title: Sample size requirements for interval estimation of the strength of association effect sizes in multiple regression analysis.
abstract: BACKGROUND
  Effect size reporting and interpreting practices have been extensively recommended in academic journals when analyzing primary outcomes of all empirical studies. Accordingly, the sample squared multiple correlation coefficient is the commonly reported strength of association index in practical applications of multiple linear regression.
  
  
  METHODS
  This paper examines the sample size procedures proposed by Bonett and Wright for precise interval estimation of the squared multiple correlation coefficient.
  
  
  RESULTS
  The simulation results showed that their simple method for attaining the desired precision of expected width provides satisfactory results only when sample sizes are large. Moreover, the suggested sample size formula for achieving the designated assurance probability is inaccurate and problematic.
  
  
  CONCLUSIONS
  According to these findings, their sample size procedures are not recommended.
authors.affiliation: Department of Management Science and Institute of Statistics, National Chiao Tung University, Hsinchu, Taiwán. gwshieh@mail.nctu.edu.tw
authors.forename: Gwowen
authors.initials: G
authors.lastname: Shieh
mesh_terms: D016001:Confidence Intervals; D015999:Multivariate Analysis; D012044:Regression Analysis; D018401:Sample Size