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Furthermore, since this model has two predictors, and cases are removed whenever at least one predictor is missing, there are also necessarily fewer cases available than for the two-level AR(1) model, which had only one predictor. The reason is that the lagged day-level predictor is, by definition, missing for the first day of each person (as well as in the possible case where a person has missing scores on the measurements for the entire previous day of the study). As before, the summary() [http://www.selleckchem.com/products/Imatinib-Mesylate.html Imatinib research buy] function is used to obtain the model results, which are shown in the lower part of Table ?Table2.2. For Neg1, the fixed day-level inertia was not significant [��010 = 0.10, t(50.7) = 1.7, p = 0.09], and the random effect for this inertia was not significant either [��(u01i) = 0.15, [http://www.selleckchem.com/products/VX-770.html Ivacaftor cell line] ��(3)2=4.6, p = 0.2]. However, after we removed the non-significant random effect from the model, the fixed effect estimate became larger and significant [��010 = 0.20, t(449) = 3.6, p [https://en.wikipedia.org/wiki/Oxymatrine Oxymatrine] for Pos1, ��010 = 0.28, t(70.8) = 5.5, p

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