11th Mar, 2022

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Asked 11th Sep, 2017

What is the justification of its validation?

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The sample size is calculated using a power analysis. A power analysis calculates, for varying sample sizes, a probability (power, β) of finding a statistically significant result (at chosen Type I error, α) for a given population effect size (Cohen, 1988).

1 Recommendation

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).

18 Recommendations

Hi,

You have many websites that propose to calculte sample size:

- http://www.raosoft.com/samplesize.html
- http://clincalc.com/stats/samplesize.aspx
- https://www.surveysystem.com/sscalc.htm

And here it is a paper answering to your second question: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2876926/

I hope that will help you,

Julian

The sample size must be 5 to 10 % of the popullation and in the case of a small population (less 100) all the population.

2 Recommendations

Which sample size is needed depend on the analyses you make, and which statistics you focus on. Different statistics from the same research implementatin may require different sample sizes.

If you ar using the Mplus program for you analyses (which are recommended, as this is a very, very flexible and easy program with a lot of support material), you can determine sample size using Monte Carlo techniques.

See: Muthén, L.K. & Muthén, B.O. (2002). How to use a Monte Carlo study to decide on sample size and determine power. *Structural Equation Modeling*, *4*, 599-620.

The following sources are also helpful:

- Burmeister, E. and Aitken, L. M. (2012). Sample size: How many is enough? Australian Critical Care, 25, 4, pp. 271-274.
- Lenth, R. V. (2001). Some Practical Guidelines for Effective Sample Size Determination. The American Statistician, 55, 3, pp. 187-193.
- Sample Size Calculation? : https://www.researchgate.net/post/Sample_Size_Calculation

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).

18 Recommendations

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).

1 Recommendation

This formula is the easiest way to do it.

- 86.61 KBFormula.jpg
- 144.96 KBHow to calculate.jpg

2 Recommendations

Dear **Md. Ashraf Uzzaman** ,

Go to http://www.raosoft.com/samplesize.html and you get immediately the sample you need.

Bests,

Igor Gurkov

15 Recommendations

Awesome information. Another helpful calculation table can be found at https://www.surveysystem.com/sscalc.htm

1 Recommendation

The problem with calculations as the above mentioned is that required sample sizes are different for different types of analyses, and for different types of effects.

In serious research you need to specify the analysis and make the required sample size calculations accordingly.

Hello everyone. I would have a question if you can please help. What would be the most representative sample or the best method to calculate this sample if I want to analyze the impact of Social Media in Tourism among Generation Y who are let's say approximately 3.5 million people? Thanks!

Alma Braimllari Spaho could you please explain why 5 to 10 % is a good sample? I don't seem to be able to find any literature on this regard. Thank you!

Bruce Neagle do you have the link to that discussion by chance? Thank you!

Hi i m following mixed methodology , i will do survey and semi structure interview, whats the sample size should be ?

2 Recommendations

Simply, the sample size is related to the accuracy of the result you require. If you require 1% accuracy on the 'true' mean value then you'll need 10000 (random) participants, particles, experiments etc. The standard error is inversely proportional to the square of the number (of whatevers). Or the number of experiments, participants etc is inversely proportion to the variance (or the standard error squared).

Amee Joan For 0.01 (1%) standard error on the mean you'll need to sample them all. For 0.05 (5%) then 1/20^{2} or 400 is a good guideline and in line with Akarsu Bayram above.

2 Recommendations

Alan F Rawle Thank you

Akarsu Bayram Thank you

1 Recommendation

For PLS-SEM, better to go for 200 samples for statistical significance. However, it does not matter all the time as 10 time rule is applicable for PLS-SEM, that supports for relatively a smaller sample size.

For covariance based SEM does need at least 300 samples for a decent statistical significance.

2 Recommendations

Results of regression analysis shows that overall **67%** teachers’ self-efficacy have effected on students’ academic achievements, while sub-factor: students’ engagement 58%, instructional strategies 65% and classroom management have affected 60% on students’ achievement scores. Why there is so variations in effect when we sum 58+65+60= 183/3=61 %, why it is not **67%?**

2 Recommendations

Can we go with 50 respondents for quantitative survey? Will it be valid for statistical result?

3 Recommendations

am in a similar position, I want to do something based on primary teachers but am not in a position to survey all of the primary teachers in the area due to logistics. Am looking at 100-150 for a 24 item quantitative survey. Not enough people?

2 Recommendations

Adnan Majeed Thank you

1 Recommendation

Sample Size Rule

Sekaran (2013) wrote:

"*Roscoe (1975) proposes the following rules of thumb for determining sample size:*

Sekaran, U., 2003. Research methods for business: A skill building approach. John Wiley & Sons.

13 Recommendations

As I recall the AOAC (Association of Official Analytical Chemists) had a statistical guide for sample size and analysis.

3 Recommendations

Use this method. http://www.raosoft.com/samplesize.html

2 Recommendations

You the below link http://www.raosoft.com/samplesize.html

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