Thank you - I am joining SEMNET; it appears to have the information I seek. DW --- [EMAIL PROTECTED] wrote: > : On 18 Jun 2003 15:08:24 -0700, > [EMAIL PROTECTED] (Dianne Worth) > : wrote: > > :> My next question is this: > :> Rather than multiple regression, I want to use > structural equation > :> modeling. The sample is < 250, which I've been > told is not large > :> enough for LISREL. The alternative software uses > partial least > > The issue of sample size for SEM is rather confusing > (to me, at least). > The number 200 (or 250?) gets thrown around a lot, I > think, because of an > early paper by Boomsma which showed that there are > convergence problems in > a certain type of model when N < 200. > > There are many more things to consider, however, > when determining the > appropriate sample size for SEM, not the least of > which include the > distribution of the observed variables, the number > of indicators per > latent variable, power considerations. Below I've > reproduced an excellent > brief summary of the literature that a PhD student > in Norway posted to > the SEM listserv some time back. I'm sure you'll > find more than this > if you search the SEMNET archives at > > http://bama.ua.edu/archives/semnet.html > > Mike Babyak > > >>> Joar Vittersx <[EMAIL PROTECTED]> > 01/29/98 08:34am >>> > SEMNETTERS > > Bentler & Chou (1987) suggested that a ratio as low > as 5 subjects per > parameter would be sufficient if the data are > normally distributed: > "The ratio of sample size to the number of free > parameters may be able > to go as low as 5:1 under normal and elliptical > theory, especially when > there are many indicators of the latent variable and > the associated > loadings are large." (p.173). If the data are not > normally distributed, > on the other hand, a sample size of 5000 subjects > may sometimes be > needed (Hu & Bentler, 1995) In general, Anderson > and Gerbing argues > that a sample size of 150 or more typically will be > needed to obtain > parameter estimates that have standard errors small > enough to be of > practical use (Anderson & Gerbing, 1988, p. 415). > Boomsma (1982) found > that sample sizes of 100 to be accurate under ML > estimation with normal > data. In a series of Monte Carlos studies with > sample sizes between 150 > and 1000, Finch, West & MacKinnon (1997) found that > estimates of model > parameters were generally unaffected by sample size. > Barrett & Kline > (1981), using real data, reported that a minimum of > 50 subjects were > the minimum needed to reproduce the factor pattern > of the Sixteen > Personality Factor Questionnaire. Finally, sample > size as a function of > the number of variables was not found to be an > important factor in > determining stability in structural equation > modeling in a study by > Guadagnoli & Velicer (1988). In this study, the > sample sizes varied > from 50 to 1000 and the number of variables ranged > from 36 to 144. > Component saturation and absolute sample size were > found to be the most > important factors, and with high component > saturation (i.e. factor > loadings of .80) solutions were stable across > replicated samples > regardless of the number of indicators, even with as > few as 50 > participants. With factor loadings of .60, a sample > size of 150 should > be sufficient to obtain an accurate solution. > > References > Anderson, J. C., & Gerbing, D. W. (1988). > Structural Equation modeling > in practice : A review and recommended two-step > approach. Psychological > Bulletin, 103(3), 411-423. > > Barrett, P. T., & Kline, P. (1981). The observation > to variable ratio > in factor analysis. Personality Study and Group > Behavior, 1, 23-33. > > Bentler, P. M., & Chou, C. (1987). Practical issues > in structural > modelling. Socialogocal Methods and Research, 16, > 78-117. > > Boomsma, A. (1982). The robustness of LISREL > against smal sample size > in factor analysis models. In K. G. J�reskog & H. > Wold (Eds.), Systems > under indirect observaion, Part 1 (pp. 149-173). > Amsterdam: > North-Holland. > > Finch, J. F., West, S. G., & MacKinnon, D. P. > (1997). Effects of sample > size and nonnormality on the estimation of mediated > effects in latent > variable models. Structural Equation Modeling, 4(2), > 87-107. > > Guadagnoli, E., & Velicer, W. F. (1988). Relation > of sample size to the > stability of component patterns. Psychological > Bulletin, 103(2), > 265-275. > > Hu, L.-T., & Bentler, P. (1995). Evaluating model > fit. In R. H. Hoyle > (Ed.), Structural Equation Modeling. Concepts, > Issues, and Applications > . London: Sage. > > > . > . > ================================================================= > Instructions for joining and leaving this list, > remarks about the > problem of INAPPROPRIATE MESSAGES, and archives are > available at: > . http://jse.stat.ncsu.edu/ > . > =================================================================
__________________________________ Do you Yahoo!? SBC Yahoo! DSL - Now only $29.95 per month! http://sbc.yahoo.com . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
