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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.
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Relative Risk01:12

Relative Risk

Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...
Odds Ratio01:09

Odds Ratio

The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
Hazard Ratio01:12

Hazard Ratio

The hazard ratio (HR) is a widely used measure in clinical trials to compare the risk of events, such as death or disease recurrence, between two groups over time. It reflects the ratio of hazard rates—the instantaneous risk of the event occurring—between a treatment group and a control group. This measure provides valuable insights into the relative effectiveness of a treatment by assessing how the risk of an event differs between the two groups.
For example, in a clinical trial evaluating a...

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Sample size requirements for studies estimating odds ratios or relative risks.

S Lemeshow1, D W Hosmer, J Klar

  • 1University of Massachusetts, Amherst 01003.

Statistics in Medicine
|July 1, 1988
PubMed
Summary
This summary is machine-generated.

This study provides new formulas for calculating the necessary sample size in case-control and cohort studies. These formulas ensure accurate estimation of odds ratios and relative risks as a percentage of the true value, independent of hypothesis testing.

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Area of Science:

  • Epidemiology
  • Biostatistics
  • Medical Research Methodology

Background:

  • Accurate sample size determination is crucial for the validity of epidemiological studies.
  • Previous methods for sample size calculation often focused on fixed distances rather than relative percentages for effect size estimation.
  • A gap existed in the literature for calculating sample size for relative risk estimation in cohort studies based on percentage error.

Purpose of the Study:

  • To present novel formulae for sample size determination in case-control and cohort studies.
  • To enable estimation of the odds ratio (case-control) and relative risk (cohort) within a specified percentage (epsilon) of the true population value.
  • To provide study size guidelines independent of traditional hypothesis testing.

Main Methods:

  • Development of mathematical formulae for sample size calculation.
  • The approach focuses on estimating the effect size (odds ratio or relative risk) within a relative percentage error (epsilon).
  • Formulations consider a specified probability of achieving the desired precision.

Main Results:

  • New formulae are presented for determining the required number of subjects in case-control studies to estimate the odds ratio.
  • New formulae are presented for determining the required number of subjects in cohort studies to estimate the relative risk.
  • The proposed method allows sample size calculation based on a percentage of the true effect size, offering a different approach from prior fixed-distance methods.

Conclusions:

  • The developed formulae offer a practical and statistically sound method for sample size determination in epidemiological research.
  • These guidelines facilitate the planning of case-control and cohort studies with a focus on achieving a desired level of precision in effect size estimation.
  • The approach provides flexibility by not relying on hypothesis testing frameworks, accommodating different research objectives.