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Table 1 References for sample size calculation

From: When is enough, enough? Understanding and solving your sample size problems in health services research

Title Primer Concepts Sample size ROT Simulation
Some practical guidelines for effective sample size determination [2]    
Sample size calculations for the design of health studies: a review of key concepts for non-statisticians [1]    
Sample size calculations: basic principles and common pitfalls [15]    
Sample size: how many participants do I need in my research? [3]    
Using effect size–or why the P value is not enough [8]    
Statistics and ethics: some advice for young statisticians [16]      
Separated at birth: statisticians, social scientists and causality in health services research [17]      
Reporting the results of epidemiological studies [9]      
Surgical mortality as an indicator of hospital quality: the problem with small sample size [18]      
Do multiple outcome measures require p-value adjustment? [11]      
The problem of multiple inference in studies designed to generate hypothesis [19]      
Understanding power and rules of thumb for determining sample sizes [20]      
Statistical rules of thumb [21]      
A suggested statistical procedure for estimating the minimum sample size required for a complex cross-sectional study [22]    Complex cross-sectional   
A simple method of sample size calculation for liner and logistic regression [23]    Regression  
How many subjects does it take to do a regression analysis [10]    Regression  
Sample size determination in logistic regression [24]    Logistic regression  
A simulation study of the number of events per variable in a logistic regressions analysis [25]    Logistic regression  
Power and sample size calculations for studies involving linear regression [26]    Linear regression  
How to calculate sample size in randomized controlled trial? [27]    Randomised control trial  
Sufficient sample sizes for multilevel modelling [28]    Multilevel  
Sample size considerations for multilevel surveys [29]    Multilevel  
Sample size and accuracy of estimates in multilevel models: new simulation results [30]    Multilevel  
Robustness issues in multilevel regression analysis [31]    Multilevel  
  1. Primer =  basic paper on the concepts around sample size determination, provides a basic but important understanding. Concepts =  provides a more detailed explanation around specific aspects of sample size calculation. Sample size =  these papers provide examples of sample size calculation for specific analysis types. ROT =  these papers provide sample size ‘rules of thumb’ for one or more type of analysis. Simulation =  these papers report the results of sample size simulation for various types of analysis