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. Author manuscript; available in PMC: 2017 Nov 1.
Published in final edited form as: Soc Sci Res. 2016 Apr 4;60:297–310. doi: 10.1016/j.ssresearch.2016.04.002

Table 2.

Latent class growth analysis (LCGA) and latent class growth mixture model (LGMM) fit indices for sexual harassment.

Log likelihood Number of parameters BIC SSA
BIC		 Entropy Posterior possibilities Adjusted LMR test
LCGA models
  1 class −9113 7 18,282 18,260 – – –
  2 classes −8637 14 17,385 17,341 0.63 0.84/0.91 936.27 (p<0.01)
  3 classes −8550 21 17,269 17,202 0.57 0.77/0.70/0.85 168.84 (p = 0.22)
LGMM solution
  2 classes −8567 16 17,262 17,212 0.59 0.88/0.86 –
  2 classes + Roy drop out modela −8561 18 17,265 17,208 0.59 0.89/0.86 –

Bold values indicate lowest BIC or SSABIC value, or highest Log Likelihood, Entropy or Posterior possibilities value.

Note. The 2 class model was retained given the relative poorer fit according to Entropy, Posterior Possibilities and Adjusted LMR test. Additionally, although the Log Likelihood, BIC, and SSABIC were lower for the 3 class model, the relative drop in these fit indices was much greater when increasing the model from 1 to 2 classes vs. 2 to 3 classes.

a

The continuous intercept variance for the infrequent group was set at zero as the solution resulted in a negative variance (i.e., Heywood case). This variance was not significant in the LGMM solution, but was retained as model estimation terminated normally.