Table 1.

Statistically Significant Effects of SES from the Best-Fitting Multilevel Linear Models of PLT by Analysis Window

Effect	Estimate	SE	t
TestWin-7 (1500–1750 ms after prompt)
Intercept	1.22	0.21	5.95
Higher-SES vs. Lower-SES	−0.41	0.17	−2.38
TestWin-8 (1750–2000 ms after prompt)
Intercept	0.98	0.13	7.52
Higher-SES vs. Lower-SES	−0.55	0.19	−2.87

The models presented are the best-fitting model for each time window; when effects or interactions do not appear, it is because adding them to the models did not reliably improve the fit. Formula in R – TestWin-7: DepVar ~ SES + Shape + (1 + Shape | Subject) + (1 | Rep Type); TestWin-8: DepVar ~ SES + (1 | Subject) + (1 | Rep Type). For the remaining 14 analysis windows, no models tested provided a better fit than an empty model with no fixed effects.