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.
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).
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).
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!
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 1/202 or 400 is a good guideline and in line with Akarsu Bayram above.