Contents
What is the minimum sample size for reliability test?
The RCSI sample size handbook: a rough guide Conroy R (2016) This study summarized that sample size of 30 can measure reliability using Cronbach’s alpha considering the scale items have strong correlations. Therefore, the minimum sample size required for this case study is approximately 68 samples per group.
How big should Cronbach alpha be?
The general rule of thumb is that a Cronbach’s alpha of . 70 and above is good, . 80 and above is better, and . 90 and above is best.
How many items are needed for Cronbach’s alpha?
To compute Cronbach’s alpha for all four items – q1, q2, q3, q4 – use the reliability command: RELIABILITY /VARIABLES=q1 q2 q3 q4.
Is Cronbach Alpha necessary?
With only two items, standardized to have equal standard deviations (z-scored), there’s no need to use software to obtain the alpha value; alpha in that case will equal the square of the correlation between the items.
What is the minimum sample size for Cronbach’s coefficient alpha?
The general view on this subject is that the sample coefficient alpha obtained from larger samples tends to produce a more accurate estimate of the population coefficient alpha. In reliability literature, Kline (1986) suggested a minimum sample size of 300, as did Nunnally and Bernstein (1994).
How does sample size affect the coefficient alpha?
This research indicates that the performance of an estimator of the coefficient alpha depends not only on the sample size but also on the largest eigenvalue of the sample data set. Thus, when the largest eigenvalue increases, unbiased estimation of the population coefficient alpha is possible, even though the sample size is small.
When to use unbiased estimation of population coefficient alpha?
Thus, when the largest eigenvalue increases, unbiased estimation of the population coefficient alpha is possible, even though the sample size is small. The simulations in this study were based on Monte-Carlo method with bootstrap technique.