff's voltage law...
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One-Compartment Open Model: Urinary Excretion Data and Determination of k01:11

One-Compartment Open Model: Urinary Excretion Data and Determination of k

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The one-compartment open model leverages urinary excretion data to estimate renal clearance, which gauges the kidney's capacity to expel a drug. This method offers several benefits, including directly measuring drug elimination and assessing the kidney's contribution to overall drug clearance. However, this approach has limitations. It assumes sole renal excretion of the drug, which is not true for all drugs. Accurate urinary excretion and plasma drug concentration measurement can also...
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Related Experiment Video

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Nanoparticle Tracking Analysis for the Quantification and Size Determination of Extracellular Vesicles
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Sample size determination for semiparametric analysis of current status data.

Chi-Chung Wen1, Yi-Hau Chen2

  • 11 Department of Mathematics, Tamkang University, New Taipei City, Taiwan.

Statistical Methods in Medical Research
|March 1, 2018
PubMed
Summary

This study introduces a new sample size calculation for semiparametric survival analysis with current status data. This method is crucial for planning future studies in survival analysis research.

Keywords:
Cox proportional hazards modelpowersample size calculationstudy designtransformation models

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Area of Science:

  • Statistics
  • Biostatistics
  • Survival Analysis

Background:

  • Semiparametric transformation models are widely used in survival analysis due to their flexibility.
  • Existing sample size calculations do not cover current status data, a common scenario in observational studies.
  • Current status data only records event occurrence before a single examination time.

Purpose of the Study:

  • To develop a sample size calculation formula for semiparametric analyses with current status data.
  • To enable robust planning for two-group comparisons and regression analyses in such settings.

Main Methods:

  • Developed a novel sample size calculation for semiparametric models with current status data.
  • The formula incorporates effect size, power, covariate distributions, and event proportions.
  • Validated the method using simulations.

Main Results:

  • The proposed sample size calculation is shown to be adequate through simulations.
  • Empirical power closely matched the planned power levels in simulation studies.
  • The formula is practical for implementation in real-world research.

Conclusions:

  • The developed sample size calculation addresses a critical gap in survival analysis methodology.
  • This facilitates more accurate study design for research utilizing current status data.
  • Applications demonstrated in animal tumorigenicity and elderly osteoporosis studies.