I'm a little confused as to how to interpret the p-values in the model below, under "Fixed effects." I had two fixed effects (group and condition), group with three levels and condition with two. The three groups are EN, HS, and SB, and the two conditions are EN-GJT-R-GAP and EN-GJT-R-RES.

Under "Fixed Effects," I'm not sure what (Intercept) refers to? I thought the estimate referred to a difference between each parameter and the first one alphabetically (the one listed as (Intercept)), but here I have two different fixed effects, so does (Intercept) refer to groupEN or conditionEN-GJT-R-GAP? How could it simultaneously refer to both? And what do the estimates for groupHS, groupSB, and conditionEN-GJT-R-RES refer to? Also, what does the p-value for (Intercept) refer to? I thought that for the other ones (not (Intercept)), the p-values indicate the statistical significance of each parameter vis-à-vis the (Intercept), but again, how can this work if there are two different parameters the (Intercept) could refer to, and what does the p-value of the (Intercept) refer to if it's not being compared to anything else? Clearly I'm missing a lot of things, so any help would be vastly appreciated!

```
Linear mixed model fit by REML. t-tests use Satterthwaite's method ['lmerModLmerTest']
Formula: score ~ group + condition + (1 | subject) + (1 | token_set) + (1 | list)
Data: EN_JT_1
REML criterion at convergence: 521.2
Scaled residuals:
Min 1Q Median 3Q Max
-3.4748 -0.3124 0.2425 0.6686 1.8308
Random effects:
Groups Name Variance Std.Dev.
subject (Intercept) 2.170e-02 1.473e-01
token_set (Intercept) 3.147e-03 5.610e-02
list (Intercept) 1.319e-10 1.148e-05
Residual 9.288e-02 3.048e-01
Number of obs: 852, groups: subject, 71; token_set, 24; list, 2
Fixed effects:
Estimate Std. Error df t value Pr(>|t|)
(Intercept) 0.99723 0.03554 70.75609 28.056 < 2e-16 ***
groupHS -0.11226 0.04723 67.77282 -2.377 0.0203 *
groupSB 0.04257 0.05227 67.77205 0.814 0.4182
conditionEN-GJT-R-RES -0.27753 0.03099 21.38884 -8.955 1.1e-08 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Correlation of Fixed Effects:
(Intr) gropHS gropSB
groupHS -0.531
groupSB -0.480 0.361
cEN-GJT-R-R -0.436 0.000 0.000
optimizer (nloptwrap) convergence code: 0 (OK)
boundary (singular) fit: see ?isSingular
```