I am examining the direct causal effect of x on y.
Let's assume we a model as follows
y ~ x
Shows no significant effect of x on y. The reason may be that x variable has extreme values (5 data points) that should not be excluded from dataset (they are not measuring errors). The distributions of x and y variable variable are lognormal.
y ~ s(x)
Shows nonlinear significant effect of x on y
Thus, I should use splines since there is a nonlinear relationship between x and y? Is my understanding correct?
EDITED AFTER ANSWERS
Splines model has clearly better AIC. Plotting raw data and eyeballing these plots shows a similar non-linear relationship. I expect the relationship to be non-linear in real life/nature.