prepost_stan: Processed data from experiment ALEXIS 108. For creating...
In stamnosslin/alexis108: Data from Experiment on Discrimination Suppression

Description Usage Format

Threshold estimates derived from data108 using Bayesian inference and Hamiltonian Monte Carlo.

1	prepost_stan

A data frame with 13 rows and 16 colums.

ici: Inter-click interval in ms, Note: -1 is for sessions with no lead click
thmode_pre: Threshold estimate first 10 days, i.e., stimulus level at 75 % corrrect responses. The estimate is the mode of the posterior distribution
hdi95pre_lo: Lower 95 estimates from the first 10 days
hdi95pre_hi: Upper 95 estimates from the first 10 days
thmode_post: Threshold estimate last 10 days, i.e., stimulus level at 75 % corrrect responses. The estimate is the mode of the posterior distribution
hdi95pre_lo: Lower 95 % Highest posterior density interval for threshold estimates from the last 10 days
hdi95pre_hi: Upper 95 % Highest posterior density interval for threshold estimates from the last 10 days
thdiff: Threshold difference last 10 - first 10 dyas. The estimate is the mode of the posterior distribution of threshold differences
hdi95diff_lo: Lower 95 % Highest posterior density interval for threshold difference
hdi95diff_hi: Upper 95 % Highest posterior density interval for threshold difference
wmode_pre: Spread of psychometric function. The estimate is the mode of the posterior distribution
wmode_post: Lapse rate (parameter lambda) of psychometric function. The estimate is the mode of the posterior distribution
lapsemdn_pre: Lapse rate (parameter lambda) of psychometric function for first 10 days. The estimate is the mode of the posterior distribution
lapsemdn_post: Lapse rate (parameter lambda) of psychometric function for last 10 days. The estimate is the mode of the posterior distribution
min_neff: Diagnostics: The minimum n_eff value for the estimated parameters (high values are good)
maxR: Diagnostics: The maximum Rhat value for the estimated parameters (values should be very close to 1)