The role of sample size in statistical inference - reject or accept H0 or
Ha. What should be the sample size (n) for a correct decision (minimum risk)?
Please let me know if the following references/sites are helpful to you:
1. Power and Sample Size Determination for Testing a Population ...
https://onlinecourses.science.psu.edu/stat500/node/46When the null hypothesis cannot be rejected, there are two possible cases: 1) one can accept the null hypothesis, 2) the sample size is not large enough to ...
2. Hypothesis Testing, Power, Sample Size and Confidence Intervals
...
http://biostat.mc.vanderbilt.edu/wiki/pub/Main/AnesShortCourse/HypothesisTestingPart1.pdfJun 3, 2010 ... Hypothesis Testing, Power, Sample Size and Confidence Intervals (Part 1). Outline. Introduction to hypothesis testing. Scientific and statistical ...
3. Sampling and sample size - MIT OpenCourseWare
https://ocw.mit.edu/resources/res-14-002-abdul-latif-jameel-poverty-action-lab-executive-training-evaluating-social-programs-2011-spring-2011/lecture-notes/MITRES_14_002S11_lec5.pdfIntro to the scientific method. • Hypothesis testing. • Statistical significance. • Factors that influence power. • Effect size. • Sample size. • Cluster randomized trials.
Dennis
Dennis Mazur
Hello!
There are good publications on samples size estimation and statistical power calculation for hypothesis testing. In brief, your estimated sample size depends on the magnitude of your expected effect, which is the difference between the mean values of your two compared groups divided by the standard deviation, your chosen significance level alpha, for example 0.05, and your chosen statistical power, e.g. 80%. Have a look at the attached publication.
http://www.sciencedirect.com/science/article/pii/S0022480404007279?via%3Dihub
Dr. Dennis Mazur - I have checked the links. Pages are not found.
Dr. Helena U Zacharias
Madam - The publication you indicated, no doubt good on the above topic.
Can you add a little bit more information as bullets for easy understanding?
Regards
As I described earlier, the required sample size depends on three variables:
* magnitude of expected effect: this is the difference in the mean values of the two groups you would expect (this magnitude could be, e.g. derived from other studies, literature, etc.) divided by the standard deviation of one group (under the assumption that both groups have the same standard deviation, otherwise you can use a pooled standard deviation)
* chosen significance level alpha, e.g. 0.05
* chosen statistical power (the power of a binary hypothesis test is the probability that the test correctly rejects the null hypothesis (H0) when the alternative hypothesis (H1) is true), e.g. 80%
You can easily determine the required sample size by using, e.g. g*power. Have a further look at the attached links, including a very good introduction to statistics in Nature.
https://www.nature.com/collections/qghhqm/pointsofsignificance
http://www.nature.com/nmeth/journal/v10/n12/pdf/nmeth.2738.pdf
http://www.gpower.hhu.de/
Dr.Helena
Madam - Thanks for providing good information. ResearchGate readers will be benefited.
Dear RG colleague,
Determining the sample sizes involve resource and statistical issues. Usually, researchers regard 100 participants as the minimum sample size when the population is large. However, In most studies the sample size is determined effectively by two factors: (1) the nature of data analysis proposed and (2) estimated response rate.
For example, if you plan to use a linear regression a sample size of 50+ 8K is required, where K is the number of predictors. Some researchers believes it is desirable to have at least 10 respondents for each item being tested in a factor analysis, Further, up to 300 responses is not unusual for Likert scale development according to other researchers.
Another method of calculating the required sample size is using the Power and Sample size program (www.power-analysis.com).
Regards,
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