"Power and sample size estimations are measures of how many patients are needed in a study. Nearly all clinical studies entail studying a sample of patients with a particular characteristic rather than the whole population. We then use this sample to draw inferences about the whole population."
Reference: Jones SR, Carley S, Harrison Man introduction to power and sample size estimation. Emergency Medicine Journal 2003;20:453-458.
The references in this section will help you calculate what is a minimum adequate sample for your study to draw valid conclusions.
Statistics and Data Interpretation for Social Work by 
Statistical Analysis of Clinical Data on a Pocket Calculator, Part 2 by 
Using Statistics in the Social and Health Sciences with SPSS and Excel by 
Statistical Analysis of Clinical Data on a Pocket Calculator by 
Sampling by 
Sampling by 
Sampling by 
Pensampelan : panduan asas penyelidik by 
Statistical tests for your quantitative research project by 
Quantitative Research Methods for Communication by 
Introduction to Statistics by 
A Crash Course in Statistics by 
Statistics, Data Analysis, and Decision Modeling by 
Applied Survey Data Analysis by 
Nonparametric Methods in Statistics with SAS Applications by
1. Jones SR, Carley S, Harrison M. An introduction to power and sample size estimation. Emergency Medicine Journal 2003;20:453-458. https://emj.bmj.com/content/20/5/453 (FREE)
2. Online sample size calculator for clinical research: https://www.openepi.com/Menu/OE_Menu.htm
3. Suen LJ, Huang HM, Lee HH. [A comparison of convenience sampling and purposive sampling]. Hu Li Za Zhi. 2014 Jun;61(3):105-11. Chinese. doi: 10.6224/JN.61.3.105. PMID: 24899564. https://pubmed.ncbi.nlm.nih.gov/24899564/
4. Guerra Valero YC, Wallis SC, Lipman J, Stove C, Roberts JA, Parker SL. Clinical application of microsampling versus conventional sampling techniques in the quantitative bioanalysis of antibiotics: a systematic review. Bioanalysis. 2018 Mar;10(6):407-423. doi: 10.4155/bio-2017-0269. Epub 2018 Feb 16. PMID: 29451394. https://pubmed.ncbi.nlm.nih.gov/29451394/
5. Tanna S, Lawson G. Self-sampling and quantitative analysis of DBS: can it shift the balance in over-burdened healthcare systems? Bioanalysis. 2015;7(16):1963-6. doi: 10.4155/bio.15.110. PMID: 26327176. https://pubmed.ncbi.nlm.nih.gov/26327176/
6. Li H, Han J, Pan J, Liu T, Parker CE, Borchers CH. Current trends in quantitative proteomics - an update. J Mass Spectrom. 2017 May;52(5):319-341. doi: 10.1002/jms.3932. PMID: 28418607. https://pubmed.ncbi.nlm.nih.gov/28418607/
7. Trevelin LC, Novaes RL, Colas-Rosas PF, Benathar TC, Peres CA. Enhancing sampling design in mist-net bat surveys by accounting for sample size optimization. PLoS One. 2017 Mar 23;12(3):e0174067. doi: 10.1371/journal.pone.0174067. PMID: 28334046; PMCID: PMC5363843. https://pubmed.ncbi.nlm.nih.gov/28334046/
