title: Fundamentals of estimating sample size.
abstract: BACKGROUND
  Estimating sample size is an integral requirement in the planning stages of quantitative studies. However, although abundant literature is available that describes techniques for calculating sample size, many are in-depth and have varying degrees of complexity.
  
  
  OBJECTIVE
  To provide an overview of four basic parameters that underpin the determination of sample size and to explain sample-size estimation for three study designs common in nursing research.
  
  
  CONCLUSIONS
  Researchers can estimate basic sample size if they have a comprehension of four parameters, such as significance level, power, effect size, and standard deviation (for continuous data) or event rate (for dichotomous data). In this paper, these parameters are applied to determine sample size for the following well-established study designs: a comparison of two independent means, the paired mean study design and a comparison of two proportions.
  
  
  CONCLUSIONS
  An informed choice of parameter values to input into estimates of sample size enables the researcher to derive the minimum sample size required with sufficient power to detect a meaningful effect. An understanding of the parameters provides the foundation from which to generalise to more complex size estimates. It also enables more informed entry of required parameters into sample size software.
  
  
  CONCLUSIONS
  Underpinning the concept of evidence-based practice in nursing and midwifery is the application of findings that are statistically sound. Researchers with a good understanding of parameters, such as significance level, power, effect size, standard deviation and event rate, are enabled to calculate an informed sample size estimation and to report more clearly the rationale for applying any particular parameter value in sample size determination.
authors.affiliation: School of Nursing & Midwifery Trinity College Dublin, Republic of Ireland.
authors.forename: Helen Evelyn
authors.initials: HE
authors.lastname: Malone
authors.affiliation: School of Nursing & Midwifery Trinity College Dublin, Republic of Ireland.
authors.forename: Honor
authors.initials: H
authors.lastname: Nicholl
authors.affiliation: Trinity College Dublin, Republic of Ireland.
authors.forename: Imelda
authors.initials: I
authors.lastname: Coyne
mesh_terms: D012107:Research Design; D018401:Sample Size
keywords: effect size; power; quantitative research; sample size; significance level; standard deviation