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. Author manuscript; available in PMC: 2020 Aug 7.
Published in final edited form as: Quant Method Psychol. 2019;15(2):96–111. doi: 10.20982/tqmp.15.2.p096

Table 3.

Monte Carlo Analyses of Unstandardized Coefficients (bs) for the Group Difference in Slopes for a Linear Latent Growth Model as a Function of Sample Size and Estimation Method

Monte Carlo Results Bias Estimates
N
SD
Avg
Coverage
SE
Percent
CI
Delta BTSP Delta BTSP Delta BTSP Delta BTSP Delta BTSP
50 .1258 .1216 .1250 .937 .942 −.0042 −.0008 3.34 .64 .013 .008
100 .0878 .0866 .0876 .943 .944 −.0012 −.0002 1.37 .23 .007 .006
150 .0720 .0708 .0713 .942 .943 −.0012 −.0007 1.67 .97 .008 .007
250 .0554 .0550 .0552 .947 .949 −.0004 −.0002 .72 .36 .003 .001
500 .0394 .0390 .0391 .945 .946 −.0004 −.0003 1.02 .76 .005 .004
Mdn .943 .944 1.37 .64 .007 .006

Note. Avg = average SE of b across replications, Coverage = 95% coverage for b, CI = 95% confidence interval, Delta = delta method, BTSP = bootstrap.. Unlike in Table 1, results are not reported separately for small and medium effect sizes because findings did not vary by effect size for b, and the equations approach is not applicable.