Hello all,
I want to perform a structural equation modeling, path analyses. My question is at least how many participants do I need?
Thank you in advance.
Meryem Berrin BULUT
There are no restrictions for PLS path modeling. For other methods (like dwls, uls, Ml etc) , it differs according to the number of questions and dimensions.
Could you please give reference? I have a scale of 20 items, 13 items, 7 items and 18 items. How many participants do i need?
It seems that there are 58 questions in 4 different scales in total. I recommend you to use DWLS or GLS method if the distribution of your the data is notn-normal. In this case, you should collect at least 750 data according to my experience to get accurate results. If you prefer to use PLS, 250 participant would be suffice. However, this method (PLS) is less powerful because it is non-parametric.
you can find sample size requirements in this journal (For PLS-SEM):
Chin, W. W., “The Partial Least Squares
Approach for Structural Equation Modeling”,
Ed: G. A. Marcoulides, Modern Methods for
Business Research: 295-336. Lawrence
Erlbaum Associates, Hillsdale, New Jersey,
(1998).
you can find sample size requirements in this book (For SEM):
Confirmatory Factor Analysis for Applied Research, First Edition (Methodology in the Social Sciences
Also you can read following paragraph for Sample size:
(quotation= Structural Equation Modeling: Applications Using Mplus, Xiaoqian Wang, Jichuan Wang)
"Although determination of appropriate sample size is a critical issue in SEM, unfortunately, there is no consensus in the literatureregarding what would be the appropriate sample size for SEM. Some evidence exists that simple SEM models could be meaningfully tested even if sample size is quite small (Hoyle, 1999; Hoyle and Kenny, 1999; Marsh and Hau, 1999), but usually, N = 100–150 is considered the minimum sample size for conducting SEM (Tinsley and Tinsley, 1987; Anderson and Gerbing, 1988; Ding, Velicer, and Harlow, 1995; Tabachnick and Fidell, 2001). Some researchers consider an even larger sample size for SEM, for example, N = 200 (Hoogland and Boomsma 1998; Boomsma and Hoogland, 2001; Kline, 2005). Simulation studies show that with normally distributed indicator variables and no missing data, a reasonable sample size for a simple CFA model is about N = 150 (Muthén and Muthén, 2002). For multi-group modeling, the rule of thumb is 100 cases/observations per group (Kline, 2005).
Sample size is often considered in light of the number of observed variables. For normally distributed data, Bentler and Chou (1987) suggest a ratio as low as 5 cases per variable would be sufficient when latent variables have multiple indicators. A widely accepted rule of thumb is 10 cases/observations per indicator variable in setting a lower bound of an adequate sample size (Nunnally, 1967)."
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