# Model 1 (single-trial data)
Hypothesis 1: Choice Behavior (single-trial analysis with logistic regression)
```r
# Model 1: Binary choice on each trial ~ effort +reward + trial number
# Syntax: glmer(choice ~ effort + reward + trial_number + (1|participant), family = binomial())
```
# Model 2 (condition-averaged data)
Hypothesis 2: Which effort processes do FMT power relate to?
## Model 2a (time-locked to choice evaluation)
```r
# Model 2a: FMT power (during choice evaluation) ~ effort + reward
# R syntax: lmer(fmtPow ~ effort + reward + (1 | participant))
```
## Model 2b (time-locked to choice production)
```r
# Model 2b: FMT power (during effort production) ~ effort + reward
# R syntax: lmer(fmtPow ~ effort + reward + (1 | participant))
```
# Model 3 (condition-averaged data)
Hypothesis 3: RewP amplitude will vary as a function of effort and reward levels.
```r
# Model 3a/3b: RewP amplitude ~ effort + reward
# R syntax: lmer(RewP ~ effort + reward + (1 | participant))
```
# Model 4 (condition-averaged data)
Hypothesis 4: Subjective value will be associated with trial-by-trial variations in FMT power, RewP amplitude (or delta power), and/or the FMT-RewP (or -delta) interactions (single-trial analysis).
In model 4 we will test whether trial-by-trial subjective value of effort offer (relative to the baseline choice) will vary as a function of trial-by-trial FMT power during choice evaluation, RewP amplitude (or delta power), and the interaction of FMT power and RewP amplitude (or delta power). We will examine whether a particular electrophysiological measure more strongly relate to variations in subjective values than another electrophysiological measure.
```r
# Model 4: Single-trial subjective value of high effort offer ~ single-trial FMT power + single-trial RewP amplitude (or delta power) + single-trial FMT power * RewP amplitude (or *delta power) interaction + trial number
# R syntax: lmer(subjective_value ~ fmtPow * RewP + trial number + (1 | participant))
```