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Modèle nonlinéaire à processus latent 73Nonlinear Model with Latent Process for Cognitive Evolution 10210.60.5(a)ε4 non carrierε4 carrierlatent process0.40.30.20.13028065 70 75 80 85 90 95age in years(b)3432263028MMSE2422IST2624222020N=252 N=546 N=692 N=546 N=299 N=99 1818N=249 N=540 N=673 N=521 N=273 N=8065 70 75 80 85 90 9565 70 75 80 85 90 95age in yearsage in years134012351130BVRT10DSSTW2592087N=252 N=542 N=670 N=497 N=254 N=5765 70 75 80 85 90 95age in years15N=179 N=360 N=518 N=379 N=183 N=3465 70 75 80 85 90 95age in yearsFigure 4. (a) Predicted mean evolution for the latent process for ɛ4 carriers and for ɛ4 noncarriers. (b) Estimated andobserved mean evolutions for each test with the number of subjects used for the computation of each observed mean (solidline with crosses = observed mean evolution; solid line with dots = estimated marginal mean evolution; dashed line with dots =estimated subject-specific mean evolution; dashed line = 95% confidence interval of the observed mean).cognitive level tended to refuse the other tests and particularlythe DSSTW, which is more difficult. Missing data arethus associated with random effects. For instance, the meanof subject-specific deviations Ŵijk is −0.0037 for subjects aged90 or more who completed the MMSE (N = 99), and 0.028,0.042, and 0.056, respectively, for those who completed theIST (N = 80), BVRT (N = 57), and DSSTW (N = 34). Theimpact of missing data on conditional and marginal estimates